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Sample records for surface emg classification

  1. Simultaneous Force Regression and Movement Classification of Fingers via Surface EMG within a Unified Bayesian Framework.

    Science.gov (United States)

    Baldacchino, Tara; Jacobs, William R; Anderson, Sean R; Worden, Keith; Rowson, Jennifer

    2018-01-01

    This contribution presents a novel methodology for myolectric-based control using surface electromyographic (sEMG) signals recorded during finger movements. A multivariate Bayesian mixture of experts (MoE) model is introduced which provides a powerful method for modeling force regression at the fingertips, while also performing finger movement classification as a by-product of the modeling algorithm. Bayesian inference of the model allows uncertainties to be naturally incorporated into the model structure. This method is tested using data from the publicly released NinaPro database which consists of sEMG recordings for 6 degree-of-freedom force activations for 40 intact subjects. The results demonstrate that the MoE model achieves similar performance compared to the benchmark set by the authors of NinaPro for finger force regression. Additionally, inherent to the Bayesian framework is the inclusion of uncertainty in the model parameters, naturally providing confidence bounds on the force regression predictions. Furthermore, the integrated clustering step allows a detailed investigation into classification of the finger movements, without incurring any extra computational effort. Subsequently, a systematic approach to assessing the importance of the number of electrodes needed for accurate control is performed via sensitivity analysis techniques. A slight degradation in regression performance is observed for a reduced number of electrodes, while classification performance is unaffected.

  2. EMG finger movement classification based on ANFIS

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    Caesarendra, W.; Tjahjowidodo, T.; Nico, Y.; Wahyudati, S.; Nurhasanah, L.

    2018-04-01

    An increase number of people suffering from stroke has impact to the rapid development of finger hand exoskeleton to enable an automatic physical therapy. Prior to the development of finger exoskeleton, a research topic yet important i.e. machine learning of finger gestures classification is conducted. This paper presents a study on EMG signal classification of 5 finger gestures as a preliminary study toward the finger exoskeleton design and development in Indonesia. The EMG signals of 5 finger gestures were acquired using Myo EMG sensor. The EMG signal features were extracted and reduced using PCA. The ANFIS based learning is used to classify reduced features of 5 finger gestures. The result shows that the classification of finger gestures is less than the classification of 7 hand gestures.

  3. Comparative study of PCA in classification of multichannel EMG signals.

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    Geethanjali, P

    2015-06-01

    Electromyographic (EMG) signals are abundantly used in the field of rehabilitation engineering in controlling the prosthetic device and significantly essential to find fast and accurate EMG pattern recognition system, to avoid intrusive delay. The main objective of this paper is to study the influence of Principal component analysis (PCA), a transformation technique, in pattern recognition of six hand movements using four channel surface EMG signals from ten healthy subjects. For this reason, time domain (TD) statistical as well as auto regression (AR) coefficients are extracted from the four channel EMG signals. The extracted statistical features as well as AR coefficients are transformed using PCA to 25, 50 and 75 % of corresponding original feature vector space. The classification accuracy of PCA transformed and non-PCA transformed TD statistical features as well as AR coefficients are studied with simple logistic regression (SLR), decision tree (DT) with J48 algorithm, logistic model tree (LMT), k nearest neighbor (kNN) and neural network (NN) classifiers in the identification of six different movements. The Kruskal-Wallis (KW) statistical test shows that there is a significant reduction (P PCA transformed features compared to non-PCA transformed features. SLR with non-PCA transformed time domain (TD) statistical features performs better in accuracy and computational power compared to other features considered in this study. In addition, the motion control of three drives for six movements of the hand is implemented with SLR using TD statistical features in off-line with TMSLF2407 digital signal controller (DSC).

  4. A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

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    Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

    2016-08-01

    Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

  5. [Detection of surface EMG signal using active electrode].

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    He, Qinghua; Peng, Chenglin; Wu, Baoming; Wang, He

    2003-09-01

    Research of surface electromyogram(EMG) signal is important in rehabilitation medicine, sport medicine and clinical diagnosis, accurate detection of signal is the base of quantitative analysis of surface EMG signal. In this article were discussed how to reduce possible noise in the detection of surface EMG. Considerations on the design of electrode unit were presented. Instrumentation amplifier AD620 was employed to design a bipolar active electrode for use in surface EMG detection. The experiments showed that active electrode could be used to improve signal/noise ratio, reduce noise and detect surface EMG signal effectively.

  6. Long-term surface EMG monitoring using K-means clustering and compressive sensing

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    Balouchestani, Mohammadreza; Krishnan, Sridhar

    2015-05-01

    In this work, we present an advanced K-means clustering algorithm based on Compressed Sensing theory (CS) in combination with the K-Singular Value Decomposition (K-SVD) method for Clustering of long-term recording of surface Electromyography (sEMG) signals. The long-term monitoring of sEMG signals aims at recording of the electrical activity produced by muscles which are very useful procedure for treatment and diagnostic purposes as well as for detection of various pathologies. The proposed algorithm is examined for three scenarios of sEMG signals including healthy person (sEMG-Healthy), a patient with myopathy (sEMG-Myopathy), and a patient with neuropathy (sEMG-Neuropathr), respectively. The proposed algorithm can easily scan large sEMG datasets of long-term sEMG recording. We test the proposed algorithm with Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) dimensionality reduction methods. Then, the output of the proposed algorithm is fed to K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers in order to calclute the clustering performance. The proposed algorithm achieves a classification accuracy of 99.22%. This ability allows reducing 17% of Average Classification Error (ACE), 9% of Training Error (TE), and 18% of Root Mean Square Error (RMSE). The proposed algorithm also reduces 14% clustering energy consumption compared to the existing K-Means clustering algorithm.

  7. The effect of time on EMG classification of hand motions in able-bodied and transradial amputees

    DEFF Research Database (Denmark)

    Waris, Asim; Niazi, Imran Khan; Jamil, Mohsin

    2018-01-01

    While several studies have demonstrated the short-term performance of pattern recognition systems, long-term investigations are very limited. In this study, we investigated changes in classification performance over time. Ten able-bodied individuals and six amputees took part in this study. EMG s...... difference between training and testing day increases. Furthermore, for iEMG, performance in amputees was directly proportional to the size of the residual limb.......While several studies have demonstrated the short-term performance of pattern recognition systems, long-term investigations are very limited. In this study, we investigated changes in classification performance over time. Ten able-bodied individuals and six amputees took part in this study. EMG...... was computed for all possible combinations between the days. For all subjects, surface sEMG (7.2 ± 7.6%), iEMG (11.9 ± 9.1%) and cEMG (4.6 ± 4.8%) were significantly different (P 

  8. Reliability of surface EMG measurements from the suprahyoid muscle complex

    DEFF Research Database (Denmark)

    Kothari, Mohit; Stubbs, Peter William; Pedersen, Asger Roer

    2017-01-01

    of using the suprahyoid muscle complex (SMC) using surface electromyography (sEMG) to assess changes to neural pathways by determining the reliability of measurements in healthy participants over days. Methods: Seventeen healthy participants were recruited. Measurements were performed twice with one week...... on stimulus type/intensity) had significantly different MEP values between day 1 and day 2 for single pulse and paired pulse TMS. A large stimulus artefact resulted in MEP responses that could not be assessed in four participants. Conclusions: The assessment of the SMC using sEMG following TMS was poorly...... reliable for ≈50% of participants. Although using sEMG to assess swallowing musculature function is easier to perform clinically and more comfortable to patients than invasive measures, as the measurement of muscle activity using TMS is unreliable, the use of sEMG for this muscle group is not recommended...

  9. Surface EMG signals based motion intent recognition using multi-layer ELM

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    Wang, Jianhui; Qi, Lin; Wang, Xiao

    2017-11-01

    The upper-limb rehabilitation robot is regard as a useful tool to help patients with hemiplegic to do repetitive exercise. The surface electromyography (sEMG) contains motion information as the electric signals are generated and related to nerve-muscle motion. These sEMG signals, representing human's intentions of active motions, are introduced into the rehabilitation robot system to recognize upper-limb movements. Traditionally, the feature extraction is an indispensable part of drawing significant information from original signals, which is a tedious task requiring rich and related experience. This paper employs a deep learning scheme to extract the internal features of the sEMG signals using an advanced Extreme Learning Machine based auto-encoder (ELMAE). The mathematical information contained in the multi-layer structure of the ELM-AE is used as the high-level representation of the internal features of the sEMG signals, and thus a simple ELM can post-process the extracted features, formulating the entire multi-layer ELM (ML-ELM) algorithm. The method is employed for the sEMG based neural intentions recognition afterwards. The case studies show the adopted deep learning algorithm (ELM-AE) is capable of yielding higher classification accuracy compared to the Principle Component Analysis (PCA) scheme in 5 different types of upper-limb motions. This indicates the effectiveness and the learning capability of the ML-ELM in such motion intent recognition applications.

  10. Preferred sensor sites for surface EMG signal decomposition

    International Nuclear Information System (INIS)

    Zaheer, Farah; Roy, Serge H; De Luca, Carlo J

    2012-01-01

    Technologies for decomposing the electromyographic (EMG) signal into its constituent motor unit action potential trains have become more practical by the advent of a non-invasive methodology using surface EMG (sEMG) sensors placed on the skin above the muscle of interest (De Luca et al 2006 J. Neurophysiol. 96 1646–57 and Nawab et al 2010 Clin. Neurophysiol. 121 1602–15). This advancement has widespread appeal among researchers and clinicians because of the ease of use, reduced risk of infection, and the greater number of motor unit action potential trains obtained compared to needle sensor techniques. In this study we investigated the influence of the sensor site on the number of identified motor unit action potential trains in six lower limb muscles and one upper limb muscle with the intent of locating preferred sensor sites that provided the greatest number of decomposed motor unit action potential trains, or motor unit yield. Sensor sites rendered varying motor unit yields throughout the surface of a muscle. The preferred sites were located between the center and the tendinous areas of the muscle. The motor unit yield was positively correlated with the signal-to-noise ratio of the detected sEMG. The signal-to-noise ratio was inversely related to the thickness of the tissue between the sensor and the muscle fibers. A signal-to-noise ratio of 3 was found to be the minimum required to obtain a reliable motor unit yield. (paper)

  11. Real-time intelligent pattern recognition algorithm for surface EMG signals

    Directory of Open Access Journals (Sweden)

    Jahed Mehran

    2007-12-01

    Full Text Available Abstract Background Electromyography (EMG is the study of muscle function through the inquiry of electrical signals that the muscles emanate. EMG signals collected from the surface of the skin (Surface Electromyogram: sEMG can be used in different applications such as recognizing musculoskeletal neural based patterns intercepted for hand prosthesis movements. Current systems designed for controlling the prosthetic hands either have limited functions or can only be used to perform simple movements or use excessive amount of electrodes in order to achieve acceptable results. In an attempt to overcome these problems we have proposed an intelligent system to recognize hand movements and have provided a user assessment routine to evaluate the correctness of executed movements. Methods We propose to use an intelligent approach based on adaptive neuro-fuzzy inference system (ANFIS integrated with a real-time learning scheme to identify hand motion commands. For this purpose and to consider the effect of user evaluation on recognizing hand movements, vision feedback is applied to increase the capability of our system. By using this scheme the user may assess the correctness of the performed hand movement. In this work a hybrid method for training fuzzy system, consisting of back-propagation (BP and least mean square (LMS is utilized. Also in order to optimize the number of fuzzy rules, a subtractive clustering algorithm has been developed. To design an effective system, we consider a conventional scheme of EMG pattern recognition system. To design this system we propose to use two different sets of EMG features, namely time domain (TD and time-frequency representation (TFR. Also in order to decrease the undesirable effects of the dimension of these feature sets, principle component analysis (PCA is utilized. Results In this study, the myoelectric signals considered for classification consists of six unique hand movements. Features chosen for EMG signal

  12. An implementation of movement classification for prosthesis control using custom-made EMG system

    Directory of Open Access Journals (Sweden)

    Mejić Luka

    2017-01-01

    Full Text Available Electromyography (EMG is a well known technique used for recording electrical activity produced by human muscles. In the last few decades, EMG signals are used as a control input for prosthetic hands. There are several multifunctional myoelectric prosthetic hands for amputees on the market, but so forth, none of these devices permits the natural control of more than two degrees of freedom. In this paper we present our implementation of the pattern classification using custom made components (electrodes and an embedded EMG amplifier. The components were evaluated in offline and online tests, in able bodied as well as amputee subjects. This type of control is based on computing the time domain features of the EMG signals recorded from the forearm and using these features as input for a Linear Discriminant Analysis (LDA classifier estimating the intention of the prosthetic user. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. III - 41007

  13. Surface EMG in advanced hand prosthetics.

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    Castellini, Claudio; van der Smagt, Patrick

    2009-01-01

    One of the major problems when dealing with highly dexterous, active hand prostheses is their control by the patient wearing them. With the advances in mechatronics, building prosthetic hands with multiple active degrees of freedom is realisable, but actively controlling the position and especially the exerted force of each finger cannot yet be done naturally. This paper deals with advanced robotic hand control via surface electromyography. Building upon recent results, we show that machine learning, together with a simple downsampling algorithm, can be effectively used to control on-line, in real time, finger position as well as finger force of a highly dexterous robotic hand. The system determines the type of grasp a human subject is willing to use, and the required amount of force involved, with a high degree of accuracy. This represents a remarkable improvement with respect to the state-of-the-art of feed-forward control of dexterous mechanical hands, and opens up a scenario in which amputees will be able to control hand prostheses in a much finer way than it has so far been possible.

  14. Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders.

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    Subasi, Abdulhamit

    2013-06-01

    Support vector machine (SVM) is an extensively used machine learning method with many biomedical signal classification applications. In this study, a novel PSO-SVM model has been proposed that hybridized the particle swarm optimization (PSO) and SVM to improve the EMG signal classification accuracy. This optimization mechanism involves kernel parameter setting in the SVM training procedure, which significantly influences the classification accuracy. The experiments were conducted on the basis of EMG signal to classify into normal, neurogenic or myopathic. In the proposed method the EMG signals were decomposed into the frequency sub-bands using discrete wavelet transform (DWT) and a set of statistical features were extracted from these sub-bands to represent the distribution of wavelet coefficients. The obtained results obviously validate the superiority of the SVM method compared to conventional machine learning methods, and suggest that further significant enhancements in terms of classification accuracy can be achieved by the proposed PSO-SVM classification system. The PSO-SVM yielded an overall accuracy of 97.41% on 1200 EMG signals selected from 27 subject records against 96.75%, 95.17% and 94.08% for the SVM, the k-NN and the RBF classifiers, respectively. PSO-SVM is developed as an efficient tool so that various SVMs can be used conveniently as the core of PSO-SVM for diagnosis of neuromuscular disorders. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. EOG and EMG: two important switches in automatic sleep stage classification.

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    Estrada, E; Nazeran, H; Barragan, J; Burk, J R; Lucas, E A; Behbehani, K

    2006-01-01

    Sleep is a natural periodic state of rest for the body, in which the eyes are usually closed and consciousness is completely or partially lost. In this investigation we used the EOG and EMG signals acquired from 10 patients undergoing overnight polysomnography with their sleep stages determined by expert sleep specialists based on RK rules. Differentiation between Stage 1, Awake and REM stages challenged a well trained neural network classifier to distinguish between classes when only EEG-derived signal features were used. To meet this challenge and improve the classification rate, extra features extracted from EOG and EMG signals were fed to the classifier. In this study, two simple feature extraction algorithms were applied to EOG and EMG signals. The statistics of the results were calculated and displayed in an easy to visualize fashion to observe tendencies for each sleep stage. Inclusion of these features show a great promise to improve the classification rate towards the target rate of 100%

  16. Multi-step EMG Classification Algorithm for Human-Computer Interaction

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    Ren, Peng; Barreto, Armando; Adjouadi, Malek

    A three-electrode human-computer interaction system, based on digital processing of the Electromyogram (EMG) signal, is presented. This system can effectively help disabled individuals paralyzed from the neck down to interact with computers or communicate with people through computers using point-and-click graphic interfaces. The three electrodes are placed on the right frontalis, the left temporalis and the right temporalis muscles in the head, respectively. The signal processing algorithm used translates the EMG signals during five kinds of facial movements (left jaw clenching, right jaw clenching, eyebrows up, eyebrows down, simultaneous left & right jaw clenching) into five corresponding types of cursor movements (left, right, up, down and left-click), to provide basic mouse control. The classification strategy is based on three principles: the EMG energy of one channel is typically larger than the others during one specific muscle contraction; the spectral characteristics of the EMG signals produced by the frontalis and temporalis muscles during different movements are different; the EMG signals from adjacent channels typically have correlated energy profiles. The algorithm is evaluated on 20 pre-recorded EMG signal sets, using Matlab simulations. The results show that this method provides improvements and is more robust than other previous approaches.

  17. Self-Recalibrating Surface EMG Pattern Recognition for Neuroprosthesis Control Based on Convolutional Neural Network.

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    Zhai, Xiaolong; Jelfs, Beth; Chan, Rosa H M; Tin, Chung

    2017-01-01

    Hand movement classification based on surface electromyography (sEMG) pattern recognition is a promising approach for upper limb neuroprosthetic control. However, maintaining day-to-day performance is challenged by the non-stationary nature of sEMG in real-life operation. In this study, we propose a self-recalibrating classifier that can be automatically updated to maintain a stable performance over time without the need for user retraining. Our classifier is based on convolutional neural network (CNN) using short latency dimension-reduced sEMG spectrograms as inputs. The pretrained classifier is recalibrated routinely using a corrected version of the prediction results from recent testing sessions. Our proposed system was evaluated with the NinaPro database comprising of hand movement data of 40 intact and 11 amputee subjects. Our system was able to achieve ~10.18% (intact, 50 movement types) and ~2.99% (amputee, 10 movement types) increase in classification accuracy averaged over five testing sessions with respect to the unrecalibrated classifier. When compared with a support vector machine (SVM) classifier, our CNN-based system consistently showed higher absolute performance and larger improvement as well as more efficient training. These results suggest that the proposed system can be a useful tool to facilitate long-term adoption of prosthetics for amputees in real-life applications.

  18. A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

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    Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

    2017-11-01

    Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this

  19. Surface EMG and intra-socket force measurement to control a prosthetic device

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    Sanford, Joe; Patterson, Rita; Popa, Dan

    2015-06-01

    Surface electromyography (SEMG) has been shown to be a robust and reliable interaction method allowing for basic control of powered prosthetic devices. Research has shown a marked decrease in EMG-classification efficiency throughout activities of daily life due to socket shift and movement and fatigue as well as changes in degree of fit of the socket throughout the subject's lifetime. Users with the most severe levels of amputation require the most complex devices with the greatest number of degrees of freedom. Controlling complex dexterous devices with limited available inputs requires the addition of sensing and interaction modalities. However, the larger the amputation severity, the fewer viable SEMG sites are available as control inputs. Previous work reported the use of intra-socket pressure, as measured during wrist flexion and extension, and has shown that it is possible to control a powered prosthetic device with pressure sensors. In this paper, we present data correlations of SEMG data with intra-socket pressure data. Surface EMG sensors and force sensors were housed within a simulated prosthetic cuff fit to a healthy-limbed subject. EMG and intra-socket force data was collected from inside the cuff as a subject performed pre-defined grip motions with their dominant hand. Data fusion algorithms were explored and allowed a subject to use both intra-socket pressure and SEMG data as control inputs for a powered prosthetic device. This additional input modality allows for an improvement in input classification as well as information regarding socket fit through out activities of daily life.

  20. FastICA peel-off for ECG interference removal from surface EMG.

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    Chen, Maoqi; Zhang, Xu; Chen, Xiang; Zhu, Mingxing; Li, Guanglin; Zhou, Ping

    2016-06-13

    Multi-channel recording of surface electromyographyic (EMG) signals is very likely to be contaminated by electrocardiographic (ECG) interference, specifically when the surface electrode is placed on muscles close to the heart. A novel fast independent component analysis (FastICA) based peel-off method is presented to remove ECG interference contaminating multi-channel surface EMG signals. Although demonstrating spatial variability in waveform shape, the ECG interference in different channels shares the same firing instants. Utilizing the firing information estimated from FastICA, ECG interference can be separated from surface EMG by a "peel off" processing. The performance of the method was quantified with synthetic signals by combining a series of experimentally recorded "clean" surface EMG and "pure" ECG interference. It was demonstrated that the new method can remove ECG interference efficiently with little distortion to surface EMG amplitude and frequency. The proposed method was also validated using experimental surface EMG signals contaminated by ECG interference. The proposed FastICA peel-off method can be used as a new and practical solution to eliminating ECG interference from multichannel EMG recordings.

  1. Patterns of motor recruitment can be determined using surface EMG.

    Science.gov (United States)

    Wakeling, James M

    2009-04-01

    Previous studies have reported how different populations of motor units (MUs) can be recruited during dynamic and locomotor tasks. It was hypothesised that the higher-threshold units would contribute higher-frequency components to the sEMG spectra due to their faster conduction velocities, and thus recruitment patterns that increase the proportion of high-threshold units active would lead to higher-frequency elements in the sEMG spectra. This idea was tested by using a model of varying recruitment coupled to a three-layer volume conductor model to generate a series of sEMG signals. The recruitment varied from (A) orderly recruitment where the lowest-threshold MUs were initially activated and higher-threshold MUs were sequentially recruited as the contraction progressed, (B) a recurrent inhibition model that started with orderly recruitment, but as the higher-threshold units were activated they inhibited the lower-threshold MUs (C) nine models with intermediate properties that were graded between these two extremes. The sEMG was processed using wavelet analysis and the spectral properties quantified by their mean frequency, and an angle theta that was determined from the principal components of the spectra. Recruitment strategies that resulted in a greater proportion of faster MUs being active had a significantly lower theta and higher mean frequency.

  2. Associations between motor unit action potential parameters and surface EMG features.

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    Del Vecchio, Alessandro; Negro, Francesco; Felici, Francesco; Farina, Dario

    2017-10-01

    The surface interference EMG signal provides some information on the neural drive to muscles. However, the association between neural drive to muscle and muscle activation has long been debated with controversial indications due to the unavailability of motor unit population data. In this study, we clarify the potential and limitations of interference EMG analysis to infer motor unit recruitment strategies with an experimental investigation of several concurrently active motor units and of the associated features of the surface EMG. For this purpose, we recorded high-density surface EMG signals during linearly increasing force contractions of the tibialis anterior muscle, up to 70% of maximal force. The recruitment threshold (RT), conduction velocity (MUCV), median frequency (MDF MU ), and amplitude (RMS MU ) of action potentials of 587 motor units from 13 individuals were assessed and associated with features of the interference EMG. MUCV was positively associated with RT ( R 2 = 0.64 ± 0.14), whereas MDF MU and RMS MU showed a weaker relation with RT ( R 2 = 0.11 ± 0.11 and 0.39 ± 0.24, respectively). Moreover, the changes in average conduction velocity estimated from the interference EMG predicted well the changes in MUCV ( R 2 = 0.71), with a strong association to ankle dorsiflexion force ( R 2 = 0.81 ± 0.12). Conversely, both the average EMG MDF and RMS were poorly associated with motor unit recruitment. These results clarify the limitations of EMG spectral and amplitude analysis in inferring the neural strategies of muscle control and indicate that, conversely, the average conduction velocity could provide relevant information on these strategies. NEW & NOTEWORTHY The surface EMG provides information on the neural drive to muscles. However, the associations between EMG features and neural drive have been long debated due to unavailability of motor unit population data. Here, by using novel highly accurate decomposition of the EMG, we related motor unit

  3. Surface EMG decomposition based on K-means clustering and convolution kernel compensation.

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    Ning, Yong; Zhu, Xiangjun; Zhu, Shanan; Zhang, Yingchun

    2015-03-01

    A new approach has been developed by combining the K-mean clustering (KMC) method and a modified convolution kernel compensation (CKC) method for multichannel surface electromyogram (EMG) decomposition. The KMC method was first utilized to cluster vectors of observations at different time instants and then estimate the initial innervation pulse train (IPT). The CKC method, modified with a novel multistep iterative process, was conducted to update the estimated IPT. The performance of the proposed K-means clustering-Modified CKC (KmCKC) approach was evaluated by reconstructing IPTs from both simulated and experimental surface EMG signals. The KmCKC approach successfully reconstructed all 10 IPTs from the simulated surface EMG signals with true positive rates (TPR) of over 90% with a low signal-to-noise ratio (SNR) of -10 dB. More than 10 motor units were also successfully extracted from the 64-channel experimental surface EMG signals of the first dorsal interosseous (FDI) muscles when a contraction force was held at 8 N by using the KmCKC approach. A "two-source" test was further conducted with 64-channel surface EMG signals. The high percentage of common MUs and common pulses (over 92% at all force levels) between the IPTs reconstructed from the two independent groups of surface EMG signals demonstrates the reliability and capability of the proposed KmCKC approach in multichannel surface EMG decomposition. Results from both simulated and experimental data are consistent and confirm that the proposed KmCKC approach can successfully reconstruct IPTs with high accuracy at different levels of contraction.

  4. Innervation zone of the vastus medialis muscle: position and effect on surface EMG variables

    International Nuclear Information System (INIS)

    Gallina, A; Merletti, R; Gazzoni, M

    2013-01-01

    The aim of this study was to investigate the position of the innervation zone (IZ) of the vastus medialis (VM) and its effect on the electromyographic (EMG) amplitude and mean frequency estimates. Eighteen healthy subjects performed maximal isometric knee extensions at three knee angles. Surface EMG signals were collected by using a 16 × 8 electrode grid placed on the VM muscle. The position of the IZ was estimated through visual analysis, and traditional bipolar signals were obtained from channels over and away from it; amplitude and mean frequency values were extracted and compared using an analysis of variance (ANOVA) with repeated measures. The IZ is shaped as a line running from the proximal–lateral to the distal–medial aspect of the VM muscle. The presence of an IZ under the electrodes lowered the EMG amplitude (P < 0.001, F = 58.11) and increased the EMG mean frequency (P < 0.001, F = 26.47); variations of these parameters due to the knee flexion angle were less frequently observed in EMG signals collected over than away from the IZ. Electrodes placed ‘over the belly of the VM muscle’ are likely to collect EMG signals influenced by the presence of the IZ, thus hindering the detection of changes in muscle activity. (paper)

  5. Intermuscular Coherence Between Surface EMG Signals Is Higher for Monopolar Compared to Bipolar Electrode Configurations

    Directory of Open Access Journals (Sweden)

    Maurice Mohr

    2018-05-01

    Full Text Available Introduction: The vasti muscles have to work in concert to control knee joint motion during movements like walking, running, or squatting. Coherence analysis between surface electromyography (EMG signals is a common technique to study muscle synchronization during such movements and gain insight into strategies of the central nervous system to optimize neuromuscular performance. However, different assessment methods related to EMG data acquisition, e.g., different electrode configurations or amplifier technologies, have produced inconsistent observations. Therefore, the aim of this study was to elucidate the effect of different EMG acquisition techniques (monopolar vs. bipolar electrode configuration, potential vs. current amplifier on the magnitude, reliability, and sensitivity of intermuscular coherence between two vasti muscles during stable and unstable squatting exercises.Methods: Surface EMG signals from vastus lateralis (VL and medialis (VM were obtained from eighteen adults while performing series of stable und unstable bipedal squats. The EMG signals were acquired using three different recording techniques: (1 Bipolar with a potential amplifier, (2 monopolar with a potential amplifier, and (3 monopolar electrodes with a current amplifier. VL-VM coherence between the respective raw EMG signals was determined during two trials of stable squatting and one trial of unstable squatting to compare the coherence magnitude, reliability, and sensitivity between EMG recording techniques.Results: VL-VM coherence was about twice as high for monopolar recordings compared to bipolar recordings for all squatting exercises while coherence was similar between monopolar potential and current recordings. Reliability measures were comparable between recording systems while the sensitivity to an increase in intermuscular coherence during unstable vs. stable squatting was lowest for the monopolar potential system.Discussion and Conclusion: The choice of

  6. Subspace based adaptive denoising of surface EMG from neurological injury patients

    Science.gov (United States)

    Liu, Jie; Ying, Dongwen; Zev Rymer, William; Zhou, Ping

    2014-10-01

    Objective: After neurological injuries such as spinal cord injury, voluntary surface electromyogram (EMG) signals recorded from affected muscles are often corrupted by interferences, such as spurious involuntary spikes and background noises produced by physiological and extrinsic/accidental origins, imposing difficulties for signal processing. Conventional methods did not well address the problem caused by interferences. It is difficult to mitigate such interferences using conventional methods. The aim of this study was to develop a subspace-based denoising method to suppress involuntary background spikes contaminating voluntary surface EMG recordings. Approach: The Karhunen-Loeve transform was utilized to decompose a noisy signal into a signal subspace and a noise subspace. An optimal estimate of EMG signal is derived from the signal subspace and the noise power. Specifically, this estimator is capable of making a tradeoff between interference reduction and signal distortion. Since the estimator partially relies on the estimate of noise power, an adaptive method was presented to sequentially track the variation of interference power. The proposed method was evaluated using both semi-synthetic and real surface EMG signals. Main results: The experiments confirmed that the proposed method can effectively suppress interferences while keep the distortion of voluntary EMG signal in a low level. The proposed method can greatly facilitate further signal processing, such as onset detection of voluntary muscle activity. Significance: The proposed method can provide a powerful tool for suppressing background spikes and noise contaminating voluntary surface EMG signals of paretic muscles after neurological injuries, which is of great importance for their multi-purpose applications.

  7. Changes in force, surface and motor unit EMG during post-exercise development of low frequency fatigue in vastus lateralis muscle

    NARCIS (Netherlands)

    de Ruiter, C.J.; Elzinga, M.J.; Verdijk, P.W.L.; van Mechelen, W.; de Haan, A.

    2005-01-01

    We investigated the effects of low frequency fatigue (LFF) on post-exercise changes in rectified surface EMG (rsEMG) and single motor unit EMG (smuEMG) in vastus lateralis muscle (n=9). On two experimental days the knee extensors were fatigued with a 60-s-isometric contraction (exercise) at 50%

  8. Effectiveness of the Wavelet Transform on the Surface EMG to Understand the Muscle Fatigue During Walk

    Science.gov (United States)

    Hussain, M. S.; Mamun, Md.

    2012-01-01

    Muscle fatigue is the decline in ability of a muscle to create force. Electromyography (EMG) is a medical technique for measuring muscle response to nervous stimulation. During a sustained muscle contraction, the power spectrum of the EMG shifts towards lower frequencies. These effects are due to muscle fatigue. Muscle fatigue is often a result of unhealthy work practice. In this research, the effectiveness of the wavelet transform applied to the surface EMG (SEMG) signal as a means of understanding muscle fatigue during walk is presented. Power spectrum and bispectrum analysis on the EMG signal getting from right rectus femoris muscle is executed utilizing various wavelet functions (WFs). It is possible to recognize muscle fatigue appreciably with the proper choice of the WF. The outcome proves that the most momentous changes in the EMG power spectrum are symbolized by WF Daubechies45. Moreover, this research has compared bispectrum properties to the other WFs. To determine muscle fatigue during gait, Daubechies45 is used in this research to analyze the SEMG signal.

  9. Surface EMG system for use in long-term vigorous activities

    Science.gov (United States)

    de Luca, G.; Bergman, P.; de Luca, C.

    The purpose of the project was to develop an advanced surface electromyographic (EMG) system that is portable, un-tethered, and able to detect high-fidelity EMG signals from multiple channels. The innovation was specifically designed to extend NASA's capability to perform neurological status monitoring for long-term, vigorous activities. These features are a necessary requirement of ground-based and in-flight studies planned for the International Space Station and human expeditions to Mars. The project consisted of developing 1) a portable EMG digital data logger using a handheld PC for acquiring the signal and storing the data from as many as 8 channels, and 2) an EMG electrode/skin interface to improve signal fidelity and skin adhesion in the presence of sweat and mechanical disturbances encountered during vigorous activities. The system, referred to as a MyoMonitor, was configured with a communication port for downloading the data from the data logger to the PC computer workstation. Software specifications were developed and implemented for programming of acquisition protocols, power management, and transferring data to the PC for processing and graphical display. The prototype MyoMonitor was implemented using a handheld PC that features a color LCD screen, enhanced keyboard, extended Lithium Ion battery and recharger, and 128 Mbytes of F ash Memory. The system was designed to be belt-worn,l thereby allowing its use under vigorous activities. The Monitor utilizes up to 8 differential surface EMG sensors. The prototype allowed greater than 2 hours of continuous 8-channel EMG data to be collected, or 17.2 hours of continuous single channel EMG data. Standardized tests in human subjects were conducted to develop the mechanical and electrical properties of the prototype electrode/interface system. Tests conducted during treadmill running and repetitive lifting demonstrated that the prototype interface significantly reduced the detrimental effects of sweat

  10. A model for generating Surface EMG signal of m. Tibialis Anterior.

    Science.gov (United States)

    Siddiqi, Ariba; Kumar, Dinesh; Arjunan, Sridhar P

    2014-01-01

    A model that simulates surface electromyogram (sEMG) signal of m. Tibialis Anterior has been developed and tested. This has a firing rate equation that is based on experimental findings. It also has a recruitment threshold that is based on observed statistical distribution. Importantly, it has considered both, slow and fast type which has been distinguished based on their conduction velocity. This model has assumed that the deeper unipennate half of the muscle does not contribute significantly to the potential induced on the surface of the muscle and has approximated the muscle to have parallel structure. The model was validated by comparing the simulated and the experimental sEMG signal recordings. Experiments were conducted on eight subjects who performed isometric dorsiflexion at 10, 20, 30, 50, 75, and 100% maximal voluntary contraction. Normalized root mean square and median frequency of the experimental and simulated EMG signal were computed and the slopes of the linearity with the force were statistically analyzed. The gradients were found to be similar (p>0.05) for both experimental and simulated sEMG signal, validating the proposed model.

  11. The reliability of surface EMG recorded from the pelvic floor muscles.

    Science.gov (United States)

    Auchincloss, Cindy C; McLean, Linda

    2009-08-30

    The neuromuscular function of the pelvic floor muscles (PFMs) is frequently evaluated using surface electrodes embedded on vaginal probes. The purpose of this study was to determine the between-trial and between-day reliability of EMG data recorded from the PFM using two different vaginal probes while subjects performed PFM maximum voluntary contractions and a coughing task. The Femiscan and the Periform vaginal probes were used to acquire EMG data while the subjects performed the tasks. Peak RMS amplitudes were computed for each instrument, task, and side of the pelvic floor using a sliding window technique. The between-trial reliability was evaluated using intraclass correlation coefficients (ICCs) and coefficients of variation (CV). Between-trial reliability was determined using ICCs, Pearson's correlation coefficients, computing the mean absolute difference between days, and calculating the standard error the measurement (SEM) for each instrument and task. EMG amplitude differences were detected between the left and right PFM (pperformed separately for each side. Overall, between-trial reliability was fair to high for the Femiscan (ICC((3,1))=0.58-0.98, CV=8.5-20.7%) and good to high for the Periform (ICC((3,1))=0.80-0.98, CV=9.6-19.5%), however between-day reliability was generally poor for both vaginal probes (ICC((3,1))=0.08-0.84). The results suggest that although it is acceptable to use PFM surface EMG as a biofeedback tool for training purposes, it is not recommended for use to make between-subject comparisons or to use as an outcome measure between-days when evaluating PFM function.

  12. A Review of Classification Techniques of EMG Signals during Isotonic and Isometric Contractions

    Directory of Open Access Journals (Sweden)

    Nurhazimah Nazmi

    2016-08-01

    Full Text Available In recent years, there has been major interest in the exposure to physical therapy during rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and human machine interface (HMI applications. An automated system will guide the user to perform the training during rehabilitation independently. Advances in engineering have extended electromyography (EMG beyond the traditional diagnostic applications to also include applications in diverse areas such as movement analysis. This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who would like to select the most appropriate methodology in classifying motion patterns, especially during different types of contractions. For feature extraction, the probability density function (PDF of EMG signals will be the main interest of this study. Following that, a brief explanation of the different methods for pre-processing, feature extraction and classifying EMG signals will be compared in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.

  13. Simultaneous and Continuous Estimation of Shoulder and Elbow Kinematics from Surface EMG Signals

    Directory of Open Access Journals (Sweden)

    Qin Zhang

    2017-05-01

    Full Text Available In this paper, we present a simultaneous and continuous kinematics estimation method for multiple DoFs across shoulder and elbow joint. Although simultaneous and continuous kinematics estimation from surface electromyography (EMG is a feasible way to achieve natural and intuitive human-machine interaction, few works investigated multi-DoF estimation across the significant joints of upper limb, shoulder and elbow joints. This paper evaluates the feasibility to estimate 4-DoF kinematics at shoulder and elbow during coordinated arm movements. Considering the potential applications of this method in exoskeleton, prosthetics and other arm rehabilitation techniques, the estimation performance is presented with different muscle activity decomposition and learning strategies. Principle component analysis (PCA and independent component analysis (ICA are respectively employed for EMG mode decomposition with artificial neural network (ANN for learning the electromechanical association. Four joint angles across shoulder and elbow are simultaneously and continuously estimated from EMG in four coordinated arm movements. By using ICA (PCA and single ANN, the average estimation accuracy 91.12% (90.23% is obtained in 70-s intra-cross validation and 87.00% (86.30% is obtained in 2-min inter-cross validation. This result suggests it is feasible and effective to use ICA (PCA with single ANN for multi-joint kinematics estimation in variant application conditions.

  14. Surface EMG characteristics of people with multiple sclerosis during static contractions of the knee extensors.

    Science.gov (United States)

    Scott, Sasha M; Hughes, Adrienne R; Galloway, Stuart D R; Hunter, Angus M

    2011-01-01

    This study was designed to determine whether any alterations existed in surface electromyography (sEMG) in people with multiple sclerosis (MS) during isometric contractions of the knee extensors. Fifteen people with MS and 14 matched controls (mean ± SD age and body mass index 53·7 ± 10·5 versus 54·6 ± 9·6 years and 27·7 ± 6·1 versus 26·5 ± 4, respectively) completed 20%, 40%, 60% and 80% of their maximal voluntary contraction (MVC) of the knee extensors. sEMG was recorded from the vastus lateralis where muscle fibre conduction velocity (MFCV) and sEMG amplitude (RMS) were assessed. Body composition was determined using dual-energy X-ray absorptiometry and physical activity with the use of accelerometry. People with MS showed significantly (P<0·05) faster MFCV during MVC (6·6 ± 2·7 versus 4·7 ± 1·4 m s(-1) ) and all submaximal contractions, while RMS was significantly (P<0·05) less (0·11 ± 0·03 versus 0·24 ± 0·06 mV) in comparison with the controls. MVC along with specific thigh lean mass to torque, rate of force development and mean physical activity were significantly (P<0·01) less in PwMS. People with MS have elevated MFCV alongside reduced RMS during isometric contraction. This elevation in MFCV should be accounted for when interpreting sEMG from people with MS. © 2010 University of Stirling. Clinical physiology and Functional Imaging © 2010 Scandinavian Society of Clinical Physiology and Nuclear Medicine.

  15. Assessment of Diaphragm and External Intercostals Fatigue from Surface EMG using Cervical Magnetic Stimulation

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    Ya-Ju Chang

    2008-03-01

    Full Text Available This study was designed: (1 to test the reliability of surface electromyography (sEMG recording of the diaphragm and external intercostals contractions response to cervical magnetic stimulation (CMS, (2 to examine the amount and the types of inspiratory muscle fatigue that developed after maximum voluntary ventilation (MVV maneuvers.Ten male college students without physical disability (22.1±2.0 years old participated in the study and each completed a control (quiet breathing trial and a fatigue (MVV maneuvers trial sequentially. In the quiet breathing trial, the subjects maintained quiet breathing for five minutes. The subjects performed five maximal static inspiratory efforts and received five CMS before and after the quiet breathing. In the MVV trial, subjects performed five maximal inspiratory efforts and received five CMS before, immediately after, and ten minutes after two sets of MVV maneuvers performed five minutes apart. Maximal inspiratory pressure (PImax, sEMG of diaphragm and external intercostals during maximal static inspiratory efforts and during CMS were recorded. In the quiet breathing trial, high intraclass correlation coefficients (ICC=0.95-0.99 were observed in all the variables. In the MVV trial, the PImax, the EMG amplitude and the median power frequency during maximal static inspiratory efforts significantly decreased in both the diaphragm and the external intercostals immediately after the MVV maneuvers Sensors 2008, 8 2175 (P 0.05. It is concluded that the sEMG recordings of the diaphragm during maximal static inspiratory efforts and in response to CMS allow reproducible sequential assessment of diaphragm contractility. MVV maneuvers resulted in inspiratory muscles fatigue, possibly central fatigue.

  16. Real time estimation of generation, extinction and flow of muscle fibre action potentials in high density surface EMG.

    Science.gov (United States)

    Mesin, Luca

    2015-02-01

    Developing a real time method to estimate generation, extinction and propagation of muscle fibre action potentials from bi-dimensional and high density surface electromyogram (EMG). A multi-frame generalization of an optical flow technique including a source term is considered. A model describing generation, extinction and propagation of action potentials is fit to epochs of surface EMG. The algorithm is tested on simulations of high density surface EMG (inter-electrode distance equal to 5mm) from finite length fibres generated using a multi-layer volume conductor model. The flow and source term estimated from interference EMG reflect the anatomy of the muscle, i.e. the direction of the fibres (2° of average estimation error) and the positions of innervation zone and tendons under the electrode grid (mean errors of about 1 and 2mm, respectively). The global conduction velocity of the action potentials from motor units under the detection system is also obtained from the estimated flow. The processing time is about 1 ms per channel for an epoch of EMG of duration 150 ms. A new real time image processing algorithm is proposed to investigate muscle anatomy and activity. Potential applications are proposed in prosthesis control, automatic detection of optimal channels for EMG index extraction and biofeedback. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Comparison of sEMG-Based Feature Extraction and Motion Classification Methods for Upper-Limb Movement

    Directory of Open Access Journals (Sweden)

    Shuxiang Guo

    2015-04-01

    Full Text Available The surface electromyography (sEMG technique is proposed for muscle activation detection and intuitive control of prostheses or robot arms. Motion recognition is widely used to map sEMG signals to the target motions. One of the main factors preventing the implementation of this kind of method for real-time applications is the unsatisfactory motion recognition rate and time consumption. The purpose of this paper is to compare eight combinations of four feature extraction methods (Root Mean Square (RMS, Detrended Fluctuation Analysis (DFA, Weight Peaks (WP, and Muscular Model (MM and two classifiers (Neural Networks (NN and Support Vector Machine (SVM, for the task of mapping sEMG signals to eight upper-limb motions, to find out the relation between these methods and propose a proper combination to solve this issue. Seven subjects participated in the experiment and six muscles of the upper-limb were selected to record sEMG signals. The experimental results showed that NN classifier obtained the highest recognition accuracy rate (88.7% during the training process while SVM performed better in real-time experiments (85.9%. For time consumption, SVM took less time than NN during the training process but needed more time for real-time computation. Among the four feature extraction methods, WP had the highest recognition rate for the training process (97.7% while MM performed the best during real-time tests (94.3%. The combination of MM and NN is recommended for strict real-time applications while a combination of MM and SVM will be more suitable when time consumption is not a key requirement.

  18. Linear correlation between fractal dimension of surface EMG signal from Rectus Femoris and height of vertical jump

    International Nuclear Information System (INIS)

    Ancillao, Andrea; Galli, Manuela; Rigoldi, Chiara; Albertini, Giorgio

    2014-01-01

    Fractal dimension was demonstrated to be able to characterize the complexity of biological signals. The EMG time series are well known to have a complex behavior and some other studies already tried to characterize these signals by their fractal dimension. This paper is aimed at studying the correlation between the fractal dimension of surface EMG signal recorded over Rectus Femoris muscles during a vertical jump and the height reached in that jump. Healthy subjects performed vertical jumps at different heights. Surface EMG from Rectus Femoris was recorded and the height of each jump was measured by an optoelectronic motion capture system. Fractal dimension of sEMG was computed and the correlation between fractal dimension and eight of the jump was studied. Linear regression analysis showed a very high correlation coefficient between the fractal dimension and the height of the jump for all the subjects. The results of this study show that the fractal dimension is able to characterize the EMG signal and it can be related to the performance of the jump. Fractal dimension is therefore an useful tool for EMG interpretation

  19. Effective Low-Power Wearable Wireless Surface EMG Sensor Design Based on Analog-Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Mohammadreza Balouchestani

    2014-12-01

    Full Text Available Surface Electromyography (sEMG is a non-invasive measurement process that does not involve tools and instruments to break the skin or physically enter the body to investigate and evaluate the muscular activities produced by skeletal muscles. The main drawbacks of existing sEMG systems are: (1 they are not able to provide real-time monitoring; (2 they suffer from long processing time and low speed; (3 they are not effective for wireless healthcare systems because they consume huge power. In this work, we present an analog-based Compressed Sensing (CS architecture, which consists of three novel algorithms for design and implementation of wearable wireless sEMG bio-sensor. At the transmitter side, two new algorithms are presented in order to apply the analog-CS theory before Analog to Digital Converter (ADC. At the receiver side, a robust reconstruction algorithm based on a combination of ℓ1-ℓ1-optimization and Block Sparse Bayesian Learning (BSBL framework is presented to reconstruct the original bio-signals from the compressed bio-signals. The proposed architecture allows reducing the sampling rate to 25% of Nyquist Rate (NR. In addition, the proposed architecture reduces the power consumption to 40%, Percentage Residual Difference (PRD to 24%, Root Mean Squared Error (RMSE to 2%, and the computation time from 22 s to 9.01 s, which provide good background for establishing wearable wireless healthcare systems. The proposed architecture achieves robust performance in low Signal-to-Noise Ratio (SNR for the reconstruction process.

  20. A Simple Network to Remove Interference in Surface EMG Signal from Single Gene Affected Phenylketonuria Patients for Proper Diagnosis

    Science.gov (United States)

    Mohanty, Madhusmita; Basu, Mousumi; Pattanayak, Deba Narayan; Mohapatra, Sumant Kumar

    2018-04-01

    Recently Autosomal Recessive Single Gene (ARSG) diseases are highly effective to the children within the age of 5-10 years. One of the most ARSG disease is a Phenylketonuria (PKU). This single gene disease is associated with mutations in the gene that encodes the enzyme phenylalanine hydroxylase (PAH, Gene 612349). Through this mutation process, PAH of the gene affected patient can not properly manufacture PAH as a result the patients suffer from decreased muscle tone which shows abnormality in EMG signal. Here the extraction of the quality of the PKU affected EMG (PKU-EMG) signal is a keen interest, so it is highly necessary to remove the added ECG signal as well as the biological and instrumental noises. In the Present paper we proposed a method for detection and classification of the PKU affected EMG signal. Here Discrete Wavelet Transformation is implemented for extraction of the features of the PKU affected EMG signal. Adaptive Neuro-Fuzzy Inference System (ANFIS) network is used for the classification of the signal. Modified Particle Swarm Optimization (MPSO) and Modified Genetic Algorithm (MGA) are used to train the ANFIS network. Simulation result shows that the proposed method gives better performance as compared to existing approaches. Also it gives better accuracy of 98.02% for the detection of PKU-EMG signal. The advantages of the proposed model is to use MGA and MPSO to train the parameters of ANFIS network for classification of ECG and EMG signal of PKU affected patients. The proposed method obtained the high SNR (18.13 ± 0.36 dB), SNR (0.52 ± 1.62 dB), RE (0.02 ± 0.32), MSE (0.64 ± 2.01), CC (0.99 ± 0.02), RMSE (0.75 ± 0.35) and MFRE (0.01 ± 0.02), RMSE (0.75 ± 0.35) and MFRE (0.01 ± 0.02). From authors knowledge, this is the first time a composite method is used for diagnosis of PKU affected patients. The accuracy (98.02%), sensitivity (100%) and specificity (98.59%) helps for proper clinical treatment. It can help for readers

  1. Fasciculations and their F-response revisited: High-density surface EMG in ALS and benign fasciculations

    NARCIS (Netherlands)

    Kleine, B.U.; Boekestein, W.A.; Arts, I.M.; Zwarts, M.J.; Schelhaas, H.J.; Stegeman, D.F.

    2012-01-01

    Objective: To compare the prevalence of fasciculation potentials (FPs) with F-responses between patients with amyotrophic lateral sclerosis (ALS) and patients with benign fasciculations. Methods: In seven patients with ALS and seven patients with benign fasciculations, high-density surface EMG was

  2. Motor unit properties of biceps brachii in chronic stroke patients assessed with high-density surface EMG

    NARCIS (Netherlands)

    Kallenberg, L.A.C.; Hermens, Hermanus J.

    2009-01-01

    The aim of this study was to investigate motor unit (MU) characteristics of the biceps brachii in post-stroke patients, using high-density surface electromyography (sEMG). Eighteen chronic hemiparetic stroke patients took part. The Fugl-Meyer score for the upper extremity was assessed. Subjects

  3. Low-back electromyography (EMG data-driven load classification for dynamic lifting tasks.

    Directory of Open Access Journals (Sweden)

    Deema Totah

    Full Text Available Numerous devices have been designed to support the back during lifting tasks. To improve the utility of such devices, this research explores the use of preparatory muscle activity to classify muscle loading and initiate appropriate device activation. The goal of this study was to determine the earliest time window that enabled accurate load classification during a dynamic lifting task.Nine subjects performed thirty symmetrical lifts, split evenly across three weight conditions (no-weight, 10-lbs and 24-lbs, while low-back muscle activity data was collected. Seven descriptive statistics features were extracted from 100 ms windows of data. A multinomial logistic regression (MLR classifier was trained and tested, employing leave-one subject out cross-validation, to classify lifted load values. Dimensionality reduction was achieved through feature cross-correlation analysis and greedy feedforward selection. The time of full load support by the subject was defined as load-onset.Regions of highest average classification accuracy started at 200 ms before until 200 ms after load-onset with average accuracies ranging from 80% (±10% to 81% (±7%. The average recall for each class ranged from 69-92%.These inter-subject classification results indicate that preparatory muscle activity can be leveraged to identify the intent to lift a weight up to 100 ms prior to load-onset. The high accuracies shown indicate the potential to utilize intent classification for assistive device applications.Active assistive devices, e.g. exoskeletons, could prevent back injury by off-loading low-back muscles. Early intent classification allows more time for actuators to respond and integrate seamlessly with the user.

  4. sEMG Signal Acquisition Strategy towards Hand FES Control

    Directory of Open Access Journals (Sweden)

    Cinthya Lourdes Toledo-Peral

    2018-01-01

    Full Text Available Due to damage of the nervous system, patients experience impediments in their daily life: severe fatigue, tremor or impaired hand dexterity, hemiparesis, or hemiplegia. Surface electromyography (sEMG signal analysis is used to identify motion; however, standardization of electrode placement and classification of sEMG patterns are major challenges. This paper describes a technique used to acquire sEMG signals for five hand motion patterns from six able-bodied subjects using an array of recording and stimulation electrodes placed on the forearm and its effects over functional electrical stimulation (FES and volitional sEMG combinations, in order to eventually control a sEMG-driven FES neuroprosthesis for upper limb rehabilitation. A two-part protocol was performed. First, personalized templates to place eight sEMG bipolar channels were designed; with these data, a universal template, called forearm electrode set (FELT, was built. Second, volitional and evoked movements were recorded during FES application. 95% classification accuracy was achieved using two sessions per movement. With the FELT, it was possible to perform FES and sEMG recordings simultaneously. Also, it was possible to extract the volitional and evoked sEMG from the raw signal, which is highly important for closed-loop FES control.

  5. Classification of EMG signals using artificial neural networks for virtual hand prosthesis control.

    Science.gov (United States)

    Mattioli, Fernando E R; Lamounier, Edgard A; Cardoso, Alexandre; Soares, Alcimar B; Andrade, Adriano O

    2011-01-01

    Computer-based training systems have been widely studied in the field of human rehabilitation. In health applications, Virtual Reality presents itself as an appropriate tool to simulate training environments without exposing the patients to risks. In particular, virtual prosthetic devices have been used to reduce the great mental effort needed by patients fitted with myoelectric prosthesis, during the training stage. In this paper, the application of Virtual Reality in a hand prosthesis training system is presented. To achieve this, the possibility of exploring Neural Networks in a real-time classification system is discussed. The classification technique used in this work resulted in a 95% success rate when discriminating 4 different hand movements.

  6. Neural network committees for finger joint angle estimation from surface EMG signals

    Directory of Open Access Journals (Sweden)

    Reddy Narender P

    2009-01-01

    Full Text Available Abstract Background In virtual reality (VR systems, the user's finger and hand positions are sensed and used to control the virtual environments. Direct biocontrol of VR environments using surface electromyography (SEMG signals may be more synergistic and unconstraining to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models. Methodology SEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-extension rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the parameters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects. Results There was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion. Conclusion Although hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals.

  7. Relationship between oxygen uptake slow component and surface EMG during heavy exercise in humans: influence of pedal rate.

    Science.gov (United States)

    Vercruyssen, Fabrice; Missenard, Olivier; Brisswalter, Jeanick

    2009-08-01

    The aim of this study was to test the hypothesis that extreme pedal rates contributed to the slow component of oxygen uptake (VO(2) SC) in association with changes in surface electromyographic (sEMG) during heavy-cycle exercise. Eight male trained cyclists performed two square-wave transitions at 50 and 110 rpm at a work rate that would elicit a VO(2) corresponding to 50% of the difference between peak VO(2) and the ventilatory threshold. Pulmonary gas exchange was measured breath-by-breath and sEMG was obtained from the vastus lateralis and medialis muscles. Integrated EMG flow (QiEMG) and mean power frequency (MPF) were computed. The relative amplitude of the VO(2) SC was significantly higher during the 110-rpm bout (556+/-186 ml min(-1), Pexercise only during the 110-rpm bout and were associated with the greater amplitude of the VO(2) SC observed for this condition (Pmotor units recruitment pattern, muscle energy turnover and muscle temperature have been suggested to explain the different VO(2) SC to heavy pedal rate bouts.

  8. Analysis of High-Density Surface EMG and Finger Pressure in the Left Forearm of Violin Players: A Feasibility Study.

    Science.gov (United States)

    Cattarello, Paolo; Merletti, Roberto; Petracca, Francesco

    2017-09-01

    Wrist and finger flexor muscles of the left hand were evaluated using high-density surface EMG (HDsEMG) in 17 violin players. Pressure sensors also were mounted below the second string of the violin to evaluate, simultaneously, finger pressure. Electrode grid size was 110x70 mm (12x8 electrodes with interelectrode distance=10 mm and Ø=3 mm). The study objective was to observe the activation patterns of these muscles while the violinists sequentially played four notes--SI (B), DO# (C#), RE (D), MI (E)--at 2 bows/s (one bow up in 0.5 s and one down in 0.5 s) and 4 bows/s on the second string, while producing a constant (CONST) or ramp (RAMP) sound volume. HDsEMG images obtained while playing the notes were compared with those obtained during isometric radial or ulnar flexion of the wrist or fingers. Two image descriptors provided information on image differences. Results showed that the technique was reliable and provided reliable signals, and that recognizably different sEMG images could be associated with the four notes tested, despite the variability within and between subjects playing the same note. sEMG activity of the left hand muscles and pressure on the string in the RAMP task were strongly affected in some individuals by the sound volume (controlled by the right hand) and much less in other individuals. These findings question whether there is an individual or generally optimal way of pressing violin strings with the left hand. The answer to this question might substantially modify the teaching of string instruments.

  9. High-density surface EMG maps from upper-arm and forearm muscles

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    Rojas-Martínez Monica

    2012-12-01

    Full Text Available Abstract Background sEMG signal has been widely used in different applications in kinesiology and rehabilitation as well as in the control of human-machine interfaces. In general, the signals are recorded with bipolar electrodes located in different muscles. However, such configuration may disregard some aspects of the spatial distribution of the potentials like location of innervation zones and the manifestation of inhomogineties in the control of the muscular fibers. On the other hand, the spatial distribution of motor unit action potentials has recently been assessed with activation maps obtained from High Density EMG signals (HD-EMG, these lasts recorded with arrays of closely spaced electrodes. The main objective of this work is to analyze patterns in the activation maps, associating them with four movement directions at the elbow joint and with different strengths of those tasks. Although the activation pattern can be assessed with bipolar electrodes, HD-EMG maps could enable the extraction of features that depend on the spatial distribution of the potentials and on the load-sharing between muscles, in order to have a better differentiation between tasks and effort levels. Methods An experimental protocol consisting of isometric contractions at three levels of effort during flexion, extension, supination and pronation at the elbow joint was designed and HD-EMG signals were recorded with 2D electrode arrays on different upper-limb muscles. Techniques for the identification and interpolation of artifacts are explained, as well as a method for the segmentation of the activation areas. In addition, variables related to the intensity and spatial distribution of the maps were obtained, as well as variables associated to signal power of traditional single bipolar recordings. Finally, statistical tests were applied in order to assess differences between information extracted from single bipolar signals or from HD-EMG maps and to analyze

  10. Analyzing surface EMG signals to determine relationship between jaw imbalance and arm strength loss

    Directory of Open Access Journals (Sweden)

    Truong Quang Dang Khoa

    2012-08-01

    Full Text Available Abstract Background This study investigated the relationship between dental occlusion and arm strength; in particular, the imbalance in the jaw can cause loss in arm strength phenomenon. One of the goals of this study was to record the maximum forces that the subjects can resist against the pull-down force on their hands while biting a spacer of adjustable height on the right or left side of the jaw. Then EMG measurement was used to determine the EMG-Force relationship of the jaw, neck and arms muscles. This gave us useful insights on the arms strength loss due to the biomechanical effects of the imbalance in the jaw mechanism. Methods In this study to determine the effects of the imbalance in the jaw to the strength of the arms, we conducted experiments with a pool of 20 healthy subjects of both genders. The subjects were asked to resist a pull down force applied on the contralateral arm while biting on a firm spacer using one side of the jaw. Four different muscles – masseter muscles, deltoid muscles, bicep muscles and trapezoid muscles – were involved. Integrated EMG (iEMG and Higuchi fractal dimension (HFD were used to analyze the EMG signals. Results The results showed that (1 Imbalance in the jaw causes loss of arm strength contra-laterally; (2 The loss is approximately a linear function of the height of the spacers. Moreover, the iEMG showed the intensity of muscle activities decreased when the degrees of jaw imbalance increased (spacer thickness increased. In addition, the tendency of Higuchi fractal dimension decreased for all muscles. Conclusions This finding indicates that muscle fatigue and the decrease in muscle contraction level leads to the loss of arm strength.

  11. Estimation of continuous multi-DOF finger joint kinematics from surface EMG using a multi-output Gaussian Process.

    Science.gov (United States)

    Ngeo, Jimson; Tamei, Tomoya; Shibata, Tomohiro

    2014-01-01

    Surface electromyographic (EMG) signals have often been used in estimating upper and lower limb dynamics and kinematics for the purpose of controlling robotic devices such as robot prosthesis and finger exoskeletons. However, in estimating multiple and a high number of degrees-of-freedom (DOF) kinematics from EMG, output DOFs are usually estimated independently. In this study, we estimate finger joint kinematics from EMG signals using a multi-output convolved Gaussian Process (Multi-output Full GP) that considers dependencies between outputs. We show that estimation of finger joints from muscle activation inputs can be improved by using a regression model that considers inherent coupling or correlation within the hand and finger joints. We also provide a comparison of estimation performance between different regression methods, such as Artificial Neural Networks (ANN) which is used by many of the related studies. We show that using a multi-output GP gives improved estimation compared to multi-output ANN and even dedicated or independent regression models.

  12. The reliability of a maximal isometric hip strength and simultaneous surface EMG screening protocol in elite, junior rugby league athletes.

    Science.gov (United States)

    Charlton, Paula C; Mentiplay, Benjamin F; Grimaldi, Alison; Pua, Yong-Hao; Clark, Ross A

    2017-02-01

    Firstly to describe the reliability of assessing maximal isometric strength of the hip abductor and adductor musculature using a hand held dynamometry (HHD) protocol with simultaneous wireless surface electromyographic (sEMG) evaluation of the gluteus medius (GM) and adductor longus (AL). Secondly, to describe the correlation between isometric strength recorded with the HHD protocol and a laboratory standard isokinetic device. Reliability and correlational study. A sample of 24 elite, male, junior, rugby league athletes, age 16-20 years participated in repeated HHD and isometric Kin-Com (KC) strength testing with simultaneous sEMG assessment, on average (range) 6 (5-7) days apart by a single assessor. Strength tests included; unilateral hip abduction (ABD) and adduction (ADD) and bilateral ADD assessed with squeeze (SQ) tests in 0 and 45° of hip flexion. HHD demonstrated good to excellent inter-session reliability for all outcome measures (ICC (2,1) =0.76-0.91) and good to excellent association with the laboratory reference KC (ICC (2,1) =0.80-0.88). Whilst intra-session, inter-trial reliability of EMG activation and co-activation outcome measures ranged from moderate to excellent (ICC (2,1) =0.70-0.94), inter-session reliability was poor (all ICC (2,1) Isometric strength testing of the hip ABD and ADD musculature using HHD may be measured reliably in elite, junior rugby league athletes. Due to the poor inter-session reliability of sEMG measures, it is not recommended for athlete screening purposes if using the techniques implemented in this study. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  13. Recognition of grasp types through principal components of DWT based EMG features.

    Science.gov (United States)

    Kakoty, Nayan M; Hazarika, Shyamanta M

    2011-01-01

    With the advancement in machine learning and signal processing techniques, electromyogram (EMG) signals have increasingly gained importance in man-machine interaction. Multifingered hand prostheses using surface EMG for control has appeared in the market. However, EMG based control is still rudimentary, being limited to a few hand postures based on higher number of EMG channels. Moreover, control is non-intuitive, in the sense that the user is required to learn to associate muscle remnants actions to unrelated posture of the prosthesis. Herein lies the promise of a low channel EMG based grasp classification architecture for development of an embedded intelligent prosthetic controller. This paper reports classification of six grasp types used during 70% of daily living activities based on two channel forearm EMG. A feature vector through principal component analysis of discrete wavelet transform coefficients based features of the EMG signal is derived. Classification is through radial basis function kernel based support vector machine following preprocessing and maximum voluntary contraction normalization of EMG signals. 10-fold cross validation is done. We have achieved an average recognition rate of 97.5%. © 2011 IEEE

  14. Classification of Anticipatory Signals for Grasp and Release from Surface Electromyography

    Science.gov (United States)

    Siu, Ho Chit; Shah, Julie A.; Stirling, Leia A.

    2016-01-01

    Surface electromyography (sEMG) is a technique for recording natural muscle activation signals, which can serve as control inputs for exoskeletons and prosthetic devices. Previous experiments have incorporated these signals using both classical and pattern-recognition control methods in order to actuate such devices. We used the results of an experiment incorporating grasp and release actions with object contact to develop an intent-recognition system based on Gaussian mixture models (GMM) and continuous-emission hidden Markov models (HMM) of sEMG data. We tested this system with data collected from 16 individuals using a forearm band with distributed sEMG sensors. The data contain trials with shifted band alignments to assess robustness to sensor placement. This study evaluated and found that pattern-recognition-based methods could classify transient anticipatory sEMG signals in the presence of shifted sensor placement and object contact. With the best-performing classifier, the effect of label lengths in the training data was also examined. A mean classification accuracy of 75.96% was achieved through a unigram HMM method with five mixture components. Classification accuracy on different sub-movements was found to be limited by the length of the shortest sub-movement, which means that shorter sub-movements within dynamic sequences require larger training sets to be classified correctly. This classification of user intent is a potential control mechanism for a dynamic grasping task involving user contact with external objects and noise. Further work is required to test its performance as part of an exoskeleton controller, which involves contact with actuated external surfaces. PMID:27792155

  15. Changes in force, surface and motor unit EMG during post-exercise development of low frequency fatigue in vastus lateralis muscle.

    Science.gov (United States)

    de Ruiter, C J; Elzinga, M J H; Verdijk, P W L; van Mechelen, W; de Haan, A

    2005-08-01

    We investigated the effects of low frequency fatigue (LFF) on post-exercise changes in rectified surface EMG (rsEMG) and single motor unit EMG (smuEMG) in vastus lateralis muscle (n = 9). On two experimental days the knee extensors were fatigued with a 60-s-isometric contraction (exercise) at 50% maximal force capacity (MFC). On the first day post-exercise (15 s, 3, 9, 15, 21 and 27 min) rsEMG and electrically-induced (surface stimulation) forces were investigated. SmuEMG was obtained on day two. During short ramp and hold (5 s) contractions at 50% MFC, motor unit discharges of the same units were followed over time. Post-exercise MFC and tetanic force (100 Hz stimulation) recovered to about 90% of the pre-exercise values, but recovery with 20 Hz stimulation was less complete: the 20-100 Hz force ratio (mean +/- SD) decreased from 0.65+/-0.06 (pre-exercise) to 0.56+/-0.04 at 27 min post-exercise (Pexercise rsEMG (% pre-exercise maximum) and motor unit discharge rate were 51.1 +/- 12.7% and 14.1 +/- 3.7 (pulses per second; pps) respectively, 15 s post-exercise the respective values were 61.4 +/- 15.4% (P0.05). Thereafter, rsEMG (at 50% MFC) remained stable but motor unit discharge rate significantly increased to 17.7 +/- 3.9 pps 27 min post-exercise. The recruitment threshold decreased (Pexercise to 25.2 +/- 6.7% 27 min post-exercise. The increase in discharge rate was significantly greater than could be expected from the decrease in recruitment threshold. Thus, post-exercise LFF was compensated by increased motor unit discharge rates which could only partly be accounted for by the small decrease in motor unit recruitment threshold.

  16. Duration of observation required in detecting fasciculation potentials in amyotrophic lateral sclerosis using high-density surface EMG

    Directory of Open Access Journals (Sweden)

    Zhou Ping

    2012-10-01

    Full Text Available Abstract Background High-density surface electromyography (HD-SEMG has recently emerged as a potentially useful tool in the evaluation of amyotrophic lateral sclerosis (ALS. This study addresses a practical constraint that arises when applying HD-SEMG for supporting the diagnosis of ALS; specifically, how long the surface EMG should be recorded before one can be confident that fasciculation potentials (FPs are absent in a muscle being tested. Methods HD-SEMG recordings of 29 muscles from 11 ALS patients were analyzed. We used the distribution of intervals between FPs, and estimated the observation duration needed to record from one to five FPs with a probability approaching unity. Such an approach was previously tested by Mills with a concentric needle electrode. Results We found that the duration of recording was up to 70 s in order to record a single FP with a probability approaching unity. Increasing recording time to 2 minutes, the probability of recording five FPs approached approximately 0.95. Conclusions HD-SEMG appears to be a suitable method for capturing FPs comparable to intramuscular needle EMG.

  17. Motor Function Evaluation of Hemiplegic Upper-Extremities Using Data Fusion from Wearable Inertial and Surface EMG Sensors

    Directory of Open Access Journals (Sweden)

    Yanran Li

    2017-03-01

    Full Text Available Quantitative evaluation of motor function is of great demand for monitoring clinical outcome of applied interventions and further guiding the establishment of therapeutic protocol. This study proposes a novel framework for evaluating upper limb motor function based on data fusion from inertial measurement units (IMUs and surface electromyography (EMG sensors. With wearable sensors worn on the tested upper limbs, subjects were asked to perform eleven straightforward, specifically designed canonical upper-limb functional tasks. A series of machine learning algorithms were applied to the recorded motion data to produce evaluation indicators, which is able to reflect the level of upper-limb motor function abnormality. Sixteen healthy subjects and eighteen stroke subjects with substantial hemiparesis were recruited in the experiment. The combined IMU and EMG data yielded superior performance over the IMU data alone and the EMG data alone, in terms of decreased normal data variation rate (NDVR and improved determination coefficient (DC from a regression analysis between the derived indicator and routine clinical assessment score. Three common unsupervised learning algorithms achieved comparable performance with NDVR around 10% and strong DC around 0.85. By contrast, the use of a supervised algorithm was able to dramatically decrease the NDVR to 6.55%. With the proposed framework, all the produced indicators demonstrated high agreement with the routine clinical assessment scale, indicating their capability of assessing upper-limb motor functions. This study offers a feasible solution to motor function assessment in an objective and quantitative manner, especially suitable for home and community use.

  18. An isometric muscle force estimation framework based on a high-density surface EMG array and an NMF algorithm

    Science.gov (United States)

    Huang, Chengjun; Chen, Xiang; Cao, Shuai; Qiu, Bensheng; Zhang, Xu

    2017-08-01

    Objective. To realize accurate muscle force estimation, a novel framework is proposed in this paper which can extract the input of the prediction model from the appropriate activation area of the skeletal muscle. Approach. Surface electromyographic (sEMG) signals from the biceps brachii muscle during isometric elbow flexion were collected with a high-density (HD) electrode grid (128 channels) and the external force at three contraction levels was measured at the wrist synchronously. The sEMG envelope matrix was factorized into a matrix of basis vectors with each column representing an activation pattern and a matrix of time-varying coefficients by a nonnegative matrix factorization (NMF) algorithm. The activation pattern with the highest activation intensity, which was defined as the sum of the absolute values of the time-varying coefficient curve, was considered as the major activation pattern, and its channels with high weighting factors were selected to extract the input activation signal of a force estimation model based on the polynomial fitting technique. Main results. Compared with conventional methods using the whole channels of the grid, the proposed method could significantly improve the quality of force estimation and reduce the electrode number. Significance. The proposed method provides a way to find proper electrode placement for force estimation, which can be further employed in muscle heterogeneity analysis, myoelectric prostheses and the control of exoskeleton devices.

  19. Spatial distribution of surface EMG on trapezius and lumbar muscles of violin and cello players in single note playing.

    Science.gov (United States)

    Afsharipour, Babak; Petracca, Francesco; Gasparini, Mauro; Merletti, Roberto

    2016-12-01

    Musicians activate their muscles in different patterns, depending on their posture, the instrument being played, and their experience level. Bipolar surface electrodes have been used in the past to monitor such activity, but this method is highly sensitive to the location of the electrode pair. In this work, the spatial distribution of surface EMG (sEMG) of the right trapezius and right and left erector spinae muscles were studied in 16 violin players and 11 cello players. Musicians played their instrument one string at a time in sitting position with/without backrest support. A 64 sEMG electrode (16×4) grid, 10mm inter-electrode distance (IED), was placed over the middle and lower trapezius (MT and LT) of the bowing arm. Two 16×2 electrode grids (IED=10mm) were placed on the left and right erector spinae muscles. Subjects played each of the four strings of the instrument either in large (1bow/s) or detaché tip/tail (8bows/s) bowing in two sessions (two days). In each of two days, measurements were repeated after half an hour of exercise to see the effect of exercise on the muscle activity and signal stability. A "muscle activity index" (MAI) was defined as the spatial average of the segmented active region of the RMS map. Spatial maps were automatically segmented using the watershed algorithm and thresholding. Results showed that, for violin players, sliding the bow upward from the tip toward the tail results in a higher MAI for the trapezius muscle than a downward bow. On the contrary, in cello players, higher MAI is produced in the tail to tip movement. For both instruments, an increasing MAI in the trapezius was observed as the string position became increasingly lateral, from string 1 (most medial) toward string 4 (most lateral). Half an hour of performance did not cause significant differences between the signal quality and the MAI values measured before and after the exercise. The MAI of the left and right erector spinae was smaller in the case of

  20. Differential effects of type of keyboard playing task and tempo on surface EMG amplitudes of forearm muscles

    Directory of Open Access Journals (Sweden)

    Hyun Ju eChong

    2015-09-01

    Full Text Available Despite increasing interest in keyboard playing as a strategy for repetitive finger exercises in fine motor skill development and hand rehabilitation, comparative analysis of task-specific finger movements relevant to keyboard playing has been less extensive. This study examined whether there were differences in surface EMG activity levels of forearm muscles associated with different keyboard playing tasks. Results demonstrated higher muscle activity with sequential keyboard playing in a random pattern compared to individuated playing or sequential playing in a successive pattern. Also, the speed of finger movements was found as a factor that affect muscle activity levels, demonstrating that faster tempo elicited significantly greater muscle activity than self-paced tempo. The results inform our understanding of the type of finger movements involved in different types of keyboard playing at different tempi so as to consider the efficacy and fatigue level of keyboard playing as an intervention for amateur pianists or individuals with impaired fine motor skills.

  1. Automotive System for Remote Surface Classification.

    Science.gov (United States)

    Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

    2017-04-01

    In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions.

  2. EMG (elektromyografie jako metoda pro sledování účinnosti sportovního tréninku Surface EMG as a method for following-up sports training efficiency

    Directory of Open Access Journals (Sweden)

    Damian Miklavčič

    2005-02-01

    Full Text Available Účel této studie byl zhodnotit vhodnost a použitelnost povrchové elektromyografie pro vyhodnocení změn kontrakčních vlastností svalů spojených s tréninkem. Skupina osmi národních juniorských tenistů se zúčastnila šestitýdenního výcvikového programu, který byl zaměřen na zvýšení rychlosti a výbušnosti. Jejich fyzické charakteristiky byly zhodnoceny před a po období programu, a to specifickými tenisovými testy, které měří izometrickou kontrakci trhnutí středního gastroknemického svalu, a zaznamenáváním spektra frekvence EMG při 50% maximální volní kontrakci. Ve specifických tenisových testech se prokázalo, že většina hráčů zlepšila své výkony po výcvikovém období, pouze u 3 hráčů byla zjištěna zvýšená rychlost kontrakce středního gastroknemického svalu, která byla vyjádřena kratší dobou kontrakčního trhnutí po období výcviku. Stejní hráči předvedli vyšší charakteristickou frekvenci (definována jako střední frekvence ležící mezi 6. a 9. decilem spektrální distribuční funkce a širší EMG spektrum rozkmitu po výcvikovém období. Vysoká korelace byla zjištěna mezi počtem parametrů izometrické kontrakce trhnutí, která byla zlepšena o více než 2 % po období výcviku (Np, poměr mezi charakteristickou frekvencí po období výcviku (fA a před výcvikovým obdobím (fB (fA/fB (p = 0,0065, a také mezi Np a stoupáním lineárního přiblížení závislosti mezi decilovými frekvencemi signálů EMG po období výcviku (dAf a před výcvikovým obdobím (dBf (dAf = f(dBf (p = 0,0035. Korelace mezi počtem parametrů izometrické kontrakce trhnutí, které byly zlepšeny po období výcviku, a změny v charakteristických parametrech EMG evokují použitelnost EMG pro sledování účinnosti sportovního výcviku. The purpose of the present study was to evaluate the applicability of surface electromyography (EMG for evaluation of

  3. Effect of a combined inversion and plantarflexion surface on ankle kinematics and EMG activities in landing

    Directory of Open Access Journals (Sweden)

    Divya Bhaskaran

    2015-12-01

    Conclusion: These findings suggest that compared to the inversion surface, the combined plantarflexion and inversion surface seems to provide a more unstable surface condition for lateral ankle sprains during landing.

  4. Surface EMG electrodes do not accurately record from lumbar multifidus muscles.

    Science.gov (United States)

    Stokes, Ian A F; Henry, Sharon M; Single, Richard M

    2003-01-01

    This study investigated whether electromyographic signals recorded from the skin surface overlying the multifidus muscles could be used to quantify their activity. Comparison of electromyography signals recorded from electrodes on the back surface and from wire electrodes within four different slips of multifidus muscles of three human subjects performing isometric tasks that loaded the trunk from three different directions. It has been suggested that suitably placed surface electrodes can be used to record activity in the deep multifidus muscles. We tested whether there was a stronger correlation and more consistent regression relationship between signals from electrodes overlying multifidus and longissimus muscles respectively than between signals from within multifidus and from the skin surface electrodes over multifidus. The findings provided consistent evidence that the surface electrodes placed over multifidus muscles were more sensitive to the adjacent longissimus muscles than to the underlying multifidus muscles. The R(2) for surface versus intra-muscular comparisons was 0.64, while the average R(2) for surface-multifidus versus surface-longissimus comparisons was 0.80. Also, the magnitude of the regression coefficients was less variable between different tasks for the longissimus versus surface multifidus comparisons. Accurate measurement of multifidus muscle activity requires intra-muscular electrodes. Electromyography is the accepted technique to document the level of muscular activation, but its specificity to particular muscles depends on correct electrode placement. For multifidus, intra-muscular electrodes are required.

  5. Differential effects of type of keyboard playing task and tempo on surface EMG amplitudes of forearm muscles

    Science.gov (United States)

    Chong, Hyun Ju; Kim, Soo Ji; Yoo, Ga Eul

    2015-01-01

    Despite increasing interest in keyboard playing as a strategy for repetitive finger exercises in fine motor skill development and hand rehabilitation, comparative analysis of task-specific finger movements relevant to keyboard playing has been less extensive. This study examined, whether there were differences in surface EMG activity levels of forearm muscles associated with different keyboard playing tasks. Results demonstrated higher muscle activity with sequential keyboard playing in a random pattern compared to individuated playing or sequential playing in a successive pattern. Also, the speed of finger movements was found as a factor that affect muscle activity levels, demonstrating that faster tempo elicited significantly greater muscle activity than self-paced tempo. The results inform our understanding of the type of finger movements involved in different types of keyboard playing at different tempi. This helps to consider the efficacy and fatigue level of keyboard playing tasks when being used as an intervention for amateur pianists or individuals with impaired fine motor skills. PMID:26388798

  6. Muscular Activities Measurements of Forward Lean and Upright Sitting Motorcycling Postures via Surface Electromyography (sEMG

    Directory of Open Access Journals (Sweden)

    Ma’arof Muhammad Izzat Nor

    2017-01-01

    Full Text Available Motorcycling postures are generically speculated to be physical and physiologically demanding – which in-turn may lead to motorcycling fatigue, and then becoming a possible factor to road accident. The objective of this study was to measure the muscular activities of various motorcycling postures. High muscular activity reading will signifies that motorcycling is indeed physically and physiologically demanding to the motorcyclist. For this particular study, the following postures were tested: i forward lean, ii upright sitting, and iii neutral sitting (as control. Surface electromyography (sEMG measurement was conducted on the following muscles: i extensor carpi radialis, ii upper trapezius iii latissimus dorsi, and iv erector spinae. The results showed that for all test subjects, the muscular activities readings for the forward lean posture was actually close to neutral sitting’s. Whilst, the upright sitting had showed much higher muscular activities measurement instead. Conclusively, this study had proven that any types of discomforts associated with the forward lean posture is not originated from muscular activities. Whereas, confirming that any discomforts in regards to the upright sitting is indeed related to muscular activities. Further studies are warranted to discover the actual risk factors that causes physical and physiological discomforts for the forward lean motorcycling posture.

  7. ECG artifact cancellation in surface EMG signals by fractional order calculus application.

    Science.gov (United States)

    Miljković, Nadica; Popović, Nenad; Djordjević, Olivera; Konstantinović, Ljubica; Šekara, Tomislav B

    2017-03-01

    New aspects for automatic electrocardiography artifact removal from surface electromyography signals by application of fractional order calculus in combination with linear and nonlinear moving window filters are explored. Surface electromyography recordings of skeletal trunk muscles are commonly contaminated with spike shaped artifacts. This artifact originates from electrical heart activity, recorded by electrocardiography, commonly present in the surface electromyography signals recorded in heart proximity. For appropriate assessment of neuromuscular changes by means of surface electromyography, application of a proper filtering technique of electrocardiography artifact is crucial. A novel method for automatic artifact cancellation in surface electromyography signals by applying fractional order calculus and nonlinear median filter is introduced. The proposed method is compared with the linear moving average filter, with and without prior application of fractional order calculus. 3D graphs for assessment of window lengths of the filters, crest factors, root mean square differences, and fractional calculus orders (called WFC and WRC graphs) have been introduced. For an appropriate quantitative filtering evaluation, the synthetic electrocardiography signal and analogous semi-synthetic dataset have been generated. The examples of noise removal in 10 able-bodied subjects and in one patient with muscle dystrophy are presented for qualitative analysis. The crest factors, correlation coefficients, and root mean square differences of the recorded and semi-synthetic electromyography datasets showed that the most successful method was the median filter in combination with fractional order calculus of the order 0.9. Statistically more significant (p ECG peak reduction was obtained by the median filter application compared to the moving average filter in the cases of low level amplitude of muscle contraction compared to ECG spikes. The presented results suggest that the

  8. EOG-sEMG Human Interface for Communication.

    Science.gov (United States)

    Tamura, Hiroki; Yan, Mingmin; Sakurai, Keiko; Tanno, Koichi

    2016-01-01

    The aim of this study is to present electrooculogram (EOG) and surface electromyogram (sEMG) signals that can be used as a human-computer interface. Establishing an efficient alternative channel for communication without overt speech and hand movements is important for increasing the quality of life for patients suffering from amyotrophic lateral sclerosis, muscular dystrophy, or other illnesses. In this paper, we propose an EOG-sEMG human-computer interface system for communication using both cross-channels and parallel lines channels on the face with the same electrodes. This system could record EOG and sEMG signals as "dual-modality" for pattern recognition simultaneously. Although as much as 4 patterns could be recognized, dealing with the state of the patients, we only choose two classes (left and right motion) of EOG and two classes (left blink and right blink) of sEMG which are easily to be realized for simulation and monitoring task. From the simulation results, our system achieved four-pattern classification with an accuracy of 95.1%.

  9. Virtual Sensor of Surface Electromyography in a New Extensive Fault-Tolerant Classification System.

    Science.gov (United States)

    de Moura, Karina de O A; Balbinot, Alexandre

    2018-05-01

    A few prosthetic control systems in the scientific literature obtain pattern recognition algorithms adapted to changes that occur in the myoelectric signal over time and, frequently, such systems are not natural and intuitive. These are some of the several challenges for myoelectric prostheses for everyday use. The concept of the virtual sensor, which has as its fundamental objective to estimate unavailable measures based on other available measures, is being used in other fields of research. The virtual sensor technique applied to surface electromyography can help to minimize these problems, typically related to the degradation of the myoelectric signal that usually leads to a decrease in the classification accuracy of the movements characterized by computational intelligent systems. This paper presents a virtual sensor in a new extensive fault-tolerant classification system to maintain the classification accuracy after the occurrence of the following contaminants: ECG interference, electrode displacement, movement artifacts, power line interference, and saturation. The Time-Varying Autoregressive Moving Average (TVARMA) and Time-Varying Kalman filter (TVK) models are compared to define the most robust model for the virtual sensor. Results of movement classification were presented comparing the usual classification techniques with the method of the degraded signal replacement and classifier retraining. The experimental results were evaluated for these five noise types in 16 surface electromyography (sEMG) channel degradation case studies. The proposed system without using classifier retraining techniques recovered of mean classification accuracy was of 4% to 38% for electrode displacement, movement artifacts, and saturation noise. The best mean classification considering all signal contaminants and channel combinations evaluated was the classification using the retraining method, replacing the degraded channel by the virtual sensor TVARMA model. This method

  10. Assessment of work-related muscle strain by using surface EMG during test contractions interposed between work periods of simulateted mushroom picking

    DEFF Research Database (Denmark)

    Ohashi, Jun-Ya; Blangsted, Anne Katrine; Nielsen, Pernille Kofoed

    2010-01-01

    Surface electromyograms(EMG) during test contractions (TCs) were studied to assess the muscle strain in simulated mushroom picking. Additionally, the duration of the TC for the effective assessment was investigated. Nine female subjects performed standardized shoulder abduction and a stooped...... posture for one minute as TCs. Each experiment consisted of a 60-min rest, three work periods (W1-W3), a 30-min rest, and two work periods (W4 and W5) separated by a 30-min rest period. The duration of each work period was about 20 min. A total of 18 TCs was performed between the work periods and every 10...

  11. GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PROSUCTS

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    K. Fukue

    2016-06-01

    Full Text Available The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year SR(Surface Reflectance and NBAR(Nadir BRDF-Adjusted Reflectance products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR and NBAR products showed similar classification accuracy of 99%.

  12. Fractal based modelling and analysis of electromyography (EMG) to identify subtle actions.

    Science.gov (United States)

    Arjunan, Sridhar P; Kumar, Dinesh K

    2007-01-01

    The paper reports the use of fractal theory and fractal dimension to study the non-linear properties of surface electromyogram (sEMG) and to use these properties to classify subtle hand actions. The paper reports identifying a new feature of the fractal dimension, the bias that has been found to be useful in modelling the muscle activity and of sEMG. Experimental results demonstrate that the feature set consisting of bias values and fractal dimension of the recordings is suitable for classification of sEMG against the different hand gestures. The scatter plots demonstrate the presence of simple relationships of these features against the four hand gestures. The results indicate that there is small inter-experimental variation but large inter-subject variation. This may be due to differences in the size and shape of muscles for different subjects. The possible applications of this research include use in developing prosthetic hands, controlling machines and computers.

  13. Analysis of EMG Signals in Aggressive and Normal Activities by Using Higher-Order Spectra

    Directory of Open Access Journals (Sweden)

    Necmettin Sezgin

    2012-01-01

    Full Text Available The analysis and classification of electromyography (EMG signals are very important in order to detect some symptoms of diseases, prosthetic arm/leg control, and so on. In this study, an EMG signal was analyzed using bispectrum, which belongs to a family of higher-order spectra. An EMG signal is the electrical potential difference of muscle cells. The EMG signals used in the present study are aggressive or normal actions. The EMG dataset was obtained from the machine learning repository. First, the aggressive and normal EMG activities were analyzed using bispectrum and the quadratic phase coupling of each EMG episode was determined. Next, the features of the analyzed EMG signals were fed into learning machines to separate the aggressive and normal actions. The best classification result was 99.75%, which is sufficient to significantly classify the aggressive and normal actions.

  14. Analysis of EMG Signals in Aggressive and Normal Activities by Using Higher-Order Spectra

    Science.gov (United States)

    Sezgin, Necmettin

    2012-01-01

    The analysis and classification of electromyography (EMG) signals are very important in order to detect some symptoms of diseases, prosthetic arm/leg control, and so on. In this study, an EMG signal was analyzed using bispectrum, which belongs to a family of higher-order spectra. An EMG signal is the electrical potential difference of muscle cells. The EMG signals used in the present study are aggressive or normal actions. The EMG dataset was obtained from the machine learning repository. First, the aggressive and normal EMG activities were analyzed using bispectrum and the quadratic phase coupling of each EMG episode was determined. Next, the features of the analyzed EMG signals were fed into learning machines to separate the aggressive and normal actions. The best classification result was 99.75%, which is sufficient to significantly classify the aggressive and normal actions. PMID:23193379

  15. Pathological tremor prediction using surface EMG and acceleration: potential use in “ON-OFF” demand driven deep brain stimulator design

    Science.gov (United States)

    Basu, Ishita; Graupe, Daniel; Tuninetti, Daniela; Shukla, Pitamber; Slavin, Konstantin V.; Metman, Leo Verhagen; Corcos, Daniel M.

    2013-01-01

    Objective We present a proof of concept for a novel method of predicting the onset of pathological tremor using non-invasively measured surface electromyogram (sEMG) and acceleration from tremor-affected extremities of patients with Parkinson’s disease (PD) and Essential tremor (ET). Approach The tremor prediction algorithm uses a set of spectral (fourier and wavelet) and non-linear time series (entropy and recurrence rate) parameters extracted from the non-invasively recorded sEMG and acceleration signals. Main results The resulting algorithm is shown to successfully predict tremor onset for all 91 trials recorded in 4 PD patients and for all 91 trials recorded in 4 ET patients. The predictor achieves a 100% sensitivity for all trials considered, along with an overall accuracy of 85.7% for all ET trials and 80.2% for all PD trials. By using a Pearson’s chi-square test, the prediction results are shown to significantly differ from a random prediction outcome. Significance The tremor prediction algorithm can be potentially used for designing the next generation of non-invasive closed-loop predictive ON-OFF controllers for deep brain stimulation (DBS), used for suppressing pathological tremor in such patients. Such a system is based on alternating ON and OFF DBS periods, an incoming tremor being predicted during the time intervals when DBS is OFF, so as to turn DBS back ON. The prediction should be a few seconds before tremor re-appears so that the patient is tremor-free for the entire DBS ON-OFF cycle as well as the tremor-free DBS OFF interval should be maximized in order to minimize the current injected in the brain and battery usage. PMID:23658233

  16. The impact of shoulder abduction loading on EMG-based intention detection of hand opening and closing after stroke.

    Science.gov (United States)

    Lan, Yiyun; Yao, Jun; Dewald, Julius P A

    2011-01-01

    Many stroke patients are subject to limited hand functions in the paretic arm due to a significant loss of Corticospinal Tract (CST) fibers. A possible solution for this problem is to classify surface Electromyography (EMG) signals generated by hand movements and uses that to implement Functional Electrical Stimulation (FES). However, EMG usually presents an abnormal muscle coactivation pattern shown as increased coupling between muscles within and/or across joints after stroke. The resulting Abnormal Muscle Synergies (AMS) could make the classification more difficult in individuals with stroke, especially when attempting to use the hand together with other joints in the paretic arm. Therefore, this study is aimed at identifying the impact of AMS following stroke on EMG pattern recognition between two hand movements. In an effort to achieve this goal, 7 chronic hemiparetic chronic stroke subjects were recruited and asked to perform hand opening and closing movements at their paretic arm while being either fully supported by a virtual table or loaded with 25% of subject's maximum shoulder abduction force. During the execution of motor tasks EMG signals from the wrist flexors and extensors were simultaneously acquired. Our results showed that increased synergy-induced activity at elbow flexors, induced by increasing shoulder abduction loading, deteriorated the performance of EMG pattern recognition for hand opening for those with a weak grasp strength and EMG activity. However, no such impact on hand closing has yet been observed possibly because finger/wrist flexion is facilitated by the shoulder abduction-induced flexion synergy.

  17. Basic Hand Gestures Classification Based on Surface Electromyography

    Directory of Open Access Journals (Sweden)

    Aleksander Palkowski

    2016-01-01

    Full Text Available This paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average classification rate of 98.12% has been achieved for the proposed method.

  18. EMG-Torque Relation in Chronic Stroke: A Novel EMG Complexity Representation With a Linear Electrode Array.

    Science.gov (United States)

    Zhang, Xu; Wang, Dongqing; Yu, Zaiyang; Chen, Xiang; Li, Sheng; Zhou, Ping

    2017-11-01

    This study examines the electromyogram (EMG)-torque relation for chronic stroke survivors using a novel EMG complexity representation. Ten stroke subjects performed a series of submaximal isometric elbow flexion tasks using their affected and contralateral arms, respectively, while a 20-channel linear electrode array was used to record surface EMG from the biceps brachii muscles. The sample entropy (SampEn) of surface EMG signals was calculated with both global and local tolerance schemes. A regression analysis was performed between SampEn of each channel's surface EMG and elbow flexion torque. It was found that a linear regression can be used to well describe the relation between surface EMG SampEn and the torque. Each channel's root mean square (RMS) amplitude of surface EMG signal in the different torque level was computed to determine the channel with the highest EMG amplitude. The slope of the regression (observed from the channel with the highest EMG amplitude) was smaller on the impaired side than on the nonimpaired side in 8 of the 10 subjects, regardless of the tolerance scheme (global or local) and the range of torques (full or matched range) used for comparison. The surface EMG signals from the channels above the estimated muscle innervation zones demonstrated significantly lower levels of complexity compared with other channels between innervation zones and muscle tendons. The study provides a novel point of view of the EMG-torque relation in the complexity domain, and reveals its alterations post stroke, which are associated with complex neural and muscular changes post stroke. The slope difference between channels with regard to innervation zones also confirms the relevance of electrode position in surface EMG analysis.

  19. FEATURE EXTRACTION FOR EMG BASED PROSTHESES CONTROL

    Directory of Open Access Journals (Sweden)

    R. Aishwarya

    2013-01-01

    Full Text Available The control of prosthetic limb would be more effective if it is based on Surface Electromyogram (SEMG signals from remnant muscles. The analysis of SEMG signals depend on a number of factors, such as amplitude as well as time- and frequency-domain properties. Time series analysis using Auto Regressive (AR model and Mean frequency which is tolerant to white Gaussian noise are used as feature extraction techniques. EMG Histogram is used as another feature vector that was seen to give more distinct classification. The work was done with SEMG dataset obtained from the NINAPRO DATABASE, a resource for bio robotics community. Eight classes of hand movements hand open, hand close, Wrist extension, Wrist flexion, Pointing index, Ulnar deviation, Thumbs up, Thumb opposite to little finger are taken into consideration and feature vectors are extracted. The feature vectors can be given to an artificial neural network for further classification in controlling the prosthetic arm which is not dealt in this paper.

  20. A mechatronics platform to study prosthetic hand control using EMG signals.

    Science.gov (United States)

    Geethanjali, P

    2016-09-01

    In this paper, a low-cost mechatronics platform for the design and development of robotic hands as well as a surface electromyogram (EMG) pattern recognition system is proposed. This paper also explores various EMG classification techniques using a low-cost electronics system in prosthetic hand applications. The proposed platform involves the development of a four channel EMG signal acquisition system; pattern recognition of acquired EMG signals; and development of a digital controller for a robotic hand. Four-channel surface EMG signals, acquired from ten healthy subjects for six different movements of the hand, were used to analyse pattern recognition in prosthetic hand control. Various time domain features were extracted and grouped into five ensembles to compare the influence of features in feature-selective classifiers (SLR) with widely considered non-feature-selective classifiers, such as neural networks (NN), linear discriminant analysis (LDA) and support vector machines (SVM) applied with different kernels. The results divulged that the average classification accuracy of the SVM, with a linear kernel function, outperforms other classifiers with feature ensembles, Hudgin's feature set and auto regression (AR) coefficients. However, the slight improvement in classification accuracy of SVM incurs more processing time and memory space in the low-level controller. The Kruskal-Wallis (KW) test also shows that there is no significant difference in the classification performance of SLR with Hudgin's feature set to that of SVM with Hudgin's features along with AR coefficients. In addition, the KW test shows that SLR was found to be better in respect to computation time and memory space, which is vital in a low-level controller. Similar to SVM, with a linear kernel function, other non-feature selective LDA and NN classifiers also show a slight improvement in performance using twice the features but with the drawback of increased memory space requirement and time

  1. Optimal Elbow Angle for Extracting sEMG Signals During Fatiguing Dynamic Contraction

    Directory of Open Access Journals (Sweden)

    Mohamed R. Al-Mulla

    2015-09-01

    Full Text Available Surface electromyographic (sEMG activity of the biceps muscle was recorded from 13 subjects. Data was recorded while subjects performed dynamic contraction until fatigue and the signals were segmented into two parts (Non-Fatigue and Fatigue. An evolutionary algorithm was used to determine the elbow angles that best separate (using Davies-Bouldin Index, DBI both Non-Fatigue and Fatigue segments of the sEMG signal. Establishing the optimal elbow angle for feature extraction used in the evolutionary process was based on 70% of the conducted sEMG trials. After completing 26 independent evolution runs, the best run containing the optimal elbow angles for separation (Non-Fatigue and Fatigue was selected and then tested on the remaining 30% of the data to measure the classification performance. Testing the performance of the optimal angle was undertaken on nine features extracted from each of the two classes (Non-Fatigue and Fatigue to quantify the performance. Results showed that the optimal elbow angles can be used for fatigue classification, showing 87.90% highest correct classification for one of the features and on average of all eight features (including worst performing features giving 78.45%.

  2. Capacitively coupled EMG detection via ultra-low-power microcontroller STFT.

    Science.gov (United States)

    Roland, Theresa; Baumgartner, Werner; Amsuess, Sebastian; Russold, Michael F

    2017-07-01

    As motion artefacts are a major problem with electromyography sensors, a new algorithm is developed to differentiate artefacts to contraction EMG. The performance of myoelectric prosthesis is increased with this algorithm. The implementation is done for an ultra-low-power microcontroller with limited calculation resources and memory. Short Time Fourier Transformation is used to enable real-time application. The sum of the differences (SOD) of the currently measured EMG to a reference contraction EMG is calculated. The SOD is a new parameter introduced for EMG classification. The satisfactory error rates are determined by measurements done with the capacitively coupling EMG prototype, recently developed by the research group.

  3. sEMG feature evaluation for identification of elbow angle resolution in graded arm movement.

    Science.gov (United States)

    Castro, Maria Claudia F; Colombini, Esther L; Aquino, Plinio T; Arjunan, Sridhar P; Kumar, Dinesh K

    2014-11-25

    Automatic and accurate identification of elbow angle from surface electromyogram (sEMG) is essential for myoelectric controlled upper limb exoskeleton systems. This requires appropriate selection of sEMG features, and identifying the limitations of such a system.This study has demonstrated that it is possible to identify three discrete positions of the elbow; full extension, right angle, and mid-way point, with window size of only 200 milliseconds. It was seen that while most features were suitable for this purpose, Power Spectral Density Averages (PSD-Av) performed best. The system correctly classified the sEMG against the elbow angle for 100% cases when only two discrete positions (full extension and elbow at right angle) were considered, while correct classification was 89% when there were three discrete positions. However, sEMG was unable to accurately determine the elbow position when five discrete angles were considered. It was also observed that there was no difference for extension or flexion phases.

  4. Evaluation of muscle fatigue of wheelchair basketball players with spinal cord injury using recurrence quantification analysis of surface EMG.

    Science.gov (United States)

    Uzun, S; Pourmoghaddam, A; Hieronymus, M; Thrasher, T A

    2012-11-01

    Wheelchair basketball is the most popular exercise activity among individuals with spinal cord injury (SCI). The purpose of this study was to investigate muscular endurance and fatigue in wheelchair basketball athletes with SCI using surface electromyography (SEMG) and maximal torque values. SEMG characteristics of 10 wheelchair basketball players (WBP) were compared to 13 able-bodied basketball players and 12 sedentary able-bodied subjects. Participants performed sustained isometric elbow flexion at 50% maximal voluntary contraction until exhaustion. Elbow flexion torque and SEMG signals were recorded from three elbow flexor muscles: biceps brachii longus, biceps brachii brevis and brachioradialis. SEMG signals were clustered into 0.5-s epochs with 50% overlap. Root mean square (RMS) and median frequency (MDF) of SEMG signals were calculated for each muscle and epoch as traditional fatigue monitoring. Recurrence quantification analysis was used to extract the percentage of determinism (%DET) of SEMG signals. The slope of the %DET for basketball players and WBP showed slower increase with time than the sedentary able-bodied control group for three different elbow flexor muscles, while no difference was observed for the slope of the %DET between basketball and WBP. This result indicated that the athletes are less fatigable during the task effort than the nonathletes. Normalized MDF slope decay exhibited similar results between the groups as %DET, while the slope of the normalized RMS failed to show any significant differences among the groups (p > 0.05). MDF and %DET could be useful for the evaluation of muscle fatigue in wheelchair basketball training. No conclusions about special training for WBP could be determined.

  5. Surface water classification and monitoring using polarimetric synthetic aperture radar

    Science.gov (United States)

    Irwin, Katherine Elizabeth

    Surface water classification using synthetic aperture radar (SAR) is an established practice for monitoring flood hazards due to the high temporal and spatial resolution it provides. Surface water change is a dynamic process that varies both spatially and temporally, and can occur on various scales resulting in significant impacts on affected areas. Small-scale flooding hazards, caused by beaver dam failure, is an example of surface water change, which can impact nearby infrastructure and ecosystems. Assessing these hazards is essential to transportation and infrastructure maintenance. With current satellite missions operating in multiple polarizations, spatio-temporal resolutions, and frequencies, a comprehensive comparison between SAR products for surface water monitoring is necessary. In this thesis, surface water extent models derived from high resolution single-polarization TerraSAR-X (TSX) data, medium resolution dual-polarization TSX data and low resolution quad-polarization RADARSAT-2 (RS-2) data are compared. There exists a compromise between acquiring SAR data with a high resolution or high information content. Multi-polarization data provides additional phase and intensity information, which makes it possible to better classify areas of flooded vegetation and wetlands. These locations are often where fluctuations in surface water occur and are essential for understanding dynamic underlying processes. However, often multi-polarized data is acquired at a low resolution, which cannot image these zones effectively. High spatial resolution, single-polarization TSX data provides the best model of open water. However, these single-polarization observations have limited information content and are affected by shadow and layover errors. This often hinders the classification of other land cover types. The dual-polarization TSX data allows for the classification of flooded vegetation, but classification is less accurate compared to the quad-polarization RS-2 data

  6. Object-based Dimensionality Reduction in Land Surface Phenology Classification

    Directory of Open Access Journals (Sweden)

    Brian E. Bunker

    2016-11-01

    Full Text Available Unsupervised classification or clustering of multi-decadal land surface phenology provides a spatio-temporal synopsis of natural and agricultural vegetation response to environmental variability and anthropogenic activities. Notwithstanding the detailed temporal information available in calibrated bi-monthly normalized difference vegetation index (NDVI and comparable time series, typical pre-classification workflows average a pixel’s bi-monthly index within the larger multi-decadal time series. While this process is one practical way to reduce the dimensionality of time series with many hundreds of image epochs, it effectively dampens temporal variation from both intra and inter-annual observations related to land surface phenology. Through a novel application of object-based segmentation aimed at spatial (not temporal dimensionality reduction, all 294 image epochs from a Moderate Resolution Imaging Spectroradiometer (MODIS bi-monthly NDVI time series covering the northern Fertile Crescent were retained (in homogenous landscape units as unsupervised classification inputs. Given the inherent challenges of in situ or manual image interpretation of land surface phenology classes, a cluster validation approach based on transformed divergence enabled comparison between traditional and novel techniques. Improved intra-annual contrast was clearly manifest in rain-fed agriculture and inter-annual trajectories showed increased cluster cohesion, reducing the overall number of classes identified in the Fertile Crescent study area from 24 to 10. Given careful segmentation parameters, this spatial dimensionality reduction technique augments the value of unsupervised learning to generate homogeneous land surface phenology units. By combining recent scalable computational approaches to image segmentation, future work can pursue new global land surface phenology products based on the high temporal resolution signatures of vegetation index time series.

  7. Are chronic neck pain, scapular dyskinesis and altered scapulothoracic muscle activity interrelated?: A case-control study with surface and fine-wire EMG.

    Science.gov (United States)

    Castelein, Birgit; Cools, Ann; Parlevliet, Thierry; Cagnie, Barbara

    2016-12-01

    The function of the scapula is important in normal neck function and might be disturbed in patients with neck pain. The surrounding muscular system is important for the function of the scapula. To date, it is not clear if patients with idiopathic neck pain show altered activity of these scapulothoracic muscles. Therefore, the objective of this study was to investigate differences in deeper and superficial lying scapulothoracic muscle activity between patients with idiopathic neck pain and healthy controls during arm elevation, and to identify the influence of scapular dyskinesis on muscle activity. Scapular dyskinesis was rated with the yes/no method. The deeper lying (Levator Scapulae, Pectoralis Minor (Pm) and Rhomboid major) and superficial lying (Trapezius and Serratus Anterior) scapulothoracic muscles' activity was investigated with fine-wire and surface EMG, respectively, in 19 female subjects with idiopathic neck pain (age 28.3±10.1years, average duration of neck pain 45.6±36.3months) and 19 female healthy control subjects (age 29.3±11.7years) while performing scaption and towel wall slide. Possible interactions or differences between subject groups, scapular dyskinesis groups or phases of the task were studied with a linear mixed model. Higher Pm activity during the towel wallslide (p=0.024, mean difference 8.8±3.3% MVIC) was shown in patients with idiopathic neck pain in comparison with healthy controls. For the MT, a significant group∗dyskinesis interaction effect was found during scaption which revealed that patients with neck pain and scapular dyskinesis showed lower Middle Trapezius (MT) activity in comparison with healthy controls with scapular dyskinesis (p=0.029, mean difference 5.1±2.2% MVIC). In the presence of idiopathic neck pain, higher Pm activity during the towel wallslide was found. Patients with neck pain and scapular dyskinesis showed lower MT activity in comparison with healthy controls with scapular dyskinesis during scaption

  8. Qualitative internal surface roughness classification using acoustic emission

    International Nuclear Information System (INIS)

    Mohd Hafizi Zohari; Mohd Hanif Saad

    2009-04-01

    This paper describes a novel new nondestructive method of qualitative internal surface roughness classification for pipes utilizing Acoustic Emission (AE) signal. Two different flowrate are introduced in a pipe obstructed using normally available components (e.g.: valve). The AE signal at suitable location from the obstruction are obtained and the peak amplitudes, RMS amplitude and energy of the AE signal are obtained. A dimensionless number, the Bangi Number, AB, is then calculated as a ratio of the AE parameters (peak amplitude, RMS amplitude or energy) in low flowrate measurement compared to the AE parameters in high flowrate measurement. It was observed that the Bangi Number, AB obtained can then be used to successfully discriminate between rough and smooth internal surface roughness. (author)

  9. Differential topology of complex surfaces elliptic surfaces with p g=1 smooth classification

    CERN Document Server

    Morgan, John W

    1993-01-01

    This book is about the smooth classification of a certain class of algebraicsurfaces, namely regular elliptic surfaces of geometric genus one, i.e. elliptic surfaces with b1 = 0 and b2+ = 3. The authors give a complete classification of these surfaces up to diffeomorphism. They achieve this result by partially computing one of Donalson's polynomial invariants. The computation is carried out using techniques from algebraic geometry. In these computations both thebasic facts about the Donaldson invariants and the relationship of the moduli space of ASD connections with the moduli space of stable bundles are assumed known. Some familiarity with the basic facts of the theory of moduliof sheaves and bundles on a surface is also assumed. This work gives a good and fairly comprehensive indication of how the methods of algebraic geometry can be used to compute Donaldson invariants.

  10. Classification Order of Surface-Confined Intermixing at Epitaxial Interface

    Science.gov (United States)

    Michailov, M.

    The self-organization phenomena at epitaxial interface hold special attention in contemporary material science. Being relevant to the fundamental physical problem of competing, long-range and short-range atomic interactions in systems with reduced dimensionality, these phenomena have found exacting academic interest. They are also of great technological importance for their ability to bring spontaneous formation of regular nanoscale surface patterns and superlattices with exotic properties. The basic phenomenon involved in this process is surface diffusion. That is the motivation behind the present study which deals with important details of diffusion scenarios that control the fine atomic structure of epitaxial interface. Consisting surface imperfections (terraces, steps, kinks, and vacancies), the interface offers variety of barriers for surface diffusion. Therefore, the adatoms and clusters need a certain critical energy to overcome the corresponding diffusion barriers. In the most general case the critical energies can be attained by variation of the system temperature. Hence, their values define temperature limits of system energy gaps associated with different diffusion scenarios. This systematization imply classification order of surface alloying: blocked, incomplete, and complete. On that background, two diffusion problems, related to the atomic-scale surface morphology, will be discussed. The first problem deals with diffusion of atomic clusters on atomically smooth interface. On flat domains, far from terraces and steps, we analyzed the impact of size, shape, and cluster/substrate lattice misfit on the diffusion behavior of atomic clusters (islands). We found that the lattice constant of small clusters depends on the number N of building atoms at 1 < N ≤ 10. In heteroepitaxy, this effect of variable lattice constant originates from the enhanced charge transfer and the strong influence of the surface potential on cluster atomic arrangement. At constant

  11. Novel Feature Modelling the Prediction and Detection of sEMG Muscle Fatigue towards an Automated Wearable System

    Directory of Open Access Journals (Sweden)

    Mohamed R. Al-Mulla

    2010-05-01

    Full Text Available Surface Electromyography (sEMG activity of the biceps muscle was recorded from ten subjects performing isometric contraction until fatigue. A novel feature (1D spectro_std was used to extract the feature that modeled three classes of fatigue, which enabled the prediction and detection of fatigue. Initial results of class separation were encouraging, discriminating between the three classes of fatigue, a longitudinal classification on Non-Fatigue and Transition-to-Fatigue shows 81.58% correct classification with accuracy 0.74 of correct predictions while the longitudinal classification on Transition-to-Fatigue and Fatigue showed lower average correct classification of 66.51% with a positive classification accuracy 0.73 of correct prediction. Comparison of the 1D spectro_std with other sEMG fatigue features on the same dataset show a significant improvement in classification, where results show a significant 20.58% (p < 0.01 improvement when using the 1D spectro_std to classify Non-Fatigue and Transition-to-Fatigue. In classifying Transition-to-Fatigue and Fatigue results also show a significant improvement over the other features giving 8.14% (p < 0.05 on average of all compared features.

  12. Power frequency spectrum analysis of surface EMG signals of upper limb muscles during elbow flexion - A comparison between healthy subjects and stroke survivors.

    Science.gov (United States)

    Angelova, Silvija; Ribagin, Simeon; Raikova, Rositsa; Veneva, Ivanka

    2018-02-01

    After a stroke, motor units stop working properly and large, fast-twitch units are more frequently affected. Their impaired functions can be investigated during dynamic tasks using electromyographic (EMG) signal analysis. The aim of this paper is to investigate changes in the parameters of the power/frequency function during elbow flexion between affected, non-affected, and healthy muscles. Fifteen healthy subjects and ten stroke survivors participated in the experiments. Electromyographic data from 6 muscles of the upper limbs during elbow flexion were filtered and normalized to the amplitudes of EMG signals during maximal isometric tasks. The moments when motion started and when the flexion angle reached its maximal value were found. Equal intervals of 0.3407 s were defined between these two moments and one additional interval before the start of the flexion (first one) was supplemented. For each of these intervals the power/frequency function of EMG signals was calculated. The mean (MNF) and median frequencies (MDF), the maximal power (MPw) and the area under the power function (APw) were calculated. MNF was always higher than MDF. A significant decrease in these frequencies was found in only three post-stroke survivors. The frequencies in the first time interval were nearly always the highest among all intervals. The maximal power was nearly zero during first time interval and increased during the next ones. The largest values of MPw and APw were found for the flexor muscles and they increased for the muscles of the affected arm compared to the non-affected one of stroke survivors. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Hand Motion Classification Using a Multi-Channel Surface Electromyography Sensor

    Directory of Open Access Journals (Sweden)

    Dong Sun

    2012-01-01

    Full Text Available The human hand has multiple degrees of freedom (DOF for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG sensors are a low-cost method for identifying hand motions, in addition to the conventional methods that use data gloves and vision detection. The identification of multiple hand motions is challenging because the error rate typically increases significantly with the addition of more hand motions. Thus, the current study proposes two new methods for feature extraction to solve the problem above. The first method is the extraction of the energy ratio features in the time-domain, which are robust and invariant to motion forces and speeds for the same gesture. The second method is the extraction of the concordance correlation features that describe the relationship between every two channels of the multi-channel sEMG sensor system. The concordance correlation features of a multi-channel sEMG sensor system were shown to provide a vast amount of useful information for identification. Furthermore, a new cascaded-structure classifier is also proposed, in which 11 types of hand gestures can be identified accurately using the newly defined features. Experimental results show that the success rate for the identification of the 11 gestures is significantly high.

  14. Hand motion classification using a multi-channel surface electromyography sensor.

    Science.gov (United States)

    Tang, Xueyan; Liu, Yunhui; Lv, Congyi; Sun, Dong

    2012-01-01

    The human hand has multiple degrees of freedom (DOF) for achieving high-dexterity motions. Identifying and replicating human hand motions are necessary to perform precise and delicate operations in many applications, such as haptic applications. Surface electromyography (sEMG) sensors are a low-cost method for identifying hand motions, in addition to the conventional methods that use data gloves and vision detection. The identification of multiple hand motions is challenging because the error rate typically increases significantly with the addition of more hand motions. Thus, the current study proposes two new methods for feature extraction to solve the problem above. The first method is the extraction of the energy ratio features in the time-domain, which are robust and invariant to motion forces and speeds for the same gesture. The second method is the extraction of the concordance correlation features that describe the relationship between every two channels of the multi-channel sEMG sensor system. The concordance correlation features of a multi-channel sEMG sensor system were shown to provide a vast amount of useful information for identification. Furthermore, a new cascaded-structure classifier is also proposed, in which 11 types of hand gestures can be identified accurately using the newly defined features. Experimental results show that the success rate for the identification of the 11 gestures is significantly high.

  15. USDA soil classification system dictates site surface management

    International Nuclear Information System (INIS)

    Bowmer, W.J.

    1985-01-01

    Success or failure of site surface management practices greatly affects long-term site stability. The US Department of Agriculture (USDA) soil classification system best documents those parameters which control the success of installed practices for managing both erosion and surface drainage. The USDA system concentrates on soil characteristics in the upper three meters of the surface that support the associated flora both physically and physiologically. The USDA soil survey first identifies soil series based on detailed characteristics that are related to production potential. Using the production potential, land use capability classes are developed. Capability classes reveal the highest and best agronomic use for the site. Lower number classes are considered arable while higher number classes are best suited for grazing agriculture. Application of ecological principles based on the USDA soil survey reveals the current state of the site relative to its ecological potential. To assure success, site management practices must be chosen that are compatible with both production capability and current state of the site

  16. CLASSIFICATION OF WATER SURFACES USING AIRBORNE TOPOGRAPHIC LIDAR DATA

    Directory of Open Access Journals (Sweden)

    J. Smeeckaert

    2013-05-01

    Full Text Available Accurate Digital Terrain Models (DTM are inevitable inputs for mapping areas subject to natural hazards. Topographic airborne laser scanning has become an established technique to characterize the Earth surface: lidar provides 3D point clouds allowing a fine reconstruction of the topography. For flood hazard modeling, the key step before terrain modeling is the discrimination of land and water surfaces within the delivered point clouds. Therefore, instantaneous shoreline, river borders, inland waters can be extracted as a basis for more reliable DTM generation. This paper presents an automatic, efficient, and versatile workflow for land/water classification of airborne topographic lidar data. For that purpose, a classification framework based on Support Vector Machines (SVM is designed. First, a restricted set of features, based only 3D lidar point coordinates and flightline information, is defined. Then, the SVM learning step is performed on small but well-targeted areas thanks to an automatic region growing strategy. Finally, label probabilities given by the SVM are merged during a probabilistic relaxation step in order to remove pixel-wise misclassification. Results show that survey of millions of points are labelled with high accuracy (>95% in most cases for coastal areas, and >89% for rivers and that small natural and anthropic features of interest are still well classified though we work at low point densities (0.5–4 pts/m2. Our approach is valid for coasts and rivers, and provides a strong basis for further discrimination of land-cover classes and coastal habitats.

  17. [Surface electromyography signal classification using gray system theory].

    Science.gov (United States)

    Xie, Hongbo; Ma, Congbin; Wang, Zhizhong; Huang, Hai

    2004-12-01

    A new method based on gray correlation was introduced to improve the identification rate in artificial limb. The electromyography (EMG) signal was first transformed into time-frequency domain by wavelet transform. Singular value decomposition (SVD) was then used to extract feature vector from the wavelet coefficient for pattern recognition. The decision was made according to the maximum gray correlation coefficient. Compared with neural network recognition, this robust method has an almost equivalent recognition rate but much lower computation costs and less training samples.

  18. Review: Painless EMG in Children

    Directory of Open Access Journals (Sweden)

    Mahmoud Mohammadi

    2003-12-01

    Full Text Available Thanks to new techniques in Pediatric Neurology , nowadays we are more able to detect and differentiate different diseases of the nerves and muscles in children . Although these techniques are sometimes more sensitive and specific than EMG in children, but EMG and NCV study has its specific role in pediatric neurology and this is because of more availability and feasibility of these tests in children . One of the main Limitations of EMG techniques especially in pediatric age group is the pain induced by the insertion of needle electrodes into muscle as well as electrical stimulations needed to do NCV and other studies. So, all the experts in the field are trying to find some methods to reduce the pain induced by this technique . I have tried to introduce some of these methods after a brief explanation about pediatric EMG technique.

  19. Continuous and simultaneous estimation of finger kinematics using inputs from an EMG-to-muscle activation model.

    Science.gov (United States)

    Ngeo, Jimson G; Tamei, Tomoya; Shibata, Tomohiro

    2014-08-14

    Surface electromyography (EMG) signals are often used in many robot and rehabilitation applications because these reflect motor intentions of users very well. However, very few studies have focused on the accurate and proportional control of the human hand using EMG signals. Many have focused on discrete gesture classification and some have encountered inherent problems such as electro-mechanical delays (EMD). Here, we present a new method for estimating simultaneous and multiple finger kinematics from multi-channel surface EMG signals. In this study, surface EMG signals from the forearm and finger kinematic data were extracted from ten able-bodied subjects while they were tasked to do individual and simultaneous multiple finger flexion and extension movements in free space. Instead of using traditional time-domain features of EMG, an EMG-to-Muscle Activation model that parameterizes EMD was used and shown to give better estimation performance. A fast feed forward artificial neural network (ANN) and a nonparametric Gaussian Process (GP) regressor were both used and evaluated to estimate complex finger kinematics, with the latter rarely used in the other related literature. The estimation accuracies, in terms of mean correlation coefficient, were 0.85 ± 0.07, 0.78 ± 0.06 and 0.73 ± 0.04 for the metacarpophalangeal (MCP), proximal interphalangeal (PIP) and the distal interphalangeal (DIP) finger joint DOFs, respectively. The mean root-mean-square error in each individual DOF ranged from 5 to 15%. We show that estimation improved using the proposed muscle activation inputs compared to other features, and that using GP regression gave better estimation results when using fewer training samples. The proposed method provides a viable means of capturing the general trend of finger movements and shows a good way of estimating finger joint kinematics using a muscle activation model that parameterizes EMD. The results from this study demonstrates a potential control

  20. An ICA-EBM-Based sEMG Classifier for Recognizing Lower Limb Movements in Individuals With and Without Knee Pathology.

    Science.gov (United States)

    Naik, Ganesh R; Selvan, S Easter; Arjunan, Sridhar P; Acharyya, Amit; Kumar, Dinesh K; Ramanujam, Arvind; Nguyen, Hung T

    2018-03-01

    Surface electromyography (sEMG) data acquired during lower limb movements has the potential for investigating knee pathology. Nevertheless, a major challenge encountered with sEMG signals generated by lower limb movements is the intersubject variability, because the signals recorded from the leg or thigh muscles are contingent on the characteristics of a subject such as gait activity and muscle structure. In order to cope with this difficulty, we have designed a three-step classification scheme. First, the multichannel sEMG is decomposed into activities of the underlying sources by means of independent component analysis via entropy bound minimization. Next, a set of time-domain features, which would best discriminate various movements, are extracted from the source estimates. Finally, the feature selection is performed with the help of the Fisher score and a scree-plot-based statistical technique, prior to feeding the dimension-reduced features to the linear discriminant analysis. The investigation involves 11 healthy subjects and 11 individuals with knee pathology performing three different lower limb movements, namely, walking, sitting, and standing, which yielded an average classification accuracy of 96.1% and 86.2%, respectively. While the outcome of this study per se is very encouraging, with suitable improvement, the clinical application of such an sEMG-based pattern recognition system that distinguishes healthy and knee pathological subjects would be an attractive consequence.

  1. Stretchable human-machine interface based on skin-conformal sEMG electrodes with self-similar geometry

    Science.gov (United States)

    Dong, Wentao; Zhu, Chen; Hu, Wei; Xiao, Lin; Huang, Yong'an

    2018-01-01

    Current stretchable surface electrodes have attracted increasing attention owing to their potential applications in biological signal monitoring, wearable human-machine interfaces (HMIs) and the Internet of Things. The paper proposed a stretchable HMI based on a surface electromyography (sEMG) electrode with a self-similar serpentine configuration. The sEMG electrode was transfer-printed onto the skin surface conformally to monitor biological signals, followed by signal classification and controlling of a mobile robot. Such electrodes can bear rather large deformation (such as >30%) under an appropriate areal coverage. The sEMG electrodes have been used to record electrophysiological signals from different parts of the body with sharp curvature, such as the index finger, back of the neck and face, and they exhibit great potential for HMI in the fields of robotics and healthcare. The electrodes placed onto the two wrists would generate two different signals with the fist clenched and loosened. It is classified to four kinds of signals with a combination of the gestures from the two wrists, that is, four control modes. Experiments demonstrated that the electrodes were successfully used as an HMI to control the motion of a mobile robot remotely. Project supported by the National Natural Science Foundation of China (Nos. 51635007, 91323303).

  2. EMG of the hip adductor muscles in six clinical examination tests.

    Science.gov (United States)

    Lovell, Gregory A; Blanch, Peter D; Barnes, Christopher J

    2012-08-01

    To assess activation of muscles of hip adduction using EMG and force analysis during standard clinical tests, and compare athletes with and without a prior history of groin pain. Controlled laboratory study. 21 male athletes from an elite junior soccer program. Bilateral surface EMG recordings of the adductor magnus, adductor longus, gracilis and pectineus as well as a unilateral fine-wire EMG of the pectineus were made during isometric holds in six clinical examination tests. A load cell was used to measure force data. Test type was a significant factor in the EMG output for all four muscles (all muscles p stronger than Hips 45, Hips 90 and Side lay. BMI (body mass index) was a significant factor (p Muscle EMG varied significantly with clinical test position. Athletes with previous groin injury had a significant fall in some EMG outputs. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. EMG-Torque Dynamics Change With Contraction Bandwidth.

    Science.gov (United States)

    Golkar, Mahsa A; Jalaleddini, Kian; Kearney, Robert E

    2018-04-01

    An accurate model for ElectroMyoGram (EMG)-torque dynamics has many uses. One of its applications which has gained high attention among researchers is its use, in estimating the muscle contraction level for the efficient control of prosthesis. In this paper, the dynamic relationship between the surface EMG and torque during isometric contractions at the human ankle was studied using system identification techniques. Subjects voluntarily modulated their ankle torque in dorsiflexion direction, by activating their tibialis anterior muscle, while tracking a pseudo-random binary sequence in a torque matching task. The effects of contraction bandwidth, described by torque spectrum, on EMG-torque dynamics were evaluated by varying the visual command switching time. Nonparametric impulse response functions (IRF) were estimated between the processed surface EMG and torque. It was demonstrated that: 1) at low contraction bandwidths, the identified IRFs had unphysiological anticipatory (i.e., non-causal) components, whose amplitude decreased as the contraction bandwidth increased. We hypothesized that this non-causal behavior arose, because the EMG input contained a component due to feedback from the output torque, i.e., it was recorded from within a closed-loop. Vision was not the feedback source since the non-causal behavior persisted when visual feedback was removed. Repeating the identification using a nonparametric closed-loop identification algorithm yielded causal IRFs at all bandwidths, supporting this hypothesis. 2) EMG-torque dynamics became faster and the bandwidth of system increased as contraction modulation rate increased. Thus, accurate prediction of torque from EMG signals must take into account the contraction bandwidth sensitivity of this system.

  4. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  5. Differences in the EMG pattern of lea muscle activation during locomotion in Parkinson's disease

    NARCIS (Netherlands)

    Albani, G; Sandrini, G; Kunig, G; Martin-Soelch, C; Mauro, A; Pignatti, R; Pacchetti, C; Dietz, [No Value; Leenders, KL

    2003-01-01

    In this pilot study, EMG patterns of leg muscle activation were studied in five parkinsonian patients with (B1) and five without (B2) freezing. Gastrocnemius medialis (GM) and tibialis anterior (TA) activity was analysed, by means of surface electromyography (EMG), during treadmill walking at two

  6. A novel method for EMG decomposition based on matched filters

    Directory of Open Access Journals (Sweden)

    Ailton Luiz Dias Siqueira Júnior

    Full Text Available Introduction Decomposition of electromyography (EMG signals into the constituent motor unit action potentials (MUAPs can allow for deeper insights into the underlying processes associated with the neuromuscular system. The vast majority of the methods for EMG decomposition found in the literature depend on complex algorithms and specific instrumentation. As an attempt to contribute to solving these issues, we propose a method based on a bank of matched filters for the decomposition of EMG signals. Methods Four main units comprise our method: a bank of matched filters, a peak detector, a motor unit classifier and an overlapping resolution module. The system’s performance was evaluated with simulated and real EMG data. Classification accuracy was measured by comparing the responses of the system with known data from the simulator and with the annotations of a human expert. Results The results show that decomposition of non-overlapping MUAPs can be achieved with up to 99% accuracy for signals with up to 10 active motor units and a signal-to-noise ratio (SNR of 10 dB. For overlapping MUAPs with up to 10 motor units per signal and a SNR of 20 dB, the technique allows for correct classification of approximately 71% of the MUAPs. The method is capable of processing, decomposing and classifying a 50 ms window of data in less than 5 ms using a standard desktop computer. Conclusion This article contributes to the ongoing research on EMG decomposition by describing a novel technique capable of delivering high rates of success by means of a fast algorithm, suggesting its possible use in future real-time embedded applications, such as myoelectric prostheses control and biofeedback systems.

  7. sEMG-Based Gesture Recognition with Convolution Neural Networks

    Directory of Open Access Journals (Sweden)

    Zhen Ding

    2018-06-01

    Full Text Available The traditional classification methods for limb motion recognition based on sEMG have been deeply researched and shown promising results. However, information loss during feature extraction reduces the recognition accuracy. To obtain higher accuracy, the deep learning method was introduced. In this paper, we propose a parallel multiple-scale convolution architecture. Compared with the state-of-art methods, the proposed architecture fully considers the characteristics of the sEMG signal. Larger sizes of kernel filter than commonly used in other CNN-based hand recognition methods are adopted. Meanwhile, the characteristics of the sEMG signal, that is, muscle independence, is considered when designing the architecture. All the classification methods were evaluated on the NinaPro database. The results show that the proposed architecture has the highest recognition accuracy. Furthermore, the results indicate that parallel multiple-scale convolution architecture with larger size of kernel filter and considering muscle independence can significantly increase the classification accuracy.

  8. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  9. Simultaneous EEG and EMG biofeedback for peak performance in musicians.

    Science.gov (United States)

    Markovska-Simoska, Silvana; Pop-Jordanova, Nada; Georgiev, Dejan

    2008-07-01

    The aim of this study was to determine the effects of alpha neurofeedback and EMG biofeedback protocols for improvement of musical performance in violinists. The sample consisted of 12 music students (10 violinists and 2 viola players) from the Faculty of Music, Skopje (3 males, mean age of 20 +/- 0 and 9 females, mean age = 20.89 +/- 2.98). Six of them had a low alpha peak frequency (APF) ( 10 Hz). The sample was randomized in two groups. The students from the experimental group participated in 20 sessions of biofeedback (alpha/EMG), combined with music practice, while the students from the control group did only music practice. Average absolute power, interhemispheric coherence in the alpha band, alpha peak frequency (APF), individual alpha band width (IABW), amount of alpha suppression (AAS) and surface forehead integrated EMG power (IEMG), as well as a score on musical performance and inventories measuring anxiety, were assessed. Alpha-EEG/EMG-biofeedback was associated with a significant increase in average alpha power, APF and IABW in all the participants and with decreases in IEMG only in high-APF musicians. The biofeedback training success was positively correlated with the alpha power, IcoH, APF, IABW and baseline level of APF and IABW. Alpha-EEG/EMG biofeedback is capable of increasing voluntary self-regulation and the quality of musical performance. The efficiency of biofeedback training depends on the baseline EEG alpha activity status, in particular the APF.

  10. Latent Factors Limiting the Performance of sEMG-Interfaces

    Directory of Open Access Journals (Sweden)

    Sergey Lobov

    2018-04-01

    Full Text Available Recent advances in recording and real-time analysis of surface electromyographic signals (sEMG have fostered the use of sEMG human–machine interfaces for controlling personal computers, prostheses of upper limbs, and exoskeletons among others. Despite a relatively high mean performance, sEMG-interfaces still exhibit strong variance in the fidelity of gesture recognition among different users. Here, we systematically study the latent factors determining the performance of sEMG-interfaces in synthetic tests and in an arcade game. We show that the degree of muscle cooperation and the amount of the body fatty tissue are the decisive factors in synthetic tests. Our data suggest that these factors can only be adjusted by long-term training, which promotes fine-tuning of low-level neural circuits driving the muscles. Short-term training has no effect on synthetic tests, but significantly increases the game scoring. This implies that it works at a higher decision-making level, not relevant for synthetic gestures. We propose a procedure that enables quantification of the gestures’ fidelity in a dynamic gaming environment. For each individual subject, the approach allows identifying “problematic” gestures that decrease gaming performance. This information can be used for optimizing the training strategy and for adapting the signal processing algorithms to individual users, which could be a way for a qualitative leap in the development of future sEMG-interfaces.

  11. Emg Signal Analysis of Healthy and Neuropathic Individuals

    Science.gov (United States)

    Gupta, Ashutosh; Sayed, Tabassum; Garg, Ridhi; Shreyam, Richa

    2017-08-01

    Electromyography is a method to evaluate levels of muscle activity. When a muscle contracts, an action potential is generated and this circulates along the muscular fibers. In electromyography, electrodes are connected to the skin and the electrical activity of muscles is measured and graph is plotted. The surface EMG signals picked up during the muscular activity are interfaced with a system. The EMG signals from individual suffering from Neuropathy and healthy individual, so obtained, are processed and analyzed using signal processing techniques. This project includes the investigation and interpretation of EMG signals of healthy and Neuropathic individuals using MATLAB. The prospective use of this study is in developing the prosthetic device for the people with Neuropathic disability.

  12. Site Classification using Multichannel Channel Analysis of Surface Wave (MASW) method on Soft and Hard Ground

    Science.gov (United States)

    Ashraf, M. A. M.; Kumar, N. S.; Yusoh, R.; Hazreek, Z. A. M.; Aziman, M.

    2018-04-01

    Site classification utilizing average shear wave velocity (Vs(30) up to 30 meters depth is a typical parameter. Numerous geophysical methods have been proposed for estimation of shear wave velocity by utilizing assortment of testing configuration, processing method, and inversion algorithm. Multichannel Analysis of Surface Wave (MASW) method is been rehearsed by numerous specialist and professional to geotechnical engineering for local site characterization and classification. This study aims to determine the site classification on soft and hard ground using MASW method. The subsurface classification was made utilizing National Earthquake Hazards Reduction Program (NERHP) and international Building Code (IBC) classification. Two sites are chosen to acquire the shear wave velocity which is in the state of Pulau Pinang for soft soil and Perlis for hard rock. Results recommend that MASW technique can be utilized to spatially calculate the distribution of shear wave velocity (Vs(30)) in soil and rock to characterize areas.

  13. A Versatile Embedded Platform for EMG Acquisition and Gesture Recognition.

    Science.gov (United States)

    Benatti, Simone; Casamassima, Filippo; Milosevic, Bojan; Farella, Elisabetta; Schönle, Philipp; Fateh, Schekeb; Burger, Thomas; Huang, Qiuting; Benini, Luca

    2015-10-01

    Wearable devices offer interesting features, such as low cost and user friendliness, but their use for medical applications is an open research topic, given the limited hardware resources they provide. In this paper, we present an embedded solution for real-time EMG-based hand gesture recognition. The work focuses on the multi-level design of the system, integrating the hardware and software components to develop a wearable device capable of acquiring and processing EMG signals for real-time gesture recognition. The system combines the accuracy of a custom analog front end with the flexibility of a low power and high performance microcontroller for on-board processing. Our system achieves the same accuracy of high-end and more expensive active EMG sensors used in applications with strict requirements on signal quality. At the same time, due to its flexible configuration, it can be compared to the few wearable platforms designed for EMG gesture recognition available on market. We demonstrate that we reach similar or better performance while embedding the gesture recognition on board, with the benefit of cost reduction. To validate this approach, we collected a dataset of 7 gestures from 4 users, which were used to evaluate the impact of the number of EMG channels, the number of recognized gestures and the data rate on the recognition accuracy and on the computational demand of the classifier. As a result, we implemented a SVM recognition algorithm capable of real-time performance on the proposed wearable platform, achieving a classification rate of 90%, which is aligned with the state-of-the-art off-line results and a 29.7 mW power consumption, guaranteeing 44 hours of continuous operation with a 400 mAh battery.

  14. Classification of Steps on Road Surface Using Acceleration Signals

    Directory of Open Access Journals (Sweden)

    Junji Takahashi

    2015-12-01

    Full Text Available In order to reduce a road monitoring cost, we propose a system to monitor extensively road condition by cyclists with a smartphone. In this paper, we propose two methods towards road monitoring. First is to classify road signals to four road conditions. Second is to extract road signal from a smartphone's accelerometer in three positions: pants' side pocket, chest pocket and a bag in a front basket. In pants' side pocket, road signal is extracted by Independent Component Analysis. In chest pocket and bag in a front basket, road signal is extracted by selecting 1-axis affected from gravitational acceleration. In the experiment of the classification method, overall accuracy was 75%. The experimental results of the extraction methods with correlation coefficient showed the overall accuracy were more than 0.7 in pants' side pocket and chest pocket, the overall accuracy was less than 0.3 in bag in a front basket.

  15. Detection of driving fatigue by using noncontact EMG and ECG signals measurement system.

    Science.gov (United States)

    Fu, Rongrong; Wang, Hong

    2014-05-01

    Driver fatigue can be detected by constructing a discriminant mode using some features obtained from physiological signals. There exist two major challenges of this kind of methods. One is how to collect physiological signals from subjects while they are driving without any interruption. The other is to find features of physiological signals that are of corresponding change with the loss of attention caused by driver fatigue. Driving fatigue is detected based on the study of surface electromyography (EMG) and electrocardiograph (ECG) during the driving period. The noncontact data acquisition system was used to collect physiological signals from the biceps femoris of each subject to tackle the first challenge. Fast independent component analysis (FastICA) and digital filter were utilized to process the original signals. Based on the statistical analysis results given by Kolmogorov-Smirnov Z test, the peak factor of EMG (p fatigue of drivers. The discriminant criterion of fatigue was obtained from the training samples by using Mahalanobis distance, and then the average classification accuracy was given by 10-fold cross-validation. The results showed that the method proposed in this paper can give well performance in distinguishing the normal state and fatigue state. The noncontact, onboard vehicle drivers' fatigue detection system was developed to reduce fatigue-related risks.

  16. A COMPARATIVE-STUDY OF ELECTROMYOGRAMS OF THE MASSETER, TEMPORALIS, AND ANTERIOR DIGASTRIC MUSCLES OBTAINED BY SURFACE AND INTRAMUSCULAR ELECTRODES - RAW-EMG

    NARCIS (Netherlands)

    KOOLE, P; DEJONGH, HJ; BOERING, G

    Electromyographic activity was synchronously recorded by surface and intramuscular electrodes in the same muscle. The activity of the left masseter, left temporalis, and both bellies of the anterior digastric muscle was studied by this double registration technique. In rest position no

  17. Behaviour of a surface EMG based measure for motor control: Motor unit action potential rate in relation to force and muscle fatigue

    NARCIS (Netherlands)

    Kallenberg, L.A.C.; Hermens, Hermanus J.

    2008-01-01

    Surface electromyography parameters such as root-mean-square value (RMS) and median power frequency (FMED) are commonly used to assess the input of the central nervous system (CNS) to a muscle. However, RMS and FMED are influenced not only by CNS input, but also by peripheral muscle properties. The

  18. Sequential decoding of intramuscular EMG signals via estimation of a Markov model.

    Science.gov (United States)

    Monsifrot, Jonathan; Le Carpentier, Eric; Aoustin, Yannick; Farina, Dario

    2014-09-01

    This paper addresses the sequential decoding of intramuscular single-channel electromyographic (EMG) signals to extract the activity of individual motor neurons. A hidden Markov model is derived from the physiological generation of the EMG signal. The EMG signal is described as a sum of several action potentials (wavelet) trains, embedded in noise. For each train, the time interval between wavelets is modeled by a process that parameters are linked to the muscular activity. The parameters of this process are estimated sequentially by a Bayes filter, along with the firing instants. The method was tested on some simulated signals and an experimental one, from which the rates of detection and classification of action potentials were above 95% with respect to the reference decomposition. The method works sequentially in time, and is the first to address the problem of intramuscular EMG decomposition online. It has potential applications for man-machine interfacing based on motor neuron activities.

  19. SURF'S UP! – Protein classification by surface comparisons

    Indian Academy of Sciences (India)

    Prakash

    encounter large protein families with only a few members of ... server for analysis of functional relationships in protein families, as inferred from protein surface maps comparison ... features, SURF'S UP! can work with models obtained from comparative modelling. ... 1997) or, if the user is confident in the quality of automated.

  20. A Study on EMG-based Biometrics

    OpenAIRE

    Jin Su Kim; Sung Bum Pan

    2017-01-01

    Biometrics is a technology that recognizes user's information by using unique physical features of his or her body such as face, fingerprint, and iris. It also uses behavioral features such as signature, electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG). Among them, the EMG signal is a sign generated when the muscles move, which can be used in various fields such as motion recognition, personal identification, and disease diagnosis. In this paper, we analyze EMG-ba...

  1. Detection and classification of orange peel on polished steel surfaces by interferometric microscopy

    International Nuclear Information System (INIS)

    2T Research GmbH, Viktor Kaplan Strasse 2, Wiener Neustadt 2700 (Austria))" data-affiliation=" (AC2T Research GmbH, Viktor Kaplan Strasse 2, Wiener Neustadt 2700 (Austria))" >Miranda-Medina, M L; 2T Research GmbH, Viktor Kaplan Strasse 2, Wiener Neustadt 2700 (Austria))" data-affiliation=" (AC2T Research GmbH, Viktor Kaplan Strasse 2, Wiener Neustadt 2700 (Austria))" >Somkuti, P; 2T Research GmbH, Viktor Kaplan Strasse 2, Wiener Neustadt 2700 (Austria))" data-affiliation=" (AC2T Research GmbH, Viktor Kaplan Strasse 2, Wiener Neustadt 2700 (Austria))" >Steiger, B

    2013-01-01

    In this work, we provide a general description of the so-called orange peel defect produced on polished steel surfaces. By characterizing a prototype set of samples with various degrees orange peel, we attempt to create a simple model that allows the classification of additional samples through the study of surface parameters. On those surfaces, the orange peel structure has roughness amplitudes in the nanometer range. Detecting surface features on that range requires the implementation of a high-precision technique, such as phase shifting interferometry (PSI). Therefore, we can contribute to the improvement of the manufacturing of polished steel surfaces as well as to the quality control by using optical techniques.

  2. Evaluation of jaw and neck muscle activities while chewing using EMG-EMG transfer function and EMG-EMG coherence function analyses in healthy subjects.

    Science.gov (United States)

    Ishii, Tomohiro; Narita, Noriyuki; Endo, Hiroshi

    2016-06-01

    This study aims to quantitatively clarify the physiological features in rhythmically coordinated jaw and neck muscle EMG activities while chewing gum using EMG-EMG transfer function and EMG-EMG coherence function analyses in 20 healthy subjects. The chewing side masseter muscle EMG signal was used as the reference signal, while the other jaw (non-chewing side masseter muscle, bilateral anterior temporal muscles, and bilateral anterior digastric muscles) and neck muscle (bilateral sternocleidomastoid muscles) EMG signals were used as the examined signals in EMG-EMG transfer function and EMG-EMG coherence function analyses. Chewing-related jaw and neck muscle activities were aggregated in the first peak of the power spectrum in rhythmic chewing. The gain in the peak frequency represented the power relationships between jaw and neck muscle activities during rhythmic chewing. The phase in the peak frequency represented the temporal relationships between the jaw and neck muscle activities, while the non-chewing side neck muscle presented a broad range of distributions across jaw closing and opening phases. Coherence in the peak frequency represented the synergistic features in bilateral jaw closing muscles and chewing side neck muscle activities. The coherence and phase in non-chewing side neck muscle activities exhibited a significant negative correlation. From above, the bilateral coordination between the jaw and neck muscle activities is estimated while chewing when the non-chewing side neck muscle is synchronously activated with the jaw closing muscles, while the unilateral coordination is estimated when the non-chewing side neck muscle is irregularly activated in the jaw opening phase. Thus, the occurrence of bilateral or unilateral coordinated features in the jaw and neck muscle activities may correspond to the phase characteristics in the non-chewing side neck muscle activities during rhythmical chewing. Considering these novel findings in healthy subjects, EMG-EMG

  3. Defect detection and classification of machined surfaces under multiple illuminant directions

    Science.gov (United States)

    Liao, Yi; Weng, Xin; Swonger, C. W.; Ni, Jun

    2010-08-01

    Continuous improvement of product quality is crucial to the successful and competitive automotive manufacturing industry in the 21st century. The presence of surface porosity located on flat machined surfaces such as cylinder heads/blocks and transmission cases may allow leaks of coolant, oil, or combustion gas between critical mating surfaces, thus causing damage to the engine or transmission. Therefore 100% inline inspection plays an important role for improving product quality. Although the techniques of image processing and machine vision have been applied to machined surface inspection and well improved in the past 20 years, in today's automotive industry, surface porosity inspection is still done by skilled humans, which is costly, tedious, time consuming and not capable of reliably detecting small defects. In our study, an automated defect detection and classification system for flat machined surfaces has been designed and constructed. In this paper, the importance of the illuminant direction in a machine vision system was first emphasized and then the surface defect inspection system under multiple directional illuminations was designed and constructed. After that, image processing algorithms were developed to realize 5 types of 2D or 3D surface defects (pore, 2D blemish, residue dirt, scratch, and gouge) detection and classification. The steps of image processing include: (1) image acquisition and contrast enhancement (2) defect segmentation and feature extraction (3) defect classification. An artificial machined surface and an actual automotive part: cylinder head surface were tested and, as a result, microscopic surface defects can be accurately detected and assigned to a surface defect class. The cycle time of this system can be sufficiently fast that implementation of 100% inline inspection is feasible. The field of view of this system is 150mm×225mm and the surfaces larger than the field of view can be stitched together in software.

  4. Effect of vibrotactile feedback on an EMG-based proportional cursor control system.

    Science.gov (United States)

    Li, Shunchong; Chen, Xingyu; Zhang, Dingguo; Sheng, Xinjun; Zhu, Xiangyang

    2013-01-01

    Surface electromyography (sEMG) has been introduced into the bio-mechatronics systems, however, most of them are lack of the sensory feedback. In this paper, the effect of vibrotactile feedback for a myoelectric cursor control system is investigated quantitatively. Simultaneous and proportional control signals are extracted from EMG using a muscle synergy model. Different types of feedback including vibrotactile feedback and visual feedback are added, assessed and compared with each other. The results show that vibrotactile feedback is capable of improving the performance of EMG-based human machine interface.

  5. Repeatability of grasp recognition for robotic hand prosthesis control based on sEMG data.

    Science.gov (United States)

    Palermo, Francesca; Cognolato, Matteo; Gijsberts, Arjan; Muller, Henning; Caputo, Barbara; Atzori, Manfredo

    2017-07-01

    Control methods based on sEMG obtained promising results for hand prosthetics. Control system robustness is still often inadequate and does not allow the amputees to perform a large number of movements useful for everyday life. Only few studies analyzed the repeatability of sEMG classification of hand grasps. The main goals of this paper are to explore repeatability in sEMG data and to release a repeatability database with the recorded experiments. The data are recorded from 10 intact subjects repeating 7 grasps 12 times, twice a day for 5 days. The data are publicly available on the Ninapro web page. The analysis for the repeatability is based on the comparison of movement classification accuracy in several data acquisitions and for different subjects. The analysis is performed using mean absolute value and waveform length features and a Random Forest classifier. The accuracy obtained by training and testing on acquisitions at different times is on average 27.03% lower than training and testing on the same acquisition. The results obtained by training and testing on different acquisitions suggest that previous acquisitions can be used to train the classification algorithms. The inter-subject variability is remarkable, suggesting that specific characteristics of the subjects can affect repeatibility and sEMG classification accuracy. In conclusion, the results of this paper can contribute to develop more robust control systems for hand prostheses, while the presented data allows researchers to test repeatability in further analyses.

  6. Generating Control Commands From Gestures Sensed by EMG

    Science.gov (United States)

    Wheeler, Kevin R.; Jorgensen, Charles

    2006-01-01

    An effort is under way to develop noninvasive neuro-electric interfaces through which human operators could control systems as diverse as simple mechanical devices, computers, aircraft, and even spacecraft. The basic idea is to use electrodes on the surface of the skin to acquire electromyographic (EMG) signals associated with gestures, digitize and process the EMG signals to recognize the gestures, and generate digital commands to perform the actions signified by the gestures. In an experimental prototype of such an interface, the EMG signals associated with hand gestures are acquired by use of several pairs of electrodes mounted in sleeves on a subject s forearm (see figure). The EMG signals are sampled and digitized. The resulting time-series data are fed as input to pattern-recognition software that has been trained to distinguish gestures from a given gesture set. The software implements, among other things, hidden Markov models, which are used to recognize the gestures as they are being performed in real time. Thus far, two experiments have been performed on the prototype interface to demonstrate feasibility: an experiment in synthesizing the output of a joystick and an experiment in synthesizing the output of a computer or typewriter keyboard. In the joystick experiment, the EMG signals were processed into joystick commands for a realistic flight simulator for an airplane. The acting pilot reached out into the air, grabbed an imaginary joystick, and pretended to manipulate the joystick to achieve left and right banks and up and down pitches of the simulated airplane. In the keyboard experiment, the subject pretended to type on a numerical keypad, and the EMG signals were processed into keystrokes. The results of the experiments demonstrate the basic feasibility of this method while indicating the need for further research to reduce the incidence of errors (including confusion among gestures). Topics that must be addressed include the numbers and arrangements

  7. Grip Force and 3D Push-Pull Force Estimation Based on sEMG and GRNN

    Directory of Open Access Journals (Sweden)

    Changcheng Wu

    2017-06-01

    Full Text Available The estimation of the grip force and the 3D push-pull force (push and pull force in the three dimension space from the electromyogram (EMG signal is of great importance in the dexterous control of the EMG prosthetic hand. In this paper, an action force estimation method which is based on the eight channels of the surface EMG (sEMG and the Generalized Regression Neural Network (GRNN is proposed to meet the requirements of the force control of the intelligent EMG prosthetic hand. Firstly, the experimental platform, the acquisition of the sEMG, the feature extraction of the sEMG and the construction of GRNN are described. Then, the multi-channels of the sEMG when the hand is moving are captured by the EMG sensors attached on eight different positions of the arm skin surface. Meanwhile, a grip force sensor and a three dimension force sensor are adopted to measure the output force of the human's hand. The characteristic matrix of the sEMG and the force signals are used to construct the GRNN. The mean absolute value and the root mean square of the estimation errors, the correlation coefficients between the actual force and the estimated force are employed to assess the accuracy of the estimation. Analysis of variance (ANOVA is also employed to test the difference of the force estimation. The experiments are implemented to verify the effectiveness of the proposed estimation method and the results show that the output force of the human's hand can be correctly estimated by using sEMG and GRNN method.

  8. A new scheme for urban impervious surface classification from SAR images

    Science.gov (United States)

    Zhang, Hongsheng; Lin, Hui; Wang, Yunpeng

    2018-05-01

    Urban impervious surfaces have been recognized as a significant indicator for various environmental and socio-economic studies. There is an increasingly urgent demand for timely and accurate monitoring of the impervious surfaces with satellite technology from local to global scales. In the past decades, optical remote sensing has been widely employed for this task with various techniques. However, there are still a range of challenges, e.g. handling cloud contamination on optical data. Therefore, the Synthetic Aperture Radar (SAR) was introduced for the challenging task because it is uniquely all-time- and all-weather-capable. Nevertheless, with an increasing number of SAR data applied, the methodology used for impervious surfaces classification remains unchanged from the methods used for optical datasets. This shortcoming has prevented the community from fully exploring the potential of using SAR data for impervious surfaces classification. We proposed a new scheme that is comparable to the well-known and fundamental Vegetation-Impervious surface-Soil (V-I-S) model for mapping urban impervious surfaces. Three scenes of fully polarimetric Radsarsat-2 data for the cities of Shenzhen, Hong Kong and Macau were employed to test and validate the proposed methodology. Experimental results indicated that the overall accuracy and Kappa coefficient were 96.00% and 0.8808 in Shenzhen, 93.87% and 0.8307 in Hong Kong and 97.48% and 0.9354 in Macau, indicating the applicability and great potential of the new scheme for impervious surfaces classification using polarimetric SAR data. Comparison with the traditional scheme indicated that this new scheme was able to improve the overall accuracy by up to 4.6% and Kappa coefficient by up to 0.18.

  9. Unsupervised Classification of Surface Defects in Wire Rod Production Obtained by Eddy Current Sensors

    Directory of Open Access Journals (Sweden)

    Sergio Saludes-Rodil

    2015-04-01

    Full Text Available An unsupervised approach to classify surface defects in wire rod manufacturing is developed in this paper. The defects are extracted from an eddy current signal and classified using a clustering technique that uses the dynamic time warping distance as the dissimilarity measure. The new approach has been successfully tested using industrial data. It is shown that it outperforms other classification alternatives, such as the modified Fourier descriptors.

  10. Specialized Nerve Tests: EMG, NCV and SSEP

    Science.gov (United States)

    ... Treatment Spondylolisthesis BLOG FIND A SPECIALIST Treatments Specialized Nerve Tests: EMG, NCV and SSEP Ajay Jawahar MD ... spinal cord is the thick, whitish bundle of nerve tissue that extends from the lowest part of ...

  11. [The effect of EMG level by EMG biofeedback with progressive muscle relaxation training on tension headache].

    Science.gov (United States)

    Ro, U J; Kim, N C; Kim, H S

    1990-08-01

    The purpose of this study is to assess if EMG biofeedback training with progressive muscle relaxation training is effective in reducing the EMG level in patients with tension headaches. This study which lasted from 23 October to 30 December 1989, was conducted on 10 females who were diagnosed as patients with tension headaches and selected from among volunteers at C. University in Seoul. The process of the study was as follows: First, before the treatment, the baseline was measured for two weeks and the level of EMG was measured five times in five minutes. And then EMG biofeedback training was used for six weeks, 12 sessions in all, and progressive muscle relaxation was done at home by audio tape over eight weeks. Each session was composed of a 5-minute baseline, two 5-minute EMG biofeedback training periods and a 5-minute self-control stage. Each stage was followed by a five minute rest period. So each session took a total of 40 minutes. The EMG level was measured by EMG biofeedback (Autogenic-Cyborg: M 130 EMG module). The results were as follows: 1. The average age of the subjects was 44.1 years and the average history of headache was 10.6 years (range: 6 months-20 years). 2. The level of EMG was lowest between the third and the fourth week of the training except in Cases I and IV. 3. The patients began to show a nonconciliatory attitude at the first session of the fifth week of the training.

  12. User adaptation in long-term, open-loop myoelectric training: implications for EMG pattern recognition in prosthesis control

    Science.gov (United States)

    He, Jiayuan; Zhang, Dingguo; Jiang, Ning; Sheng, Xinjun; Farina, Dario; Zhu, Xiangyang

    2015-08-01

    Objective. Recent studies have reported that the classification performance of electromyographic (EMG) signals degrades over time without proper classification retraining. This problem is relevant for the applications of EMG pattern recognition in the control of active prostheses. Approach. In this study we investigated the changes in EMG classification performance over 11 consecutive days in eight able-bodied subjects and two amputees. Main results. It was observed that, when the classifier was trained on data from one day and tested on data from the following day, the classification error decreased exponentially but plateaued after four days for able-bodied subjects and six to nine days for amputees. The between-day performance became gradually closer to the corresponding within-day performance. Significance. These results indicate that the relative changes in EMG signal features over time become progressively smaller when the number of days during which the subjects perform the pre-defined motions are increased. The performance of the motor tasks is thus more consistent over time, resulting in more repeatable EMG patterns, even if the subjects do not have any external feedback on their performance. The learning curves for both able-bodied subjects and subjects with limb deficiencies could be modeled as an exponential function. These results provide important insights into the user adaptation characteristics during practical long-term myoelectric control applications, with implications for the design of an adaptive pattern recognition system.

  13. The COST733 circulation type classification software: an example for surface ozone concentrations in Central Europe

    Science.gov (United States)

    Demuzere, Matthias; Kassomenos, P.; Philipp, A.

    2011-08-01

    In the framework of the COST733 Action "Harmonisation and Applications of Weather Types Classifications for European Regions" a new circulation type classification software (hereafter, referred to as cost733class software) is developed. The cost733class software contains a variety of (European) classification methods and is flexible towards choice of domain of interest, input variables, time step, number of circulation types, sequencing and (weighted) target variables. This work introduces the capabilities of the cost733class software in which the resulting circulation types (CTs) from various circulation type classifications (CTCs) are applied on observed summer surface ozone concentrations in Central Europe. Firstly, the main characteristics of the CTCs in terms of circulation pattern frequencies are addressed using the baseline COST733 catalogue (cat 2.0), at present the latest product of the new cost733class software. In a second step, the probabilistic Brier skill score is used to quantify the explanatory power of all classifications in terms of the maximum 8 hourly mean ozone concentrations exceeding the 120-μg/m3 threshold; this was based on ozone concentrations from 130 Central European measurement stations. Averaged evaluation results over all stations indicate generally higher performance of CTCs with a higher number of types. Within the subset of methodologies with a similar number of types, the results suggest that the use of CTCs based on optimisation algorithms are performing slightly better than those which are based on other algorithms (predefined thresholds, principal component analysis and leader algorithms). The results are further elaborated by exploring additional capabilities of the cost733class software. Sensitivity experiments are performed using different domain sizes, input variables, seasonally based classifications and multiple-day sequencing. As an illustration, CTCs which are also conditioned towards temperature with various weights

  14. Reliable nanomaterial classification of powders using the volume-specific surface area method

    Energy Technology Data Exchange (ETDEWEB)

    Wohlleben, Wendel, E-mail: wendel.wohlleben@basf.com [Department of Material Physics, BASF SE (Germany); Mielke, Johannes [BAM–Federal Institute for Materials Research and Testing (Germany); Bianchin, Alvise [MBN Nanomaterialia s.p.a (Italy); Ghanem, Antoine [R& I Centre Brussels, Solvay (Belgium); Freiberger, Harald [Department of Material Physics, BASF SE (Germany); Rauscher, Hubert [European Commission, Nanobiosciences Unit, Joint Research Centre (Italy); Gemeinert, Marion; Hodoroaba, Vasile-Dan, E-mail: dan.hodoroaba@bam.de [BAM–Federal Institute for Materials Research and Testing (Germany)

    2017-02-15

    The volume-specific surface area (VSSA) of a particulate material is one of two apparently very different metrics recommended by the European Commission for a definition of “nanomaterial” for regulatory purposes: specifically, the VSSA metric may classify nanomaterials and non-nanomaterials differently than the median size in number metrics, depending on the chemical composition, size, polydispersity, shape, porosity, and aggregation of the particles in the powder. Here we evaluate the extent of agreement between classification by electron microscopy (EM) and classification by VSSA on a large set of diverse particulate substances that represent all the anticipated challenges except mixtures of different substances. EM and VSSA are determined in multiple labs to assess also the level of reproducibility. Based on the results obtained on highly characterized benchmark materials from the NanoDefine EU FP7 project, we derive a tiered screening strategy for the purpose of implementing the definition of nanomaterials. We finally apply the screening strategy to further industrial materials, which were classified correctly and left only borderline cases for EM. On platelet-shaped nanomaterials, VSSA is essential to prevent false-negative classification by EM. On porous materials, approaches involving extended adsorption isotherms prevent false positive classification by VSSA. We find no false negatives by VSSA, neither in Tier 1 nor in Tier 2, despite real-world industrial polydispersity and diverse composition, shape, and coatings. The VSSA screening strategy is recommended for inclusion in a technical guidance for the implementation of the definition.

  15. Reliable nanomaterial classification of powders using the volume-specific surface area method

    International Nuclear Information System (INIS)

    Wohlleben, Wendel; Mielke, Johannes; Bianchin, Alvise; Ghanem, Antoine; Freiberger, Harald; Rauscher, Hubert; Gemeinert, Marion; Hodoroaba, Vasile-Dan

    2017-01-01

    The volume-specific surface area (VSSA) of a particulate material is one of two apparently very different metrics recommended by the European Commission for a definition of “nanomaterial” for regulatory purposes: specifically, the VSSA metric may classify nanomaterials and non-nanomaterials differently than the median size in number metrics, depending on the chemical composition, size, polydispersity, shape, porosity, and aggregation of the particles in the powder. Here we evaluate the extent of agreement between classification by electron microscopy (EM) and classification by VSSA on a large set of diverse particulate substances that represent all the anticipated challenges except mixtures of different substances. EM and VSSA are determined in multiple labs to assess also the level of reproducibility. Based on the results obtained on highly characterized benchmark materials from the NanoDefine EU FP7 project, we derive a tiered screening strategy for the purpose of implementing the definition of nanomaterials. We finally apply the screening strategy to further industrial materials, which were classified correctly and left only borderline cases for EM. On platelet-shaped nanomaterials, VSSA is essential to prevent false-negative classification by EM. On porous materials, approaches involving extended adsorption isotherms prevent false positive classification by VSSA. We find no false negatives by VSSA, neither in Tier 1 nor in Tier 2, despite real-world industrial polydispersity and diverse composition, shape, and coatings. The VSSA screening strategy is recommended for inclusion in a technical guidance for the implementation of the definition.

  16. A sEMG model with experimentally based simulation parameters.

    Science.gov (United States)

    Wheeler, Katherine A; Shimada, Hiroshima; Kumar, Dinesh K; Arjunan, Sridhar P

    2010-01-01

    A differential, time-invariant, surface electromyogram (sEMG) model has been implemented. While it is based on existing EMG models, the novelty of this implementation is that it assigns more accurate distributions of variables to create realistic motor unit (MU) characteristics. Variables such as muscle fibre conduction velocity, jitter (the change in the interpulse interval between subsequent action potential firings) and motor unit size have been considered to follow normal distributions about an experimentally obtained mean. In addition, motor unit firing frequencies have been considered to have non-linear and type based distributions that are in accordance with experimental results. Motor unit recruitment thresholds have been considered to be related to the MU type. The model has been used to simulate single channel differential sEMG signals from voluntary, isometric contractions of the biceps brachii muscle. The model has been experimentally verified by conducting experiments on three subjects. Comparison between simulated signals and experimental recordings shows that the Root Mean Square (RMS) increases linearly with force in both cases. The simulated signals also show similar values and rates of change of RMS to the experimental signals.

  17. Classification of grass pollen through the quantitative analysis of surface ornamentation and texture.

    Science.gov (United States)

    Mander, Luke; Li, Mao; Mio, Washington; Fowlkes, Charless C; Punyasena, Surangi W

    2013-11-07

    Taxonomic identification of pollen and spores uses inherently qualitative descriptions of morphology. Consequently, identifications are restricted to categories that can be reliably classified by multiple analysts, resulting in the coarse taxonomic resolution of the pollen and spore record. Grass pollen represents an archetypal example; it is not routinely identified below family level. To address this issue, we developed quantitative morphometric methods to characterize surface ornamentation and classify grass pollen grains. This produces a means of quantifying morphological features that are traditionally described qualitatively. We used scanning electron microscopy to image 240 specimens of pollen from 12 species within the grass family (Poaceae). We classified these species by developing algorithmic features that quantify the size and density of sculptural elements on the pollen surface, and measure the complexity of the ornamentation they form. These features yielded a classification accuracy of 77.5%. In comparison, a texture descriptor based on modelling the statistical distribution of brightness values in image patches yielded a classification accuracy of 85.8%, and seven human subjects achieved accuracies between 68.33 and 81.67%. The algorithmic features we developed directly relate to biologically meaningful features of grass pollen morphology, and could facilitate direct interpretation of unsupervised classification results from fossil material.

  18. Influence of Joint Angle on EMG-Torque Model During Constant-Posture, Torque-Varying Contractions.

    Science.gov (United States)

    Liu, Pu; Liu, Lukai; Clancy, Edward A

    2015-11-01

    Relating the electromyogram (EMG) to joint torque is useful in various application areas, including prosthesis control, ergonomics and clinical biomechanics. Limited study has related EMG to torque across varied joint angles, particularly when subjects performed force-varying contractions or when optimized modeling methods were utilized. We related the biceps-triceps surface EMG of 22 subjects to elbow torque at six joint angles (spanning 60° to 135°) during constant-posture, torque-varying contractions. Three nonlinear EMG σ -torque models, advanced EMG amplitude (EMG σ ) estimation processors (i.e., whitened, multiple-channel) and the duration of data used to train models were investigated. When EMG-torque models were formed separately for each of the six distinct joint angles, a minimum "gold standard" error of 4.01±1.2% MVC(F90) resulted (i.e., error relative to maximum voluntary contraction at 90° flexion). This model structure, however, did not directly facilitate interpolation across angles. The best model which did so achieved a statistically equivalent error of 4.06±1.2% MVC(F90). Results demonstrated that advanced EMG σ processors lead to improved joint torque estimation as do longer model training durations.

  19. Age related neuromuscular changes in sEMG of m. Tibialis Anterior using higher order statistics (Gaussianity & linearity test).

    Science.gov (United States)

    Siddiqi, Ariba; Arjunan, Sridhar P; Kumar, Dinesh K

    2016-08-01

    Age-associated changes in the surface electromyogram (sEMG) of Tibialis Anterior (TA) muscle can be attributable to neuromuscular alterations that precede strength loss. We have used our sEMG model of the Tibialis Anterior to interpret the age-related changes and compared with the experimental sEMG. Eighteen young (20-30 years) and 18 older (60-85 years) performed isometric dorsiflexion at 6 different percentage levels of maximum voluntary contractions (MVC), and their sEMG from the TA muscle was recorded. Six different age-related changes in the neuromuscular system were simulated using the sEMG model at the same MVCs as the experiment. The maximal power of the spectrum, Gaussianity and Linearity Test Statistics were computed from the simulated and experimental sEMG. A correlation analysis at α=0.05 was performed between the simulated and experimental age-related change in the sEMG features. The results show the loss in motor units was distinguished by the Gaussianity and Linearity test statistics; while the maximal power of the PSD distinguished between the muscular factors. The simulated condition of 40% loss of motor units with halved the number of fast fibers best correlated with the age-related change observed in the experimental sEMG higher order statistical features. The simulated aging condition found by this study corresponds with the moderate motor unit remodelling and negligible strength loss reported in literature for the cohorts aged 60-70 years.

  20. Classification of surface types using SIR-C/X-SAR, Mount Everest Area, Tibet

    Science.gov (United States)

    Albright, Thomas P.; Painter, Thomas H.; Roberts, Dar A.; Shi, Jiancheng; Dozier, Jeff; Fielding, Eric

    1998-01-01

    Imaging radar is a promising tool for mapping snow and ice cover in alpine regions. It combines a high-resolution, day or night, all-weather imaging capability with sensitivity to hydrologic and climatic snow and ice parameters. We use the spaceborne imaging radar-C/X-band synthetic aperture radar (SIR-C/X-SAR) to map snow and glacial ice on the rugged north slope of Mount Everest. From interferometrically derived digital elevation data, we compute the terrain calibration factor and cosine of the local illumination angle. We then process and terrain-correct radar data sets acquired on April 16, 1994. In addition to the spectral data, we include surface slope to improve discrimination among several surface types. These data sets are then used in a decision tree to generate an image classification. This method is successful in identifying and mapping scree/talus, dry snow, dry snow-covered glacier, wet snow-covered glacier, and rock-covered glacier, as corroborated by comparison with existing surface cover maps and other ancillary information. Application of the classification scheme to data acquired on October 7 of the same year yields accurate results for most surface types but underreports the extent of dry snow cover.

  1. Natural mediotrusive contact: does it affect the masticatory and neck EMG activity during tooth grinding?

    Science.gov (United States)

    Fuentes, Aler D; Martin, Conchita; Bull, Ricardo; Santander, Hugo; Gutiérrez, Mario F; Miralles, Rodolfo

    2016-07-01

    There is scarce knowledge regarding the influence of a natural mediotrusive contact on mandibular and cervical muscular activity. The purpose of this study was to analyze the EMG activity of the anterior temporalis (AT) and sternocleidomastoid (SCM) muscles during awake grinding in healthy subjects with or without a natural mediotrusive occlusal contact. Fifteen subjects with natural mediotrusive occlusal contact (Group 1) and 15 subjects without natural mediotrusive occlusal contact (Group 2) participated. Bilateral surface EMG activity of AT and SCM muscles was recorded during unilateral eccentric or concentric tooth grinding tasks. EMG activity was normalized against the activity recorded during maximal voluntary clenching in intercuspal position (IP) for AT muscles and during maximal intentional isometric head-neck rotation to each side, for SCM muscles. EMG activity of AT and SCM muscles showed no statistical difference between groups. EMG activity of AT muscle was higher in the working side (WS) than in the non-WS (NWS) in Group 1 during concentric grinding (0.492 vs 0.331, p = 0.047), whereas no difference was observed in Group 2. EMG activity of SCM was similar between working and NWSs in both groups and tasks. Asymmetry indexes (AIs) were not significantly different between groups. These findings in healthy subjects support the assumption that during awake tooth grinding, central nerve control predominates over peripheral inputs, and reinforce the idea of a functional link between the motor-neuron pools that control jaw and neck muscles.

  2. Hand and finger dexterity as a function of skin temperature, EMG, and ambient condition.

    Science.gov (United States)

    Chen, Wen-Lin; Shih, Yuh-Chuan; Chi, Chia-Fen

    2010-06-01

    This article examines the changes in skin temperature (finger, hand, forearm), manual performance (hand dexterity and strength), and forearm surface electromyograph (EMG) through 40-min, 11 degrees C water cooling followed by 15-min, 34 degrees C water rewarming; additionally, it explores the relationship between dexterity and the factors of skin temperature, EMG, and ambient condition. Hand exposure in cold conditions is unavoidable and significantly affects manual performance. Two tasks requiring gross and fine dexterity were designed, namely, nut loosening and pin insertion, respectively. The nested-factorial design includes factors of gender, participant (nested within gender), immersion duration, muscle type (for EMG), and location (for skin temperature). The responses are changes in dexterity, skin temperature, normalized amplitude of EMG, and grip strength. Finally, factor analysis and stepwise regression are used to explore factors affecting hand and finger dexterity. Dexterity, EMG, and skin temperature fell with prolonged cooling, but the EMG of the flexor digitorum superficialis remained almost unchanged during the nut loosening task. All responses but the forearm skin temperature recovered to the baseline level at the end of rewarming. The three factors extracted by factor analysis are termed skin temperature, ambient condition, and EMG. They explain approximately two thirds of the variation of the linear models for both dexterities, and the factor of skin temperature is the most influential. Sustained cooling and warming significantly decreases and increases finger, hand, and forearm skin temperature. Dexterity, strength, and EMG are positively correlated to skin temperature. Therefore, keeping the finger, hand, and forearm warm is important to maintaining hand performance. The findings could be helpful to building safety guidelines for working in cold environments.

  3. Comparison of sEMG processing methods during whole-body vibration exercise.

    Science.gov (United States)

    Lienhard, Karin; Cabasson, Aline; Meste, Olivier; Colson, Serge S

    2015-12-01

    The objective was to investigate the influence of surface electromyography (sEMG) processing methods on the quantification of muscle activity during whole-body vibration (WBV) exercises. sEMG activity was recorded while the participants performed squats on the platform with and without WBV. The spikes observed in the sEMG spectrum at the vibration frequency and its harmonics were deleted using state-of-the-art methods, i.e. (1) a band-stop filter, (2) a band-pass filter, and (3) spectral linear interpolation. The same filtering methods were applied on the sEMG during the no-vibration trial. The linear interpolation method showed the highest intraclass correlation coefficients (no vibration: 0.999, WBV: 0.757-0.979) with the comparison measure (unfiltered sEMG during the no-vibration trial), followed by the band-stop filter (no vibration: 0.929-0.975, WBV: 0.661-0.938). While both methods introduced a systematic bias (P interpolation method and the band-stop filter was comparable. The band-pass filter was in poor agreement with the other methods (ICC: 0.207-0.697), unless the sEMG(RMS) was corrected for the bias (ICC ⩾ 0.931, %LOA ⩽ 32.3). In conclusion, spectral linear interpolation or a band-stop filter centered at the vibration frequency and its multiple harmonics should be applied to delete the artifacts in the sEMG signals during WBV. With the use of a band-stop filter it is recommended to correct the sEMG(RMS) for the bias as this procedure improved its performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Recharge and discharge of near-surface groundwater in Forsmark. Comparison of classification methods

    Energy Technology Data Exchange (ETDEWEB)

    Werner, Kent [Golder Associates AB, Uppsala (Sweden); Johansson, Per-Olof [Artesia Grundvattenkonsult AB, Taeby (Sweden); Brydsten, Lars [Umeaa University, Dept. of Ecology and Environmental Science (Sweden); Bosson, Emma; Berglund, Sten [Swedish Nuclear Fuel and Waste Management Co., Stockholm (Sweden)

    2007-03-15

    This report presents and compares data and models for identification of near-surface groundwater recharge and discharge (RD) areas in Forsmark. The general principles of groundwater recharge and discharge are demonstrated and applied to interpret hydrological and hydrogeological observations made in the Forsmark area. 'Continuous' RD classification methods considered in the study include topographical modelling, map overlays, and hydrological-hydrogeological flow modelling. 'Discrete' (point) methods include field-based and hydrochemistry-based RD classifications of groundwater monitoring well locations. The topographical RD modelling uses the digital elevation model as the only input. The map overlays use background maps of Quaternary deposits, soils, and ground- and field layers of the vegetation/land use map. Further, the hydrological-hydrogeological modelling is performed using the MIKE SHE-MIKE 11 software packages, taking into account e.g. topography, meteorology, hydrogeology, and geometry of watercourses and lakes. The best between-model agreement is found for the topography-based model and the MIKE SHE-MIKE 11 model. The agreement between the topographical model and the map overlays is less good. The agreement between the map overlays on the one hand, and the MIKE SHE and field-based RD classifications on the other, is thought to be less good, as inferred from the comparison made with the topography-based model. However, much improvement of the map overlays can likely be obtained, e.g. by using 'weights' and calibration (such exercises were outside the scope of the present study). For field-classified 'recharge wells', there is a good agreement to the hydrochemistry-based (Piper plot) well classification, but less good for the field-classified 'discharge wells'. In addition, the concentration of the age-dating parameter tritium shows low variability among recharge wells, but a large spread among discharge

  5. Recharge and discharge of near-surface groundwater in Forsmark. Comparison of classification methods

    International Nuclear Information System (INIS)

    Werner, Kent; Johansson, Per-Olof; Brydsten, Lars; Bosson, Emma; Berglund, Sten

    2007-03-01

    This report presents and compares data and models for identification of near-surface groundwater recharge and discharge (RD) areas in Forsmark. The general principles of groundwater recharge and discharge are demonstrated and applied to interpret hydrological and hydrogeological observations made in the Forsmark area. 'Continuous' RD classification methods considered in the study include topographical modelling, map overlays, and hydrological-hydrogeological flow modelling. 'Discrete' (point) methods include field-based and hydrochemistry-based RD classifications of groundwater monitoring well locations. The topographical RD modelling uses the digital elevation model as the only input. The map overlays use background maps of Quaternary deposits, soils, and ground- and field layers of the vegetation/land use map. Further, the hydrological-hydrogeological modelling is performed using the MIKE SHE-MIKE 11 software packages, taking into account e.g. topography, meteorology, hydrogeology, and geometry of watercourses and lakes. The best between-model agreement is found for the topography-based model and the MIKE SHE-MIKE 11 model. The agreement between the topographical model and the map overlays is less good. The agreement between the map overlays on the one hand, and the MIKE SHE and field-based RD classifications on the other, is thought to be less good, as inferred from the comparison made with the topography-based model. However, much improvement of the map overlays can likely be obtained, e.g. by using 'weights' and calibration (such exercises were outside the scope of the present study). For field-classified 'recharge wells', there is a good agreement to the hydrochemistry-based (Piper plot) well classification, but less good for the field-classified 'discharge wells'. In addition, the concentration of the age-dating parameter tritium shows low variability among recharge wells, but a large spread among discharge wells. The usefulness of hydrochemistry-based RD

  6. Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands

    Science.gov (United States)

    Atzori, Manfredo; Cognolato, Matteo; Müller, Henning

    2016-01-01

    Natural control methods based on surface electromyography (sEMG) and pattern recognition are promising for hand prosthetics. However, the control robustness offered by scientific research is still not sufficient for many real life applications, and commercial prostheses are capable of offering natural control for only a few movements. In recent years deep learning revolutionized several fields of machine learning, including computer vision and speech recognition. Our objective is to test its methods for natural control of robotic hands via sEMG using a large number of intact subjects and amputees. We tested convolutional networks for the classification of an average of 50 hand movements in 67 intact subjects and 11 transradial amputees. The simple architecture of the neural network allowed to make several tests in order to evaluate the effect of pre-processing, layer architecture, data augmentation and optimization. The classification results are compared with a set of classical classification methods applied on the same datasets. The classification accuracy obtained with convolutional neural networks using the proposed architecture is higher than the average results obtained with the classical classification methods, but lower than the results obtained with the best reference methods in our tests. The results show that convolutional neural networks with a very simple architecture can produce accurate results comparable to the average classical classification methods. They show that several factors (including pre-processing, the architecture of the net and the optimization parameters) can be fundamental for the analysis of sEMG data. Larger networks can achieve higher accuracy on computer vision and object recognition tasks. This fact suggests that it may be interesting to evaluate if larger networks can increase sEMG classification accuracy too. PMID:27656140

  7. Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands.

    Science.gov (United States)

    Atzori, Manfredo; Cognolato, Matteo; Müller, Henning

    2016-01-01

    Natural control methods based on surface electromyography (sEMG) and pattern recognition are promising for hand prosthetics. However, the control robustness offered by scientific research is still not sufficient for many real life applications, and commercial prostheses are capable of offering natural control for only a few movements. In recent years deep learning revolutionized several fields of machine learning, including computer vision and speech recognition. Our objective is to test its methods for natural control of robotic hands via sEMG using a large number of intact subjects and amputees. We tested convolutional networks for the classification of an average of 50 hand movements in 67 intact subjects and 11 transradial amputees. The simple architecture of the neural network allowed to make several tests in order to evaluate the effect of pre-processing, layer architecture, data augmentation and optimization. The classification results are compared with a set of classical classification methods applied on the same datasets. The classification accuracy obtained with convolutional neural networks using the proposed architecture is higher than the average results obtained with the classical classification methods, but lower than the results obtained with the best reference methods in our tests. The results show that convolutional neural networks with a very simple architecture can produce accurate results comparable to the average classical classification methods. They show that several factors (including pre-processing, the architecture of the net and the optimization parameters) can be fundamental for the analysis of sEMG data. Larger networks can achieve higher accuracy on computer vision and object recognition tasks. This fact suggests that it may be interesting to evaluate if larger networks can increase sEMG classification accuracy too.

  8. Neuromechanical Control for Hexapedal Robot Walking on Challenging Surfaces and Surface Classification

    DEFF Research Database (Denmark)

    Xiong, Xiaofeng; Wörgötter, Florentin; Manoonpong, Poramate

    2014-01-01

    The neuromechanical control principles of animal locomotion provide good insights for the development of bio-inspired legged robots for walking on challenging surfaces. Based on such principles, we developed a neuromechanical controller consisting of a modular neural network (MNN) and of virtual...... agonist–antagonist muscle mechanisms (VAAMs). The controller allows for variable compliant leg motions of a hexapod robot, thereby leading to energy-efficient walking on different surfaces. Without any passive mechanisms or torque and position feedback at each joint, the variable compliant leg motions...... are achieved by only changing the stiffness parameters of the VAAMs. In addition, six surfaces can be also classified by observing the motor signals generated by the controller. The performance of the controller is tested on a physical hexapod robot. Experimental results show that it can effectively walk...

  9. A Study on EMG-based Biometrics

    Directory of Open Access Journals (Sweden)

    Jin Su Kim

    2017-05-01

    Full Text Available Biometrics is a technology that recognizes user's information by using unique physical features of his or her body such as face, fingerprint, and iris. It also uses behavioral features such as signature, electrocardiogram (ECG, electromyogram (EMG, and electroencephalogram (EEG. Among them, the EMG signal is a sign generated when the muscles move, which can be used in various fields such as motion recognition, personal identification, and disease diagnosis. In this paper, we analyze EMG-based biometrics and implement a motion recognition and personal identification system. The system extracted features using non-uniform filter bank and Waveform Length (WL, and reduces the dimension using Principal Component Analysis (PCA and Linear Discriminant Analysis (LDA. Afterward, it classified the features using Euclidean Distance (ED, Support Vector Machine (SVM and K Nearest Neighbors (KNN. As a result of the motion recognition experiment, 95% of acquired EMG data and 84.66% of UCI data were obtained and as a result of the personal recognition experiment, 85% of acquired EMG data and 88.66% of UCI data were obtained.

  10. Frequency Optimization for Enhancement of Surface Defect Classification Using the Eddy Current Technique

    Science.gov (United States)

    Fan, Mengbao; Wang, Qi; Cao, Binghua; Ye, Bo; Sunny, Ali Imam; Tian, Guiyun

    2016-01-01

    Eddy current testing is quite a popular non-contact and cost-effective method for nondestructive evaluation of product quality and structural integrity. Excitation frequency is one of the key performance factors for defect characterization. In the literature, there are many interesting papers dealing with wide spectral content and optimal frequency in terms of detection sensitivity. However, research activity on frequency optimization with respect to characterization performances is lacking. In this paper, an investigation into optimum excitation frequency has been conducted to enhance surface defect classification performance. The influences of excitation frequency for a group of defects were revealed in terms of detection sensitivity, contrast between defect features, and classification accuracy using kernel principal component analysis (KPCA) and a support vector machine (SVM). It is observed that probe signals are the most sensitive on the whole for a group of defects when excitation frequency is set near the frequency at which maximum probe signals are retrieved for the largest defect. After the use of KPCA, the margins between the defect features are optimum from the perspective of the SVM, which adopts optimal hyperplanes for structure risk minimization. As a result, the best classification accuracy is obtained. The main contribution is that the influences of excitation frequency on defect characterization are interpreted, and experiment-based procedures are proposed to determine the optimal excitation frequency for a group of defects rather than a single defect with respect to optimal characterization performances. PMID:27164112

  11. An Embedded, Eight Channel, Noise Canceling, Wireless, Wearable sEMG Data Acquisition System With Adaptive Muscle Contraction Detection.

    Science.gov (United States)

    Ergeneci, Mert; Gokcesu, Kaan; Ertan, Erhan; Kosmas, Panagiotis

    2018-02-01

    Wearable technology has gained increasing popularity in the applications of healthcare, sports science, and biomedical engineering in recent years. Because of its convenient nature, the wearable technology is particularly useful in the acquisition of the physiological signals. Specifically, the (surface electromyography) sEMG systems, which measure the muscle activation potentials, greatly benefit from this technology in both clinical and industrial applications. However, the current wearable sEMG systems have several drawbacks including inefficient noise cancellation, insufficient measurement quality, and difficult integration to customized applications. Additionally, none of these sEMG data acquisition systems can detect sEMG signals (i.e., contractions), which provides a valuable environment for further studies such as human machine interaction, gesture recognition, and fatigue tracking. To this end, we introduce an embedded, eight channel, noise canceling, wireless, wearable sEMG data acquisition system with adaptive muscle contraction detection. Our design consists of two stages, which are the sEMG sensors and the multichannel data acquisition unit. For the first stage, we propose a low cost, dry, and active sEMG sensor that captures the muscle activation potentials, a data acquisition unit that evaluates these captured multichannel sEMG signals and transmits them to a user interface. In the data acquisition unit, the sEMG signals are processed through embedded, adaptive methods in order to reject the power line noise and detect the muscle contractions. Through extensive experiments, we demonstrate that our sEMG sensor outperforms a widely used commercially available product and our data acquisition system achieves 4.583 dB SNR gain with accuracy in the detection of the contractions.

  12. Review of Cuttability Indices and A New Rockmass Classification Approach for Selection of Surface Miners

    Science.gov (United States)

    Dey, Kaushik; Ghose, A. K.

    2011-09-01

    Rock excavation is carried out either by drilling and blasting or using rock-cutting machines like rippers, bucket wheel excavators, surface miners, road headers etc. Economics of mechanised rock excavation by rock-cutting machines largely depends on the achieved production rates. Thus, assessment of the performance (productivity) is important prior to deploying a rock-cutting machine. In doing so, several researchers have classified rockmass in different ways and have developed cuttability indices to correlate machine performance directly. However, most of these indices were developed to assess the performance of road headers/tunnel-boring machines apart from a few that were developed in the earlier days when the ripper was a popular excavating equipment. Presently, around 400 surface miners are in operation around the world amongst which, 105 are in India. Until now, no rockmass classification system is available to assess the performance of surface miners. Surface miners are being deployed largely on trial and error basis or based on the performance charts provided by the manufacturer. In this context, it is logical to establish a suitable cuttability index to predict the performance of surface miners. In this present paper, the existing cuttability indices are reviewed and a new cuttability indexes proposed. A new relationship is also developed to predict the output from surface miners using the proposed cuttability index.

  13. Automated real-time detection of tonic-clonic seizures using a wearable EMG device

    DEFF Research Database (Denmark)

    Beniczky, Sándor; Conradsen, Isa; Henning, Oliver

    2018-01-01

    OBJECTIVE: To determine the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) using a wearable surface EMG device. METHODS: We prospectively tested the technical performance and diagnostic accuracy of real-time seizure detection using a wearable surface EMG device....... The seizure detection algorithm and the cutoff values were prespecified. A total of 71 patients, referred to long-term video-EEG monitoring, on suspicion of GTCS, were recruited in 3 centers. Seizure detection was real-time and fully automated. The reference standard was the evaluation of video-EEG recordings...

  14. EMG evaluation of hip adduction exercises for soccer players

    DEFF Research Database (Denmark)

    Serner, Andreas; Jakobsen, Markus Due; Andersen, Lars Louis

    2014-01-01

    INTRODUCTION: Exercise programmes are used in the prevention and treatment of adductor-related groin injuries in soccer; however, there is a lack of knowledge concerning the intensity of frequently used exercises. OBJECTIVE: Primarily to investigate muscle activity of adductor longus during six...... traditional and two new hip adduction exercises. Additionally, to analyse muscle activation of gluteals and abdominals. MATERIALS AND METHODS: 40 healthy male elite soccer players, training >5 h a week, participated in the study. Muscle activity using surface electromyography (sEMG) was measured bilaterally...

  15. Tactile surface classification for limbed robots using a pressure sensitive robot skin

    International Nuclear Information System (INIS)

    Shill, Jacob J; Collins Jr, Emmanuel G; Coyle, Eric; Clark, Jonathan

    2015-01-01

    This paper describes an approach to terrain identification based on pressure images generated through direct surface contact using a robot skin constructed around a high-resolution pressure sensing array. Terrain signatures for classification are formulated from the magnitude frequency responses of the pressure images. The initial experimental results for statically obtained images show that the approach yields classification accuracies >98%. The methodology is extended to accommodate the dynamic pressure images anticipated when a robot is walking or running. Experiments with a one-legged hopping robot yield similar identification accuracies ≈99%. In addition, the accuracies are independent with respect to changing robot dynamics (i.e., when using different leg gaits). The paper further shows that the high-resolution capabilities of the sensor enables similarly textured surfaces to be distinguished. A correcting filter is developed to accommodate for failures or faults that inevitably occur within the sensing array with continued use. Experimental results show using the correcting filter can extend the effective operational lifespan of a high-resolution sensing array over 6x in the presence of sensor damage. The results presented suggest this methodology can be extended to autonomous field robots, providing a robot with crucial information about the environment that can be used to aid stable and efficient mobility over rough and varying terrains. (paper)

  16. Classification of Surface and Deep Soil Samples Using Linear Discriminant Analysis

    International Nuclear Information System (INIS)

    Wasim, M.; Ali, M.; Daud, M.

    2015-01-01

    A statistical analysis was made of the activity concentrations measured in surface and deep soil samples for natural and anthropogenic gamma-emitting radionuclides. Soil samples were obtained from 48 different locations in Gilgit, Pakistan covering about 50 km/sup 2/ areas at an average altitude of 1550 m above sea level. From each location two samples were collected: one from the top soil (2-6 cm) and another from a depth of 6-10 cm. Four radionuclides including /sup 226/Ra, /sup 232/Th, /sup 40/K and /sup 137/Cs were quantified. The data was analyzed using t-test to find out activity concentration difference between the surface and depth samples. At the surface, the median activity concentrations were 23.7, 29.1, 4.6 and 115 Bq kg/sup -1/ for 226Ra, 232Th, 137Cs and 40K respectively. For the same radionuclides, the activity concentrations were respectively 25.5, 26.2, 2.9 and 191 Bq kg/sup -1/ for the depth samples. Principal component analysis (PCA) was applied to explore patterns within the data. A positive significant correlation was observed between the radionuclides /sup 226/Ra and /sup 232/Th. The data from PCA was further utilized in linear discriminant analysis (LDA) for the classification of surface and depth samples. LDA classified surface and depth samples with good predictability. (author)

  17. EMG signals characterization in three states of contraction by fuzzy network and feature extraction

    CERN Document Server

    Mokhlesabadifarahani, Bita

    2015-01-01

    Neuro-muscular and musculoskeletal disorders and injuries highly affect the life style and the motion abilities of an individual. This brief highlights a systematic method for detection of the level of muscle power declining in musculoskeletal and Neuro-muscular disorders. The neuro-fuzzy system is trained with 70 percent of the recorded Electromyography (EMG) cut off window and then used for classification and modeling purposes. The neuro-fuzzy classifier is validated in comparison to some other well-known classifiers in classification of the recorded EMG signals with the three states of contractions corresponding to the extracted features. Different structures of the neuro-fuzzy classifier are also comparatively analyzed to find the optimum structure of the classifier used.

  18. The Response of Hyperkinesis to EMG Biofeedback.

    Science.gov (United States)

    Haight, Maryellen J.; And Others

    A study was conducted involving eight hyperkinetic males (11-15 years old) to determine if Ss receiving electromyography (EMG) biofeedback training would show a reduction in frontalis muscle tension, hyperactivity, and lability, and increases in self-esteem and visual and auditory attention span. Individual 45- and 30-minute relaxation exercises…

  19. Optimization of restricted ROC surfaces in three-class classification tasks.

    Science.gov (United States)

    Edwards, Darrin C; Metz, Charles E

    2007-10-01

    We have shown previously that an N-class ideal observer achieves the optimal receiver operating characteristic (ROC) hypersurface in a Neyman-Pearson sense. Due to the inherent complexity of evaluating observer performance even in a three-class classification task, some researchers have suggested a generally incomplete but more tractable evaluation in terms of a surface, plotting only the three "sensitivities." More generally, one can evaluate observer performance with a single sensitivity or misclassification probability as a function of two linear combinations of sensitivities or misclassification probabilities. We analyzed four such formulations including the "sensitivity" surface. In each case, we applied the Neyman-Pearson criterion to find the observer which achieves optimal performance with respect to each given set of "performance description variables" under consideration. In the unrestricted case, optimization with respect to the Neyman-Pearson criterion yields the ideal observer, as does maximization of the observer's expected utility. Moreover, during our consideration of the restricted cases, we found that the two optimization methods do not merely yield the same observer, but are in fact completely equivalent in a mathematical sense. Thus, for a wide variety of observers which maximize performance with respect to a restricted ROC surface in the Neyman-Pearson sense, that ROC surface can also be shown to provide a complete description of the observer's performance in an expected utility sense.

  20. Object-oriented classification using quasi-synchronous multispectral images (optical and radar) over agricultural surface

    Science.gov (United States)

    Marais Sicre, Claire; Baup, Frederic; Fieuzal, Remy

    2015-04-01

    In the context of climate change (with consequences on temperature and precipitation patterns), persons involved in agricultural management have the imperative to combine: sufficient productivity (as a response of the increment of the necessary foods) and durability of the resources (in order to restrain waste of water, fertilizer or environmental damages). To this end, a detailed knowledge of land use will improve the management of food and water, while preserving the ecosystems. Among the wide range of available monitoring tools, numerous studies demonstrated the interest of satellite images for agricultural mapping. Recently, the launch of several radar and optical sensors offer new perspectives for the multi-wavelength crop monitoring (Terrasar-X, Radarsat-2, Sentinel-1, Landsat-8…) allowing surface survey whatever the cloud conditions. Previous studies have demonstrated the interest of using multi-temporal approaches for crop classification, requiring several images for suitable classification results. Unfortunately, these approaches are limited (due to the satellite orbit cycle) and require waiting several days, week or month before offering an accurate land use map. The objective of this study is to compare the accuracy of object-oriented classification (random forest algorithm combined with vector layer coming from segmentation) to map winter crop (barley, rapeseed, grasslands and wheat) and soil states (bare soils with different surface roughness) using quasi-synchronous images. Satellite data are composed of multi-frequency and multi-polarization (HH, VV, HV and VH) images acquired near the 14th of April, 2010, over a studied area (90km²) located close to Toulouse in France. This is a region of alluvial plains and hills, which are mostly mixed farming and governed by a temperate climate. Remote sensing images are provided by Formosat-2 (04/18), Radarsat-2 (C-band, 04/15), Terrasar-X (X-band, 04/14) and ALOS (L-band, 04/14). Ground data are collected

  1. An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control.

    Science.gov (United States)

    Adewuyi, Adenike A; Hargrove, Levi J; Kuiken, Todd A

    2016-04-01

    Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for application to partial-hand prosthetic control.

  2. A Wireless sEMG Recording System and Its Application to Muscle Fatigue Detection

    Science.gov (United States)

    Chang, Kang-Ming; Liu, Shin-Hong; Wu, Xuan-Han

    2012-01-01

    Surface electromyography (sEMG) is an important measurement for monitoring exercise and fitness. Because if its high sampling frequency requirement, wireless transmission of sEMG data is a challenge. In this article a wireless sEMG measurement system with a sampling frequency of 2 KHz is developed based upon a MSP 430 microcontroller and Bluetooth transmission. Standard isotonic and isometric muscle contraction are clearly represented in the receiving user interface. Muscle fatigue detection is an important application of sEMG. Traditional muscle fatigue is detected from the median frequency of the sEMG power spectrum. The regression slope of the linear regression of median frequency is an important muscle fatigue index. A more negative slope value represents a higher muscle fatigue condition. To test the system performance, muscle fatigue detection was examined by having subjects run on a pedaled-multifunctional elliptical trainer for approximately 30 minutes at three loading levels. Ten subjects underwent a total of 60 exercise sessions to provide the experimental data. Results showed that the regression slope gradually decreases as expected, and there is a significant gender difference. PMID:22368481

  3. A Wireless sEMG Recording System and Its Application to Muscle Fatigue Detection

    Directory of Open Access Journals (Sweden)

    Xuan-Han Wu

    2012-01-01

    Full Text Available Surface electromyography (sEMG is an important measurement for monitoring exercise and fitness. Because if its high sampling frequency requirement, wireless transmission of sEMG data is a challenge. In this article a wireless sEMG measurement system with a sampling frequency of 2 KHz is developed based upon a MSP 430 microcontroller and Bluetooth transmission. Standard isotonic and isometric muscle contraction are clearly represented in the receiving user interface. Muscle fatigue detection is an important application of sEMG. Traditional muscle fatigue is detected from the median frequency of the sEMG power spectrum. The regression slope of the linear regression of median frequency is an important muscle fatigue index. A more negative slope value represents a higher muscle fatigue condition. To test the system performance, muscle fatigue detection was examined by having subjects run on a pedaled-multifunctional elliptical trainer for approximately 30 minutes at three loading levels. Ten subjects underwent a total of 60 exercise sessions to provide the experimental data. Results showed that the regression slope gradually decreases as expected, and there is a significant gender difference.

  4. An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

    Science.gov (United States)

    Tan, Bin; Brown de Colstoun, Eric; Wolfe, Robert E.; Tilton, James C.; Huang, Chengquan; Smith, Sarah E.

    2012-01-01

    An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to

  5. Evaluation of higher order statistics parameters for multi channel sEMG using different force levels.

    Science.gov (United States)

    Naik, Ganesh R; Kumar, Dinesh K

    2011-01-01

    The electromyograpy (EMG) signal provides information about the performance of muscles and nerves. The shape of the muscle signal and motor unit action potential (MUAP) varies due to the movement of the position of the electrode or due to changes in contraction level. This research deals with evaluating the non-Gaussianity in Surface Electromyogram signal (sEMG) using higher order statistics (HOS) parameters. To achieve this, experiments were conducted for four different finger and wrist actions at different levels of Maximum Voluntary Contractions (MVCs). Our experimental analysis shows that at constant force and for non-fatiguing contractions, probability density functions (PDF) of sEMG signals were non-Gaussian. For lesser MVCs (below 30% of MVC) PDF measures tends to be Gaussian process. The above measures were verified by computing the Kurtosis values for different MVCs.

  6. EMG monitoring during functional non-surgical therapy of Achilles tendon rupture.

    Science.gov (United States)

    Hüfner, Tobias; Wohifarth, Kai; Fink, Matthias; Thermann, H; Rollnik, Jens D

    2002-07-01

    After surgical therapy of Achilles tendon rupture, neuromuscular changes may persist, even one year after surgery. We were interested whether these changes are also evident following a non-surgical functional therapy (Variostabil therapy boot/Adidas). Twenty-one patients with complete Achilles tendon rupture were enrolled in the study (mean age 38.5 years, range 24 to 60; 18 men, three women) and followed-up clinically and with surface EMG of the gastrocnemius muscles after four, eight, 12 weeks, and one year after rupture. EMG differences between the affected and non-affected side could only be observed at baseline and after four weeks following Achilles tendon rupture. The results from our study show that EMG changes are not found following non-surgical functional therapy.

  7. Evaluation of novel algorithm embedded in a wearable sEMG device for seizure detection

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sandor; Wolf, Peter

    2012-01-01

    We implemented a modified version of a previously published algorithm for detection of generalized tonic-clonic seizures into a prototype wireless surface electromyography (sEMG) recording device. The method was modified to require minimum computational load, and two parameters were trained...... on prior sEMG data recorded with the device. Along with the normal sEMG recording, the device is able to set an alarm whenever the implemented algorithm detects a seizure. These alarms are annotated in the data file along with the signal. The device was tested at the Epilepsy Monitoring Unit (EMU......) at the Danish Epilepsy Center. Five patients were included in the study and two of them had generalized tonic-clonic seizures. All patients were monitored for 2–5 days. A double-blind study was made on the five patients. The overall result showed that the device detected four of seven seizures and had a false...

  8. Reliability of MUAP properties in multi-channel array EMG recordings of trapezius and SCM

    NARCIS (Netherlands)

    Kallenberg, L.A.C.; Preece, S.; Hermens, Hermanus J.

    2007-01-01

    Muscle activity can be assessed non-invasively by means of surface electrodes places at the skin overlyin a muscle. When multiy-channel array electrodes are used, it is possible to extract motor unit action potentials (MUAP's) from the EMG signals with a segmentation approach based on the Continuous

  9. Modulation of EMG-EMG Coherence in a Choice Stepping Task

    Directory of Open Access Journals (Sweden)

    Ippei Nojima

    2018-02-01

    Full Text Available The voluntary step execution task is a popular measure for identifying fall risks among elderly individuals in the community setting because most falls have been reported to occur during movement. However, the neurophysiological functions during this movement are not entirely understood. Here, we used electromyography (EMG to explore the relationship between EMG-EMG coherence, which reflects common oscillatory drive to motoneurons, and motor performance associated with stepping tasks: simple reaction time (SRT and choice reaction time (CRT tasks. Ten healthy elderly adults participated in the study. Participants took a single step forward in response to a visual imperative stimulus. EMG-EMG coherence was analyzed for 1000 ms before the presentation of the stimulus (stationary standing position from proximal and distal tibialis anterior (TA and soleus (SOL muscles. The main result showed that all paired EMG-EMG coherences in the alpha and beta frequency bands were greater in the SRT than the CRT task. This finding suggests that the common oscillatory drive to the motoneurons during the SRT task occurred prior to taking a step, whereas the lower value of corticospinal activity during the CRT task prior to taking a step may indicate an involvement of inhibitory activity, which is consistent with observations from our previous study (Watanabe et al., 2016. Furthermore, the beta band coherence in intramuscular TA tended to positively correlate with the number of performance errors that are associated with fall risks in the CRT task, suggesting that a reduction in the inhibitory activity may result in a decrease of stepping performance. These findings could advance the understanding of the neurophysiological features of postural adjustments in elderly individuals.

  10. Extracting time-frequency feature of single-channel vastus medialis EMG signals for knee exercise pattern recognition.

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    Full Text Available The EMG signal indicates the electrophysiological response to daily living of activities, particularly to lower-limb knee exercises. Literature reports have shown numerous benefits of the Wavelet analysis in EMG feature extraction for pattern recognition. However, its application to typical knee exercises when using only a single EMG channel is limited. In this study, three types of knee exercises, i.e., flexion of the leg up (standing, hip extension from a sitting position (sitting and gait (walking are investigated from 14 healthy untrained subjects, while EMG signals from the muscle group of vastus medialis and the goniometer on the knee joint of the detected leg are synchronously monitored and recorded. Four types of lower-limb motions including standing, sitting, stance phase of walking, and swing phase of walking, are segmented. The Wavelet Transform (WT based Singular Value Decomposition (SVD approach is proposed for the classification of four lower-limb motions using a single-channel EMG signal from the muscle group of vastus medialis. Based on lower-limb motions from all subjects, the combination of five-level wavelet decomposition and SVD is used to comprise the feature vector. The Support Vector Machine (SVM is then configured to build a multiple-subject classifier for which the subject independent accuracy will be given across all subjects for the classification of four types of lower-limb motions. In order to effectively indicate the classification performance, EMG features from time-domain (e.g., Mean Absolute Value (MAV, Root-Mean-Square (RMS, integrated EMG (iEMG, Zero Crossing (ZC and frequency-domain (e.g., Mean Frequency (MNF and Median Frequency (MDF are also used to classify lower-limb motions. The five-fold cross validation is performed and it repeats fifty times in order to acquire the robust subject independent accuracy. Results show that the proposed WT-based SVD approach has the classification accuracy of 91.85%±0

  11. Seizure detection algorithms based on EMG signals

    DEFF Research Database (Denmark)

    Conradsen, Isa

    Background: the currently used non-invasive seizure detection methods are not reliable. Muscle fibers are directly connected to the nerves, whereby electric signals are generated during activity. Therefore, an alarm system on electromyography (EMG) signals is a theoretical possibility. Objective...... on the amplitude of the signal. The other algorithm was based on information of the signal in the frequency domain, and it focused on synchronisation of the electrical activity in a single muscle during the seizure. Results: The amplitude-based algorithm reliably detected seizures in 2 of the patients, while...... the frequency-based algorithm was efficient for detecting the seizures in the third patient. Conclusion: Our results suggest that EMG signals could be used to develop an automatic seizuredetection system. However, different patients might require different types of algorithms /approaches....

  12. EMG-Based Continuous and Simultaneous Estimation of Arm Kinematics in Able-Bodied Individuals and Stroke Survivors

    Directory of Open Access Journals (Sweden)

    Jie Liu

    2017-08-01

    Full Text Available Among the potential biological signals for human-machine interactions (brain, nerve, and muscle signals, electromyography (EMG widely used in clinical setting can be obtained non-invasively as motor commands to control movements. The aim of this study was to develop a model for continuous and simultaneous decoding of multi-joint dynamic arm movements based on multi-channel surface EMG signals crossing the joints, leading to application of myoelectrically controlled exoskeleton robots for upper-limb rehabilitation. Twenty subjects were recruited for this study including 10 stroke subjects and 10 able-bodied subjects. The subjects performed free arm reaching movements in the horizontal plane with an exoskeleton robot. The shoulder, elbow and wrist movements and surface EMG signals from six muscles crossing the three joints were recorded. A non-linear autoregressive exogenous (NARX model was developed to continuously decode the shoulder, elbow and wrist movements based solely on the EMG signals. The shoulder, elbow and wrist movements were decoded accurately based only on the EMG inputs in all the subjects, with the variance accounted for (VAF > 98% for all three joints. The proposed approach is capable of simultaneously and continuously decoding multi-joint movements of the human arm by taking into account the non-linear mappings between the muscle EMGs and joint movements, which may provide less effortful control of robotic exoskeletons for rehabilitation training of individuals with neurological disorders and arm impairment.

  13. Young, healthy subjects can reduce the activity of calf muscles when provided with EMG biofeedback in upright stance

    Directory of Open Access Journals (Sweden)

    Taian M. Vieira

    2016-04-01

    Full Text Available Recent evidence suggests the minimisation of muscular effort rather than of the size of bodily sway may be the primary, nervous system goal when regulating the human, standing posture. Different programs have been proposed for balance training; none however has been focused on the activation of postural muscles during standing. In this study we investigated the possibility of minimising the activation of the calf muscles during standing through biofeedback. By providing subjects with an audio signal that varied in amplitude and frequency with the amplitude of surface electromyograms (EMG recorded from different regions of the gastrocnemius and soleus muscles, we expected them to be able to minimise the level of muscle activation during standing without increasing the excursion of the centre of pressure (CoP. CoP data and surface EMG from gastrocnemii, soleus and tibialis anterior muscles were obtained from ten healthy participants while standing at ease and while standing with EMG biofeedback. Four sensitivities were used to test subjects’ responsiveness to the EMG biofeedback. Compared with standing at ease, the two most sensitive feedback conditions induced a decrease in plantar flexor activity (~15%; P<0.05 and an increase in tibialis anterior EMG (~10%; P<0.05. Furthermore, CoP mean position significantly shifted backward (~30 mm. In contrast, the use of less sensitive EMG biofeedback resulted in a significant decrease in EMG activity of ankle plantar flexors with a marginal increase in TA activity compared with standing at ease. These changes were not accompanied by greater CoP displacements or significant changes in mean CoP position. Key results revealed subjects were able to keep standing stability while reducing the activity of gastrocnemius and soleus without loading their tibialis anterior muscle when standing with EMG biofeedback. These results may therefore posit the basis for the development of training protocols aimed at

  14. Design of sEMG assembly to detect external anal sphincter activity: a proof of concept.

    Science.gov (United States)

    Shiraz, Arsam; Leaker, Brian; Mosse, Charles Alexander; Solomon, Eskinder; Craggs, Michael; Demosthenous, Andreas

    2017-10-31

    Conditional trans-rectal stimulation of the pudendal nerve could provide a viable solution to treat hyperreflexive bladder in spinal cord injury. A set threshold of the amplitude estimate of the external anal sphincter surface electromyography (sEMG) may be used as the trigger signal. The efficacy of such a device should be tested in a large scale clinical trial. As such, a probe should remain in situ for several hours while patients attend to their daily routine; the recording electrodes should be designed to be large enough to maintain good contact while observing design constraints. The objective of this study was to arrive at a design for intra-anal sEMG recording electrodes for the subsequent clinical trials while deriving the possible recording and processing parameters. Having in mind existing solutions and based on theoretical and anatomical considerations, a set of four multi-electrode probes were designed and developed. These were tested in a healthy subject and the measured sEMG traces were recorded and appropriately processed. It was shown that while comparatively large electrodes record sEMG traces that are not sufficiently correlated with the external anal sphincter contractions, smaller electrodes may not maintain a stable electrode tissue contact. It was shown that 3 mm wide and 1 cm long electrodes with 5 mm inter-electrode spacing, in agreement with Nyquist sampling, placed 1 cm from the orifice may intra-anally record a sEMG trace sufficiently correlated with external anal sphincter activity. The outcome of this study can be used in any biofeedback, treatment or diagnostic application where the activity of the external anal sphincter sEMG should be detected for an extended period of time.

  15. Classification of reflected signals from cavitated tooth surfaces using an artificial intelligence technique incorporating a fiber optic displacement sensor

    Science.gov (United States)

    Rahman, Husna Abdul; Harun, Sulaiman Wadi; Arof, Hamzah; Irawati, Ninik; Musirin, Ismail; Ibrahim, Fatimah; Ahmad, Harith

    2014-05-01

    An enhanced dental cavity diameter measurement mechanism using an intensity-modulated fiber optic displacement sensor (FODS) scanning and imaging system, fuzzy logic as well as a single-layer perceptron (SLP) neural network, is presented. The SLP network was employed for the classification of the reflected signals, which were obtained from the surfaces of teeth samples and captured using FODS. Two features were used for the classification of the reflected signals with one of them being the output of a fuzzy logic. The test results showed that the combined fuzzy logic and SLP network methodology contributed to a 100% classification accuracy of the network. The high-classification accuracy significantly demonstrates the suitability of the proposed features and classification using SLP networks for classifying the reflected signals from teeth surfaces, enabling the sensor to accurately measure small diameters of tooth cavity of up to 0.6 mm. The method remains simple enough to allow its easy integration in existing dental restoration support systems.

  16. Design of microcontroller-based EMG and the analysis of EMG signals.

    Science.gov (United States)

    Güler, Nihal Fatma; Hardalaç, Firat

    2002-04-01

    In this work, a microcontroller-based EMG designed and tested on 40 patients. When the patients are in rest, the fast Fourier transform (FFT) analysis was applied to EMG signals recorded from right leg peroneal region. The histograms are constructed from the results of the FFT analysis. The analysis results shows that the amplitude of fibrillation potential of the muscle fiber of 30 patients measured from peroneal region is low and the duration is short. This is the reason why the motor nerves degenerated and 10 patients were found to be healthy.

  17. Classification of rare missense substitutions, using risk surfaces, with genetic- and molecular-epidemiology applications.

    Science.gov (United States)

    Tavtigian, Sean V; Byrnes, Graham B; Goldgar, David E; Thomas, Alun

    2008-11-01

    Many individually rare missense substitutions are encountered during deep resequencing of candidate susceptibility genes and clinical mutation screening of known susceptibility genes. BRCA1 and BRCA2 are among the most resequenced of all genes, and clinical mutation screening of these genes provides an extensive data set for analysis of rare missense substitutions. Align-GVGD is a mathematically simple missense substitution analysis algorithm, based on the Grantham difference, which has already contributed to classification of missense substitutions in BRCA1, BRCA2, and CHEK2. However, the distribution of genetic risk as a function of Align-GVGD's output variables Grantham variation (GV) and Grantham deviation (GD) has not been well characterized. Here, we used data from the Myriad Genetic Laboratories database of nearly 70,000 full-sequence tests plus two risk estimates, one approximating the odds ratio and the other reflecting strength of selection, to display the distribution of risk in the GV-GD plane as a series of surfaces. We abstracted contours from the surfaces and used the contours to define a sequence of missense substitution grades ordered from greatest risk to least risk. The grades were validated internally using a third, personal and family history-based, measure of risk. The Align-GVGD grades defined here are applicable to both the genetic epidemiology problem of classifying rare missense substitutions observed in known susceptibility genes and the molecular epidemiology problem of analyzing rare missense substitutions observed during case-control mutation screening studies of candidate susceptibility genes. (c) 2008 Wiley-Liss, Inc.

  18. Detecting Nasal Vowels in Speech Interfaces Based on Surface Electromyography.

    Directory of Open Access Journals (Sweden)

    João Freitas

    Full Text Available Nasality is a very important characteristic of several languages, European Portuguese being one of them. This paper addresses the challenge of nasality detection in surface electromyography (EMG based speech interfaces. We explore the existence of useful information about the velum movement and also assess if muscles deeper down in the face and neck region can be measured using surface electrodes, and the best electrode location to do so. The procedure we adopted uses Real-Time Magnetic Resonance Imaging (RT-MRI, collected from a set of speakers, providing a method to interpret EMG data. By ensuring compatible data recording conditions, and proper time alignment between the EMG and the RT-MRI data, we are able to accurately estimate the time when the velum moves and the type of movement when a nasal vowel occurs. The combination of these two sources revealed interesting and distinct characteristics in the EMG signal when a nasal vowel is uttered, which motivated a classification experiment. Overall results of this experiment provide evidence that it is possible to detect velum movement using sensors positioned below the ear, between mastoid process and the mandible, in the upper neck region. In a frame-based classification scenario, error rates as low as 32.5% for all speakers and 23.4% for the best speaker have been achieved, for nasal vowel detection. This outcome stands as an encouraging result, fostering the grounds for deeper exploration of the proposed approach as a promising route to the development of an EMG-based speech interface for languages with strong nasal characteristics.

  19. Muscle networks: Connectivity analysis of EMG activity during postural control

    Science.gov (United States)

    Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

    2015-12-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

  20. Muscle Performance Investigated With a Novel Smart Compression Garment Based on Pressure Sensor Force Myography and Its Validation Against EMG.

    Science.gov (United States)

    Belbasis, Aaron; Fuss, Franz Konstantin

    2018-01-01

    Muscle activity and fatigue performance parameters were obtained and compared between both a smart compression garment and the gold-standard, a surface electromyography (EMG) system during high-speed cycling in seven participants. The smart compression garment, based on force myography (FMG), comprised of integrated pressure sensors that were sandwiched between skin and garment, located on five thigh muscles. The muscle activity was assessed by means of crank cycle diagrams (polar plots) that displayed the muscle activity relative to the crank cycle. The fatigue was assessed by means of the median frequency of the power spectrum of the EMG signal; the fractal dimension (FD) of the EMG signal; and the FD of the pressure signal. The smart compression garment returned performance parameters (muscle activity and fatigue) comparable to the surface EMG. The major differences were that the EMG measured the electrical activity, whereas the pressure sensor measured the mechanical activity. As such, there was a phase shift between electrical and mechanical signals, with the electrical signals preceding the mechanical counterparts in most cases. This is specifically pronounced in high-speed cycling. The fatigue trend over the duration of the cycling exercise was clearly reflected in the fatigue parameters (FDs and median frequency) obtained from pressure and EMG signals. The fatigue parameter of the pressure signal (FD) showed a higher time dependency ( R 2 = 0.84) compared to the EMG signal. This reflects that the pressure signal puts more emphasis on the fatigue as a function of time rather than on the origin of fatigue (e.g., peripheral or central fatigue). In light of the high-speed activity results, caution should be exerted when using data obtained from EMG for biomechanical models. In contrast to EMG data, activity data obtained from FMG are considered more appropriate and accurate as an input for biomechanical modeling as they truly reflect the mechanical muscle

  1. Muscle Performance Investigated With a Novel Smart Compression Garment Based on Pressure Sensor Force Myography and Its Validation Against EMG

    Directory of Open Access Journals (Sweden)

    Aaron Belbasis

    2018-04-01

    Full Text Available Muscle activity and fatigue performance parameters were obtained and compared between both a smart compression garment and the gold-standard, a surface electromyography (EMG system during high-speed cycling in seven participants. The smart compression garment, based on force myography (FMG, comprised of integrated pressure sensors that were sandwiched between skin and garment, located on five thigh muscles. The muscle activity was assessed by means of crank cycle diagrams (polar plots that displayed the muscle activity relative to the crank cycle. The fatigue was assessed by means of the median frequency of the power spectrum of the EMG signal; the fractal dimension (FD of the EMG signal; and the FD of the pressure signal. The smart compression garment returned performance parameters (muscle activity and fatigue comparable to the surface EMG. The major differences were that the EMG measured the electrical activity, whereas the pressure sensor measured the mechanical activity. As such, there was a phase shift between electrical and mechanical signals, with the electrical signals preceding the mechanical counterparts in most cases. This is specifically pronounced in high-speed cycling. The fatigue trend over the duration of the cycling exercise was clearly reflected in the fatigue parameters (FDs and median frequency obtained from pressure and EMG signals. The fatigue parameter of the pressure signal (FD showed a higher time dependency (R2 = 0.84 compared to the EMG signal. This reflects that the pressure signal puts more emphasis on the fatigue as a function of time rather than on the origin of fatigue (e.g., peripheral or central fatigue. In light of the high-speed activity results, caution should be exerted when using data obtained from EMG for biomechanical models. In contrast to EMG data, activity data obtained from FMG are considered more appropriate and accurate as an input for biomechanical modeling as they truly reflect the mechanical

  2. Effect of hypnosis on masseter EMG recorded during the 'resting' and a slightly open jaw posture.

    Science.gov (United States)

    Al-Enaizan, N; Davey, K J; Lyons, M F; Cadden, S W

    2015-11-01

    The aim of this experimental study was to determine whether minimal levels of electromyographic activity in the masseter muscle are altered when individuals are in a verified hypnotic state. Experiments were performed on 17 volunteer subjects (8 male, 9 female) all of whom gave informed consent. The subjects were dentate and had no symptoms of pain or masticatory dysfunction. Surface electromyograms (EMGs) were made from the masseter muscles and quantified by integration following full-wave rectification and averaging. The EMGs were obtained (i) with the mandible in 'resting' posture; (ii) with the mandible voluntarily lowered (but with the lips closed); (iii) during maximum voluntary clenching (MVC). The first two recordings were made before, during and after the subjects were in a hypnotic state. Susceptibility to hypnosis was assessed with Spiegel's eye-roll test, and the existence of the hypnotic state was verified by changes in ventilatory pattern. On average, EMG levels expressed as percentages of MVC were less: (i) when the jaw was deliberately lowered as opposed to being in the postural position: (ii) during hypnosis compared with during the pre- and post-hypnotic periods. However, analysis of variance followed by post hoc tests with multiple comparison corrections (Bonferroni) revealed that only the differences between the level during hypnosis and those before and after hypnosis were statistically significant (P hypnosis, it appears that part of that EMG is of biological origin. © 2015 John Wiley & Sons Ltd.

  3. Robust functional statistics applied to Probability Density Function shape screening of sEMG data.

    Science.gov (United States)

    Boudaoud, S; Rix, H; Al Harrach, M; Marin, F

    2014-01-01

    Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications.

  4. Muscle fatigue evaluation of astronaut upper limb based on sEMG and subjective assessment

    Science.gov (United States)

    Zu, Xiaoqi; Zhou, Qianxiang; Li, Yun

    2012-07-01

    All movements are driven by muscle contraction, and it is easy to cause muscle fatigue. Evaluation of muscle fatigue is a hot topic in the area of astronaut life support training and rehabilitation. If muscle gets into fatigue condition, it may reduce work efficiency and has an impact on psychological performance. Therefore it is necessary to develop an accurate and usable method on muscle fatigue evaluation of astronaut upper limb. In this study, we developed a method based on surface electromyography (sEMG) and subjective assessment (Borg scale) to evaluate local muscle fatigue. Fifteen healthy young male subjects participated in the experiment. They performed isometric muscle contractions of the upper limb. sEMG of the biceps brachii were recorded during the entire process of isotonic muscle contraction and Borg scales of muscle fatigue were collected in certain times. sEMG were divided into several parts, and then mean energy of each parts were calculated by the one-twelfth band octave method. Equations were derived based on the relationship between the mean energy of sEMG and Borg scale. The results showed that cubic curve could describe the degree of local muscle fatigue, and could be used to evaluate and monitor local muscle fatigue during the entire process.

  5. Knee joint angle affects EMG-force relationship in the vastus intermedius muscle.

    Science.gov (United States)

    Saito, Akira; Akima, Hiroshi

    2013-12-01

    It is not understood how the knee joint angle affects the relationship between electromyography (EMG) and force of four individual quadriceps femoris (QF) muscles. The purpose of this study was to examine the effect of the knee joint angle on the EMG-force relationship of the four individual QF muscles, particularly the vastus intermedius (VI), during isometric knee extensions. Eleven healthy men performed 20-100% of maximal voluntary contraction (MVC) at knee joint angles of 90°, 120° and 150°. Surface EMG of the four QF synergists was recorded and normalized by the root mean square during MVC. The normalized EMG of the four QF synergists at a knee joint angle of 150° was significantly lower than that at 90° and 120° (P knee joint angle of 150°. Furthermore, the neuromuscular activation of the VI was the most sensitive to change in muscle length among the four QF synergistic muscles. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Decoding subtle forearm flexions using fractal features of surface electromyogram from single and multiple sensors.

    Science.gov (United States)

    Arjunan, Sridhar Poosapadi; Kumar, Dinesh Kant

    2010-10-21

    Identifying finger and wrist flexion based actions using a single channel surface electromyogram (sEMG) can lead to a number of applications such as sEMG based controllers for near elbow amputees, human computer interface (HCI) devices for elderly and for defence personnel. These are currently infeasible because classification of sEMG is unreliable when the level of muscle contraction is low and there are multiple active muscles. The presence of noise and cross-talk from closely located and simultaneously active muscles is exaggerated when muscles are weakly active such as during sustained wrist and finger flexion. This paper reports the use of fractal properties of sEMG to reliably identify individual wrist and finger flexion, overcoming the earlier shortcomings. SEMG signal was recorded when the participant maintained pre-specified wrist and finger flexion movements for a period of time. Various established sEMG signal parameters such as root mean square (RMS), Mean absolute value (MAV), Variance (VAR) and Waveform length (WL) and the proposed fractal features: fractal dimension (FD) and maximum fractal length (MFL) were computed. Multi-variant analysis of variance (MANOVA) was conducted to determine the p value, indicative of the significance of the relationships between each of these parameters with the wrist and finger flexions. Classification accuracy was also computed using the trained artificial neural network (ANN) classifier to decode the desired subtle movements. The results indicate that the p value for the proposed feature set consisting of FD and MFL of single channel sEMG was 0.0001 while that of various combinations of the five established features ranged between 0.009 - 0.0172. From the accuracy of classification by the ANN, the average accuracy in identifying the wrist and finger flexions using the proposed feature set of single channel sEMG was 90%, while the average accuracy when using a combination of other features ranged between 58% and 73

  7. Decoding subtle forearm flexions using fractal features of surface electromyogram from single and multiple sensors

    Directory of Open Access Journals (Sweden)

    Kumar Dinesh

    2010-10-01

    Full Text Available Abstract Background Identifying finger and wrist flexion based actions using a single channel surface electromyogram (sEMG can lead to a number of applications such as sEMG based controllers for near elbow amputees, human computer interface (HCI devices for elderly and for defence personnel. These are currently infeasible because classification of sEMG is unreliable when the level of muscle contraction is low and there are multiple active muscles. The presence of noise and cross-talk from closely located and simultaneously active muscles is exaggerated when muscles are weakly active such as during sustained wrist and finger flexion. This paper reports the use of fractal properties of sEMG to reliably identify individual wrist and finger flexion, overcoming the earlier shortcomings. Methods SEMG signal was recorded when the participant maintained pre-specified wrist and finger flexion movements for a period of time. Various established sEMG signal parameters such as root mean square (RMS, Mean absolute value (MAV, Variance (VAR and Waveform length (WL and the proposed fractal features: fractal dimension (FD and maximum fractal length (MFL were computed. Multi-variant analysis of variance (MANOVA was conducted to determine the p value, indicative of the significance of the relationships between each of these parameters with the wrist and finger flexions. Classification accuracy was also computed using the trained artificial neural network (ANN classifier to decode the desired subtle movements. Results The results indicate that the p value for the proposed feature set consisting of FD and MFL of single channel sEMG was 0.0001 while that of various combinations of the five established features ranged between 0.009 - 0.0172. From the accuracy of classification by the ANN, the average accuracy in identifying the wrist and finger flexions using the proposed feature set of single channel sEMG was 90%, while the average accuracy when using a combination

  8. High-density EMG e-textile systems for the control of active prostheses

    DEFF Research Database (Denmark)

    Farina, Dario; Lorrain, Thomas; Negro, Francesco

    2010-01-01

    Myoelectric control of active prostheses requires electrode systems that are easy to apply for daily repositioning of the electrodes by the user. In this study we propose the use of Smart Fabric and Interactive Textile (SFIT) systems as an alternative solution for recording high-density EMG signa...... classified with linear discriminant analysis. The average classification accuracy for the nine tasks was 89.1 1.9 %. These results show that SFIT systems can be used as an effective way for muscle-machine interfacing....

  9. sEMG during Whole-Body Vibration Contains Motion Artifacts and Reflex Activity

    Directory of Open Access Journals (Sweden)

    Karin Lienhard

    2015-01-01

    Full Text Available The purpose of this study was to determine whether the excessive spikes observed in the surface electromyography (sEMG spectrum recorded during whole-body vibration (WBV exercises contain motion artifacts and/or reflex activity. The occurrence of motion artifacts was tested by electrical recordings of the patella. The involvement of reflex activity was investigated by analyzing the magnitude of the isolated spikes during changes in voluntary background muscle activity. Eighteen physically active volunteers performed static squats while the sEMG was measured of five lower limb muscles during vertical WBV using no load and an additional load of 33 kg. In order to record motion artifacts during WBV, a pair of electrodes was positioned on the patella with several layers of tape between skin and electrodes. Spectral analysis of the patella signal revealed recordings of motion artifacts as high peaks at the vibration frequency (fundamental and marginal peaks at the multiple harmonics were observed. For the sEMG recordings, the root mean square of the spikes increased with increasing additional loads (p < 0.05, and was significantly correlated to the sEMG signal without the spikes of the respective muscle (r range: 0.54 - 0.92, p < 0.05. This finding indicates that reflex activity might be contained in the isolated spikes, as identical behavior has been found for stretch reflex responses evoked during direct vibration. In conclusion, the spikes visible in the sEMG spectrum during WBV exercises contain motion artifacts and possibly reflex activity.

  10. Influence of post-stroke spasticity on EMG-force coupling and force steadiness in biceps brachii.

    Science.gov (United States)

    Carlyle, Jennilee K; Mochizuki, George

    2018-02-01

    Individuals with spasticity after stroke experience a decrease in force steadiness which can impact function. Alterations in the strength of EMG-force coupling may contribute to the reduction in force steadiness observed in spasticity. The aim was to determine the extent to which force steadiness and EMG-force coupling is affected by post-stroke spasticity. This cross-sectional study involved individuals with upper limb spasticity after stroke. Participants were required to generate and maintain isometric contractions of the elbow flexors at varying force levels. Coefficient of variation of force, absolute force, EMG-force cross-correlation function peak and peak latency was measured from both limbs with surface electromyography and isometric dynamometry. Statistically significant differences were observed between the affected and less affected limbs for all outcome measures. Significant main effects of force level were also observed. Force steadiness was not statistically significantly correlated with EMG-force coupling; however, both force steadiness and absolute force were associated with the level of impairment as measured by the Chedoke McMaster Stroke Assessment Scale. Spasticity after stroke uncouples the relationship between EMG and force and is associated with reduced force steadiness during isometric contractions; however, these features of control are not associated in individuals with spasticity. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Generating Human-Like Velocity-Adapted Jumping Gait from sEMG Signals for Bionic Leg’s Control

    Directory of Open Access Journals (Sweden)

    Weiwei Yu

    2017-01-01

    Full Text Available In the case of dynamic motion such as jumping, an important fact in sEMG (surface Electromyogram signal based control on exoskeletons, myoelectric prostheses, and rehabilitation gait is that multichannel sEMG signals contain mass data and vary greatly with time, which makes it difficult to generate compliant gait. Inspired by the fact that muscle synergies leading to dimensionality reduction may simplify motor control and learning, this paper proposes a new approach to generate flexible gait based on muscle synergies extracted from sEMG signal. Two questions were discussed and solved, the first one concerning whether the same set of muscle synergies can explain the different phases of hopping movement with various velocities. The second one is about how to generate self-adapted gait with muscle synergies while alleviating model sensitivity to sEMG transient changes. From the experimental results, the proposed method shows good performance both in accuracy and in robustness for producing velocity-adapted vertical jumping gait. The method discussed in this paper provides a valuable reference for the sEMG-based control of bionic robot leg to generate human-like dynamic gait.

  12. Use of sEMG in identification of low level muscle activities: features based on ICA and fractal dimension.

    Science.gov (United States)

    Naik, Ganesh R; Kumar, Dinesh K; Arjunan, Sridhar

    2009-01-01

    This paper has experimentally verified and compared features of sEMG (Surface Electromyogram) such as ICA (Independent Component Analysis) and Fractal Dimension (FD) for identification of low level forearm muscle activities. The fractal dimension was used as a feature as reported in the literature. The normalized feature values were used as training and testing vectors for an Artificial neural network (ANN), in order to reduce inter-experimental variations. The identification accuracy using FD of four channels sEMG was 58%, and increased to 96% when the signals are separated to their independent components using ICA.

  13. EMG biofeedback of the abductor pollicis brevis in piano performance.

    Science.gov (United States)

    Montes, R; Bedmar, M; Sol Martin, M

    1993-06-01

    The aim of the present study was to apply EMG biofeedback as an auxiliary to piano teaching techniques. We studied the changes in integrated electromyographic activity, using the abductor pollicis brevis functioning as an agonist during the teaching of identical selective movements of piano playing in two groups, one with EMG biofeedback and the other following traditional method of instruction. The analysis of variance revealed an increase in the peak amplitude and the relaxation rate values for the biofeedback group. These results have implications for the application of piano playing techniques and reveal EMG biofeedback as an aid in the teaching of thumb attack with the abductor pollicis brevis as agonist.

  14. Object based classification of high resolution data in urban areas considering digital surface models

    OpenAIRE

    Oczipka, Martin Eckhard

    2010-01-01

    Over the last couple of years more and more analogue airborne cameras were replaced by digital cameras. Digitally recorded image data have significant advantages to film based data. Digital aerial photographs have a much better radiometric resolution. Image information can be acquired in shaded areas too. This information is essential for a stable and continuous classification, because no data or unclassified areas should be as small as possible. Considering this technological progress, on...

  15. A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

    Science.gov (United States)

    Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

    2017-01-01

    Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

  16. A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Qi Huang

    2017-06-01

    Full Text Available Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC, by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC. We compared PAC performance with incremental support vector classifier (ISVC and non-adapting SVC (NSVC in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05 and ISVC (13.38% ± 2.62%, p = 0.001, and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle.

  17. Automated Surface Classification of SRF Cavities for the Investigation of the Influence of Surface Properties onto the Operational Performance

    International Nuclear Information System (INIS)

    Wenskat, Marc

    2015-07-01

    Superconducting niobium radio-frequency cavities are fundamental for the European XFEL and the International Linear Collider. To use the operational advantages of superconducting cavities, the inner surface has to fulfill quite demanding requirements. The surface roughness and cleanliness improved over the last decades and with them, the achieved maximal accelerating field. Still, limitations of the maximal achieved accelerating field are observed, which are not explained by localized geometrical defects or impurities. The scope of this thesis is a better understanding of these limitations in defect free cavities based on global, rather than local, surface properties. For this goal, more than 30 cavities underwent subsequent surface treatments, cold RF tests and optical inspections within the ILC-HiGrade research program and the XFEL cavity production. An algorithm was developed which allows an automated surface characterization based on an optical inspection robot. This algorithm delivers a set of optical surface properties, which describes the inner cavity surface. These optical surface properties deliver a framework for a quality assurance of the fabrication procedures. Furthermore, they shows promising results for a better understanding of the observed limitations in defect free cavities.

  18. Automated Surface Classification of SRF Cavities for the Investigation of the Influence of Surface Properties onto the Operational Performance

    Energy Technology Data Exchange (ETDEWEB)

    Wenskat, Marc

    2015-07-15

    Superconducting niobium radio-frequency cavities are fundamental for the European XFEL and the International Linear Collider. To use the operational advantages of superconducting cavities, the inner surface has to fulfill quite demanding requirements. The surface roughness and cleanliness improved over the last decades and with them, the achieved maximal accelerating field. Still, limitations of the maximal achieved accelerating field are observed, which are not explained by localized geometrical defects or impurities. The scope of this thesis is a better understanding of these limitations in defect free cavities based on global, rather than local, surface properties. For this goal, more than 30 cavities underwent subsequent surface treatments, cold RF tests and optical inspections within the ILC-HiGrade research program and the XFEL cavity production. An algorithm was developed which allows an automated surface characterization based on an optical inspection robot. This algorithm delivers a set of optical surface properties, which describes the inner cavity surface. These optical surface properties deliver a framework for a quality assurance of the fabrication procedures. Furthermore, they shows promising results for a better understanding of the observed limitations in defect free cavities.

  19. siGnum: graphical user interface for EMG signal analysis.

    Science.gov (United States)

    Kaur, Manvinder; Mathur, Shilpi; Bhatia, Dinesh; Verma, Suresh

    2015-01-01

    Electromyography (EMG) signals that represent the electrical activity of muscles can be used for various clinical and biomedical applications. These are complicated and highly varying signals that are dependent on anatomical location and physiological properties of the muscles. EMG signals acquired from the muscles require advanced methods for detection, decomposition and processing. This paper proposes a novel Graphical User Interface (GUI) siGnum developed in MATLAB that will apply efficient and effective techniques on processing of the raw EMG signals and decompose it in a simpler manner. It could be used independent of MATLAB software by employing a deploy tool. This would enable researcher's to gain good understanding of EMG signal and its analysis procedures that can be utilized for more powerful, flexible and efficient applications in near future.

  20. Parsimonious classification of binary lacunarity data computed from food surface images using kernel principal component analysis and artificial neural networks.

    Science.gov (United States)

    Iqbal, Abdullah; Valous, Nektarios A; Sun, Da-Wen; Allen, Paul

    2011-02-01

    Lacunarity is about quantifying the degree of spatial heterogeneity in the visual texture of imagery through the identification of the relationships between patterns and their spatial configurations in a two-dimensional setting. The computed lacunarity data can designate a mathematical index of spatial heterogeneity, therefore the corresponding feature vectors should possess the necessary inter-class statistical properties that would enable them to be used for pattern recognition purposes. The objectives of this study is to construct a supervised parsimonious classification model of binary lacunarity data-computed by Valous et al. (2009)-from pork ham slice surface images, with the aid of kernel principal component analysis (KPCA) and artificial neural networks (ANNs), using a portion of informative salient features. At first, the dimension of the initial space (510 features) was reduced by 90% in order to avoid any noise effects in the subsequent classification. Then, using KPCA, the first nineteen kernel principal components (99.04% of total variance) were extracted from the reduced feature space, and were used as input in the ANN. An adaptive feedforward multilayer perceptron (MLP) classifier was employed to obtain a suitable mapping from the input dataset. The correct classification percentages for the training, test and validation sets were 86.7%, 86.7%, and 85.0%, respectively. The results confirm that the classification performance was satisfactory. The binary lacunarity spatial metric captured relevant information that provided a good level of differentiation among pork ham slice images. Copyright © 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

  1. Contemporary linkages between EMG, kinetics and stroke rehabilitation

    OpenAIRE

    Wolf, Steven L.; Butler, Andrew J.; Alberts, Jay L.; Kim, Min Wook

    2005-01-01

    EMG and kinetic measures have been primary tools in the study of movement and have provided the foundation for much of the work presented in this journal. Recently, novel ways of combining these tools have provided opportunities to examine elements of motor learning and brain plasticity. This presentation reviews the quantification of EMG within the context of transcranial magnetic stimulation. This vehicle permits acquisition of measures that are fundamental to examining prospects for cortic...

  2. Color Shaded-Relief and Surface-Classification Maps of the Fish Creek Area, Harrison Bay Quadrangle, Northern Alaska

    Science.gov (United States)

    Mars, John L.; Garrity, Christopher P.; Houseknecht, David W.; Amoroso, Lee; Meares, Donald C.

    2007-01-01

    Introduction The northeastern part of the National Petroleum Reserve in Alaska (NPRA) has become an area of active petroleum exploration during the past five years. Recent leasing and exploration drilling in the NPRA requires the U.S. Bureau of Land Management (BLM) to manage and monitor a variety of surface activities that include seismic surveying, exploration drilling, oil-field development drilling, construction of oil-production facilities, and construction of pipelines and access roads. BLM evaluates a variety of permit applications, environmental impact studies, and other documents that require rapid compilation and analysis of data pertaining to surface and subsurface geology, hydrology, and biology. In addition, BLM must monitor these activities and assess their impacts on the natural environment. Timely and accurate completion of these land-management tasks requires elevation, hydrologic, geologic, petroleum-activity, and cadastral data, all integrated in digital formats at a higher resolution than is currently available in nondigital (paper) formats. To support these land-management tasks, a series of maps was generated from remotely sensed data in an area of high petroleum-industry activity (fig. 1). The maps cover an area from approximately latitude 70?00' N. to 70?30' N. and from longitude 151?00' W. to 153?10' W. The area includes the Alpine oil field in the east, the Husky Inigok exploration well (site of a landing strip) in the west, many of the exploration wells drilled in NPRA since 2000, and the route of a proposed pipeline to carry oil from discovery wells in NPRA to the Alpine oil field. This map area is referred to as the 'Fish Creek area' after a creek that flows through the region. The map series includes (1) a color shaded-relief map based on 5-m-resolution data (sheet 1), (2) a surface-classification map based on 30-m-resolution data (sheet 2), and (3) a 5-m-resolution shaded relief-surface classification map that combines the shaded

  3. EMG changes in thigh and calf muscles in fin swimming exercise.

    Science.gov (United States)

    Jammes, Y; Delliaux, S; Coulange, M; Jammes, C; Kipson, N; Brerro-Saby, C; Bregeon, F

    2010-08-01

    Because previous researchers have reported a reduced lactic acid production that accompanies a delayed or an absent ventilatory threshold (VTh) in water-based exercise, we hypothesized that the metaboreflex, activated by muscle acidosis, might be absent in fin swimming. This motor response, delaying the occurrence of fatigue, is characterized by a decreased median frequency (MF) of electromyographic (EMG) power spectrum. Seven healthy subjects performed a maximal fin swimming exercise protocol with simultaneous recordings of surface EMGs in VASTUS MEDIALIS (VM), TIBIALIS ANTERIOR (TA) and GASTROCNEMIUS MEDIALIS (GM). We computed the root mean square (RMS) and MF and recorded the compound evoked muscle potential (M-wave) in VM. We also measured the propulsive force and oxygen uptake (VO (2)), and determined VTh. VTh was absent in 4/7 subjects and measured at 70-90% of VO (2max) in the other three. In the three studied muscles, the global EMG activity (RMS) increased while the MF decreased in proportion of VO (2), the MF changes being significantly higher in VM (-29%) and GM (-39%) than in TA (-19%). Because no M-wave changes were noted, the MF decline was attributed to the recruitment of low-frequency, fatigue-resistant motor units. Our most important finding is the persistence of the metaboreflex even in a situation of reduced muscle acidosis. (c) Georg Thieme Verlag KG Stuttgart . New York.

  4. Computational Intelligence Based Data Fusion Algorithm for Dynamic sEMG and Skeletal Muscle Force Modelling

    Energy Technology Data Exchange (ETDEWEB)

    Chandrasekhar Potluri,; Madhavi Anugolu; Marco P. Schoen; D. Subbaram Naidu

    2013-08-01

    In this work, an array of three surface Electrography (sEMG) sensors are used to acquired muscle extension and contraction signals for 18 healthy test subjects. The skeletal muscle force is estimated using the acquired sEMG signals and a Non-linear Wiener Hammerstein model, relating the two signals in a dynamic fashion. The model is obtained from using System Identification (SI) algorithm. The obtained force models for each sensor are fused using a proposed fuzzy logic concept with the intent to improve the force estimation accuracy and resilience to sensor failure or misalignment. For the fuzzy logic inference system, the sEMG entropy, the relative error, and the correlation of the force signals are considered for defining the membership functions. The proposed fusion algorithm yields an average of 92.49% correlation between the actual force and the overall estimated force output. In addition, the proposed fusionbased approach is implemented on a test platform. Experiments indicate an improvement in finger/hand force estimation.

  5. NEC Hazardous classification and compliance regarding the surface moisture monitor measurement system

    International Nuclear Information System (INIS)

    Bussell, J.H.

    1996-01-01

    The National Electrical Code, NFPA 70, and National Fire Protection Association requirements for use of Surface Moisture Monitor Systems in classified locations are discussed. The design and configuration of the surface moisture monitor are analyzed with respect to how they comply with requirements of the National Electrical Code requirements, articles 500-504

  6. EMG-Torque correction on Human Upper extremity using Evolutionary Computation

    Science.gov (United States)

    JL, Veronica; Parasuraman, S.; Khan, M. K. A. Ahamed; Jeba DSingh, Kingsly

    2016-09-01

    There have been many studies indicating that control system of rehabilitative robot plays an important role in determining the outcome of the therapy process. Existing works have done the prediction of feedback signal in the controller based on the kinematics parameters and EMG readings of upper limb's skeletal system. Kinematics and kinetics based control signal system is developed by reading the output of the sensors such as position sensor, orientation sensor and F/T (Force/Torque) sensor and there readings are to be compared with the preceding measurement to decide on the amount of assistive force. There are also other works that incorporated the kinematics parameters to calculate the kinetics parameters via formulation and pre-defined assumptions. Nevertheless, these types of control signals analyze the movement of the upper limb only based on the movement of the upper joints. They do not anticipate the possibility of muscle plasticity. The focus of the paper is to make use of the kinematics parameters and EMG readings of skeletal system to predict the individual torque of upper extremity's joints. The surface EMG signals are fed into different mathematical models so that these data can be trained through Genetic Algorithm (GA) to find the best correlation between EMG signals and torques acting on the upper limb's joints. The estimated torque attained from the mathematical models is called simulated output. The simulated output will then be compared with the actual individual joint which is calculated based on the real time kinematics parameters of the upper movement of the skeleton when the muscle cells are activated. The findings from this contribution are extended into the development of the active control signal based controller for rehabilitation robot.

  7. Fasciculation potentials in high-density surface EMG.

    NARCIS (Netherlands)

    Drost, G.; Kleine, B.U.; Stegeman, D.F.; Engelen, B.G.M. van; Zwarts, M.J.

    2007-01-01

    Fasciculation potentials (FPs) are observed in healthy individuals, but also in patients with neurogenic disorders. The exact site of origin and the clinical relevance in distinguishing, for example, amyotrophic lateral sclerosis (ALS) from other neurogenic diseases based on specific characteristics

  8. Use of the discriminant Fourier-derived cepstrum with feature-level post-processing for surface electromyographic signal classification

    International Nuclear Information System (INIS)

    Chen, Xinpu; Zhu, Xiangyang; Zhang, Dingguo

    2009-01-01

    Myoelectrical pattern classification is a crucial part in multi-functional prosthesis control. This paper investigates a discriminant Fourier-derived cepstrum (DFC) and feature-level post-processing (FLPP) to discriminate hand and wrist motions using the surface electromyographic signal. The Fourier-derived cepstrum takes advantage of the Fourier magnitude or sub-band power energy of signals directly and provides flexible use of spectral information changing with different motions. Appropriate cepstral coefficients are selected by a proposed separability criterion to construct DFC features. For the post-processing, FLPP which combines features from several analysis windows is used to improve the feature performance further. In this work, two classifiers (a linear discriminant classifier and quadratic discriminant classifier) without hyper-parameter optimization are employed to simplify the training procedure and avoid the possible bias of feature evaluation. Experimental results of the 11-motion problem show that the proposed DFC feature outperforms traditional features such as time-domain statistics and autoregressive-derived cepstrum in terms of the classification accuracy, and it is a promising method for the multi-functionality and high-accuracy control of myoelectric prostheses

  9. Classification of bacterial samples as negative or positive for a UTI and antibiogram using surface enhanced Raman spectroscopy

    Science.gov (United States)

    Kastanos, Evdokia; Hadjigeorgiou, Katerina; Kyriakides, Alexandros; Pitris, Costas

    2011-03-01

    Urinary tract infection (UTI) diagnosis requires an overnight culture to identify a sample as positive or negative for a UTI. Additional cultures are required to identify the pathogen responsible for the infection and to test its sensitivity to antibiotics. A rise in ineffective treatments, chronic infections, rising health care costs and antibiotic resistance are some of the consequences of this prolonged waiting period of UTI diagnosis. In this work, Surface Enhanced Raman Spectroscopy (SERS) is used for classifying bacterial samples as positive or negative for UTI. SERS spectra of serial dilutions of E.coli bacteria, isolated from a urine culture, were classified as positive (105-108 cells/ml) or negative (103-104 cells/ml) for UTI after mixing samples with gold nanoparticles. A leave-one-out cross validation was performed using the first two principal components resulting in the correct classification of 82% of all samples. Sensitivity of classification was 88% and specificity was 67%. Antibiotic sensitivity testing was also done using SERS spectra of various species of gram negative bacteria collected 4 hours after exposure to antibiotics. Spectral analysis revealed clear separation between the spectra of samples exposed to ciprofloxacin (sensitive) and amoxicillin (resistant). This study can become the basis for identifying urine samples as positive or negative for a UTI and determining their antibiogram without requiring an overnight culture.

  10. Electrotactile EMG feedback improves the control of prosthesis grasping force

    Science.gov (United States)

    Schweisfurth, Meike A.; Markovic, Marko; Dosen, Strahinja; Teich, Florian; Graimann, Bernhard; Farina, Dario

    2016-10-01

    Objective. A drawback of active prostheses is that they detach the subject from the produced forces, thereby preventing direct mechanical feedback. This can be compensated by providing somatosensory feedback to the user through mechanical or electrical stimulation, which in turn may improve the utility, sense of embodiment, and thereby increase the acceptance rate. Approach. In this study, we compared a novel approach to closing the loop, namely EMG feedback (emgFB), to classic force feedback (forceFB), using electrotactile interface in a realistic task setup. Eleven intact-bodied subjects and one transradial amputee performed a routine grasping task while receiving emgFB or forceFB. The two feedback types were delivered through the same electrotactile interface, using a mixed spatial/frequency coding to transmit 8 discrete levels of the feedback variable. In emgFB, the stimulation transmitted the amplitude of the processed myoelectric signal generated by the subject (prosthesis input), and in forceFB the generated grasping force (prosthesis output). The task comprised 150 trials of routine grasping at six forces, randomly presented in blocks of five trials (same force). Interquartile range and changes in the absolute error (AE) distribution (magnitude and dispersion) with respect to the target level were used to assess precision and overall performance, respectively. Main results. Relative to forceFB, emgFB significantly improved the precision of myoelectric commands (min/max of the significant levels) for 23%/36% as well as the precision of force control for 12%/32%, in intact-bodied subjects. Also, the magnitude and dispersion of the AE distribution were reduced. The results were similar in the amputee, showing considerable improvements. Significance. Using emgFB, the subjects therefore decreased the uncertainty of the forward pathway. Since there is a correspondence between the EMG and force, where the former anticipates the latter, the emgFB allowed for

  11. A comparison of two open source LiDAR surface classification algorithms

    Science.gov (United States)

    With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are op...

  12. Classification of Clean and Dirty Pighouse Surfaces Based on Spectral Reflectance

    DEFF Research Database (Denmark)

    Blanke, Mogens; Braithwaite, Ian David; Zhang, Guo-Qiang

    2004-01-01

    of designing a vision based system to locate dirty areas and subsequently direct a cleaning robot to remove dirt. Novel results include the characterisation of the spectral reflectance of real surfaces and dirt in a pig house and the design of illumination to obtain discrimination of clean from dirty areas...

  13. A comparison of two open source LiDAR surface classification algorithms

    Science.gov (United States)

    Wade T. Tinkham; Hongyu Huang; Alistair M.S. Smith; Rupesh Shrestha; Michael J. Falkowski; Andrew T. Hudak; Timothy E. Link; Nancy F. Glenn; Danny G. Marks

    2011-01-01

    With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are openly available, free to use, and are supported by published results....

  14. Facial EMG responses to emotional expressions are related to emotion perception ability.

    Directory of Open Access Journals (Sweden)

    Janina Künecke

    Full Text Available Although most people can identify facial expressions of emotions well, they still differ in this ability. According to embodied simulation theories understanding emotions of others is fostered by involuntarily mimicking the perceived expressions, causing a "reactivation" of the corresponding mental state. Some studies suggest automatic facial mimicry during expression viewing; however, findings on the relationship between mimicry and emotion perception abilities are equivocal. The present study investigated individual differences in emotion perception and its relationship to facial muscle responses - recorded with electromyogram (EMG--in response to emotional facial expressions. N° = °269 participants completed multiple tasks measuring face and emotion perception. EMG recordings were taken from a subsample (N° = °110 in an independent emotion classification task of short videos displaying six emotions. Confirmatory factor analyses of the m. corrugator supercilii in response to angry, happy, sad, and neutral expressions showed that individual differences in corrugator activity can be separated into a general response to all faces and an emotion-related response. Structural equation modeling revealed a substantial relationship between the emotion-related response and emotion perception ability, providing evidence for the role of facial muscle activation in emotion perception from an individual differences perspective.

  15. Facial EMG responses to emotional expressions are related to emotion perception ability.

    Science.gov (United States)

    Künecke, Janina; Hildebrandt, Andrea; Recio, Guillermo; Sommer, Werner; Wilhelm, Oliver

    2014-01-01

    Although most people can identify facial expressions of emotions well, they still differ in this ability. According to embodied simulation theories understanding emotions of others is fostered by involuntarily mimicking the perceived expressions, causing a "reactivation" of the corresponding mental state. Some studies suggest automatic facial mimicry during expression viewing; however, findings on the relationship between mimicry and emotion perception abilities are equivocal. The present study investigated individual differences in emotion perception and its relationship to facial muscle responses - recorded with electromyogram (EMG)--in response to emotional facial expressions. N° = °269 participants completed multiple tasks measuring face and emotion perception. EMG recordings were taken from a subsample (N° = °110) in an independent emotion classification task of short videos displaying six emotions. Confirmatory factor analyses of the m. corrugator supercilii in response to angry, happy, sad, and neutral expressions showed that individual differences in corrugator activity can be separated into a general response to all faces and an emotion-related response. Structural equation modeling revealed a substantial relationship between the emotion-related response and emotion perception ability, providing evidence for the role of facial muscle activation in emotion perception from an individual differences perspective.

  16. Identification of motion from multi-channel EMG signals for control of prosthetic hand

    International Nuclear Information System (INIS)

    Geethanjali, P.; Ray, K.K.

    2011-01-01

    Full text: The authors in this paper propose an effective and efficient pattern recognition technique from four channel electromyogram (EMG) signals for control of multifunction prosthetic hand. Time domain features such as mean absolute value, number of zero crossings, number of slope sign changes and waveform length are considered for pattern recognition. The patterns are classified using simple logistic regression (SLR) technique and decision tree (DT) using J48 algorithm. In this study six specific hand and wrist motions are identified from the EMG signals obtained from ten different able-bodied. By considering relevant dominant features for pattern recognition, the processing time as well as memory space of the SLR and DT classifiers is found to be less in comparison with neural network (NN), k-nearest neighbour model 1 (kNN Model-1), k-nearest neighbour model 2 (kNN-Model-2) and linear discriminant analysis. The classification accuracy of SLR classifier is found to be 91 ± 1.9%. (author)

  17. Intramuscular pressure and EMG relate during static contractions but dissociate with movement and fatigue

    DEFF Research Database (Denmark)

    Sjøgaard, Gisela; Jensen, Bente R.; Hargens, Allan R.

    2004-01-01

    Intramuscular pressure (IMP) and electromyography (EMG) mirror muscle force in the nonfatigued muscle during static contractions. The present study explores whether the constant IMP-EMG relationship with increased force may be extended to dynamic contractions and to fatigued muscle. IMP and EMG...... with speed of abduction. In the nonfatigued supraspinatus muscle, a linear relationship was found between IMP and EMG; in contrast, during fatigue and recovery, significant timewise changes of the IMP-to-EMG ratio occurred. The results indicate that IMP should be included along with EMG when mechanical load...... sharing between muscles is evaluated during dynamic and fatiguing contractions....

  18. Modelling the angular effects on satellite retrieved LST at global scale using a land surface classification

    Science.gov (United States)

    Ermida, Sofia; DaCamara, Carlos C.; Trigo, Isabel F.; Pires, Ana C.; Ghent, Darren

    2017-04-01

    Land Surface Temperature (LST) is a key climatological variable and a diagnostic parameter of land surface conditions. Remote sensing constitutes the most effective method to observe LST over large areas and on a regular basis. Although LST estimation from remote sensing instruments operating in the Infrared (IR) is widely used and has been performed for nearly 3 decades, there is still a list of open issues. One of these is the LST dependence on viewing and illumination geometry. This effect introduces significant discrepancies among LST estimations from different sensors, overlapping in space and time, that are not related to uncertainties in the methodologies or input data used. Furthermore, these directional effects deviate LST products from an ideally defined LST, which should represent to the ensemble of directional radiometric temperature of all surface elements within the FOV. Angular effects on LST are here conveniently estimated by means of a kernel model of the surface thermal emission, which describes the angular dependence of LST as a function of viewing and illumination geometry. The model is calibrated using LST data as provided by a wide range of sensors to optimize spatial coverage, namely: 1) a LEO sensor - the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board NASA's TERRA and AQUA; and 2) 3 GEO sensors - the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board EUMETSAT's Meteosat Second Generation (MSG), the Japanese Meteorological Imager (JAMI) on-board the Japanese Meteorological Association (JMA) Multifunction Transport SATellite (MTSAT-2), and NASA's Geostationary Operational Environmental Satellites (GOES). As shown in our previous feasibility studies the sampling of illumination and view angles has a high impact on the obtained model parameters. This impact may be mitigated when the sampling size is increased by aggregating pixels with similar surface conditions. Here we propose a methodology where land surface is

  19. A Discrete-Time Algorithm for Stiffness Extraction from sEMG and Its Application in Antidisturbance Teleoperation

    Directory of Open Access Journals (Sweden)

    Peidong Liang

    2016-01-01

    Full Text Available We have developed a new discrete-time algorithm of stiffness extraction from muscle surface electromyography (sEMG collected from human operator’s arms and have applied it for antidisturbance control in robot teleoperation. The variation of arm stiffness is estimated from sEMG signals and transferred to a telerobot under variable impedance control to imitate human motor control behaviours, particularly for disturbance attenuation. In comparison to the estimation of stiffness from sEMG, the proposed algorithm is able to reduce the nonlinear residual error effect and to enhance robustness and to simplify stiffness calibration. In order to extract a smoothing stiffness enveloping from sEMG signals, two enveloping methods are employed in this paper, namely, fast linear enveloping based on low pass filtering and moving average and amplitude monocomponent and frequency modulating (AM-FM method. Both methods have been incorporated into the proposed stiffness variance estimation algorithm and are extensively tested. The test results show that stiffness variation extraction based on the two methods is sensitive and robust to attenuation disturbance. It could potentially be applied for teleoperation in the presence of hazardous surroundings or human robot physical cooperation scenarios.

  20. Mandibular kinematics and masticatory muscles EMG in patients with short lasting TMD of mild-moderate severity.

    Science.gov (United States)

    De Felício, Cláudia Maria; Mapelli, Andrea; Sidequersky, Fernanda Vincia; Tartaglia, Gianluca M; Sforza, Chiarella

    2013-06-01

    Mandibular kinematic and standardized surface electromyography (sEMG) characteristics of masticatory muscles of subjects with short lasting TMD of mild-moderate severity were examined. Volunteers were submitted to clinical examination and questionnaire of severity. Ten subjects with TMD (age 27.3years, SD 7.8) and 10 control subjects without TMD, matched by age, were selected. Mandibular movements were recorded during free maximum mouth opening and closing (O-C) and unilateral, left and right, gum chewing. sEMG of the masseter and temporal muscles was performed during maximum teeth clenching either on cotton rolls or in intercuspal position, and during gum chewing. sEMG indices were obtained. Subjects with TMD, relative to control subjects, had lower relative mandibular rotation at the end of mouth opening, larger mean number of intersection between interincisal O-C paths during mastication and smaller asymmetry between working and balancing side, with participation beyond the expected of the contralateral muscles (Pkinematic parameters and the EMG indices of the static test, although some changes in the mastication were observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Wireless sEMG System with a Microneedle-Based High-Density Electrode Array on a Flexible Substrate.

    Science.gov (United States)

    Kim, Minjae; Gu, Gangyong; Cha, Kyoung Je; Kim, Dong Sung; Chung, Wan Kyun

    2017-12-30

    Surface electromyography (sEMG) signals reflect muscle contraction and hence, can provide information regarding a user's movement intention. High-density sEMG systems have been proposed to measure muscle activity in small areas and to estimate complex motion using spatial patterns. However, conventional systems based on wet electrodes have several limitations. For example, the electrolyte enclosed in wet electrodes restricts spatial resolution, and these conventional bulky systems limit natural movements. In this paper, a microneedle-based high-density electrode array on a circuit integrated flexible substrate for sEMG is proposed. Microneedles allow for high spatial resolution without requiring conductive substances, and flexible substrates guarantee stable skin-electrode contact. Moreover, a compact signal processing system is integrated with the electrode array. Therefore, sEMG measurements are comfortable to the user and do not interfere with the movement. The system performance was demonstrated by testing its operation and estimating motion using a Gaussian mixture model-based, simplified 2D spatial pattern.

  2. An EMG Interface for the Control of Motion and Compliance of a Supernumerary Robotic Finger

    Science.gov (United States)

    Hussain, Irfan; Spagnoletti, Giovanni; Salvietti, Gionata; Prattichizzo, Domenico

    2016-01-01

    In this paper, we propose a novel electromyographic (EMG) control interface to control motion and joints compliance of a supernumerary robotic finger. The supernumerary robotic fingers are a recently introduced class of wearable robotics that provides users additional robotic limbs in order to compensate or augment the existing abilities of natural limbs without substituting them. Since supernumerary robotic fingers are supposed to closely interact and perform actions in synergy with the human limbs, the control principles of extra finger should have similar behavior as human’s ones including the ability of regulating the compliance. So that, it is important to propose a control interface and to consider the actuators and sensing capabilities of the robotic extra finger compatible to implement stiffness regulation control techniques. We propose EMG interface and a control approach to regulate the compliance of the device through servo actuators. In particular, we use a commercial EMG armband for gesture recognition to be associated with the motion control of the robotic device and surface one channel EMG electrodes interface to regulate the compliance of the robotic device. We also present an updated version of a robotic extra finger where the adduction/abduction motion is realized through ball bearing and spur gears mechanism. We have validated the proposed interface with two sets of experiments related to compensation and augmentation. In the first set of experiments, different bimanual tasks have been performed with the help of the robotic device and simulating a paretic hand since this novel wearable system can be used to compensate the missing grasping abilities in chronic stroke patients. In the second set, the robotic extra finger is used to enlarge the workspace and manipulation capability of healthy hands. In both sets, the same EMG control interface has been used. The obtained results demonstrate that the proposed control interface is intuitive and can

  3. A connectionist-geostatistical approach for classification of deformation types in ice surfaces

    Science.gov (United States)

    Goetz-Weiss, L. R.; Herzfeld, U. C.; Hale, R. G.; Hunke, E. C.; Bobeck, J.

    2014-12-01

    Deformation is a class of highly non-linear geophysical processes from which one can infer other geophysical variables in a dynamical system. For example, in an ice-dynamic model, deformation is related to velocity, basal sliding, surface elevation changes, and the stress field at the surface as well as internal to a glacier. While many of these variables cannot be observed, deformation state can be an observable variable, because deformation in glaciers (once a viscosity threshold is exceeded) manifests itself in crevasses.Given the amount of information that can be inferred from observing surface deformation, an automated method for classifying surface imagery becomes increasingly desirable. In this paper a Neural Network is used to recognize classes of crevasse types over the Bering Bagley Glacier System (BBGS) during a surge (2011-2013-?). A surge is a spatially and temporally highly variable and rapid acceleration of the glacier. Therefore, many different crevasse types occur in a short time frame and in close proximity, and these crevasse fields hold information on the geophysical processes of the surge.The connectionist-geostatistical approach uses directional experimental (discrete) variograms to parameterize images into a form that the Neural Network can recognize. Recognizing that each surge wave results in different crevasse types and that environmental conditions affect the appearance in imagery, we have developed a semi-automated pre-training software to adapt the Neural Net to chaining conditions.The method is applied to airborne and satellite imagery to classify surge crevasses from the BBGS surge. This method works well for classifying spatially repetitive images such as the crevasses over Bering Glacier. We expand the network for less repetitive images in order to analyze imagery collected over the Arctic sea ice, to assess the percentage of deformed ice for model calibration.

  4. ON THE CLASSIFICATION OF UGC 1382 AS A GIANT LOW SURFACE BRIGHTNESS GALAXY

    Energy Technology Data Exchange (ETDEWEB)

    Hagen, Lea M. Z.; Hagen, Alex [Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802 (United States); Seibert, Mark; Rich, Jeffrey A.; Madore, Barry F. [Observatories of the Carnegie Institution for Science, 813 Santa Barbara Street, Pasadena, CA 91101 (United States); Nyland, Kristina; Young, Lisa M. [Physics Department, New Mexico Institute of Mining and Technology, Socorro, NM 87801 (United States); Neill, James D. [California Institute of Technology, Pasadena, CA 91125 (United States); Treyer, Marie [Aix Marseille Université, CNRS, Laboratoire d’Astrophysique de Marseille, UMR 7326, 38 rue F. Joliot-Curie, F-13388 Marseille (France)

    2016-08-01

    We provide evidence that UGC 1382, long believed to be a passive elliptical galaxy, is actually a giant low surface brightness (GLSB) galaxy that rivals the archetypical GLSB Malin 1 in size. Like other GLSB galaxies, it has two components: a high surface brightness disk galaxy surrounded by an extended low surface brightness (LSB) disk. For UGC 1382, the central component is a lenticular system with an effective radius of 6 kpc. Beyond this, the LSB disk has an effective radius of ∼38 kpc and an extrapolated central surface brightness of ∼26 mag arcsec{sup 2}. Both components have a combined stellar mass of ∼8 × 10{sup 10} M {sub ⊙}, and are embedded in a massive (10{sup 10} M {sub ⊙}) low-density (<3 M {sub ⊙} pc{sup 2}) HI disk with a radius of 110 kpc, making this one of the largest isolated disk galaxies known. The system resides in a massive dark matter halo of at least 2 × 10{sup 12} M {sub ⊙}. Although possibly part of a small group, its low-density environment likely plays a role in the formation and retention of the giant LSB and HI disks. We model the spectral energy distributions and find that the LSB disk is likely older than the lenticular component. UGC 1382 has UV–optical colors typical of galaxies transitioning through the green valley. Within the LSB disk are spiral arms forming stars at extremely low efficiencies. The gas depletion timescale of ∼10{sup 11} years suggests that UGC 1382 may be a very-long-term resident of the green valley. We find that the formation and evolution of the LSB disk in UGC 1382 is best explained by the accretion of gas-rich LSB dwarf galaxies.

  5. Surface mapping via unsupervised classification of remote sensing: application to MESSENGER/MASCS and DAWN/VIRS data.

    Science.gov (United States)

    D'Amore, M.; Le Scaon, R.; Helbert, J.; Maturilli, A.

    2017-12-01

    Machine-learning achieved unprecedented results in high-dimensional data processing tasks with wide applications in various fields. Due to the growing number of complex nonlinear systems that have to be investigated in science and the bare raw size of data nowadays available, ML offers the unique ability to extract knowledge, regardless the specific application field. Examples are image segmentation, supervised/unsupervised/ semi-supervised classification, feature extraction, data dimensionality analysis/reduction.The MASCS instrument has mapped Mercury surface in the 400-1145 nm wavelength range during orbital observations by the MESSENGER spacecraft. We have conducted k-means unsupervised hierarchical clustering to identify and characterize spectral units from MASCS observations. The results display a dichotomy: a polar and equatorial units, possibly linked to compositional differences or weathering due to irradiation. To explore possible relations between composition and spectral behavior, we have compared the spectral provinces with elemental abundance maps derived from MESSENGER's X-Ray Spectrometer (XRS).For the Vesta application on DAWN Visible and infrared spectrometer (VIR) data, we explored several Machine Learning techniques: image segmentation method, stream algorithm and hierarchical clustering.The algorithm successfully separates the Olivine outcrops around two craters on Vesta's surface [1]. New maps summarizing the spectral and chemical signature of the surface could be automatically produced.We conclude that instead of hand digging in data, scientist could choose a subset of algorithms with well known feature (i.e. efficacy on the particular problem, speed, accuracy) and focus their effort in understanding what important characteristic of the groups found in the data mean. [1] E Ammannito et al. "Olivine in an unexpected location on Vesta's surface". In: Nature 504.7478 (2013), pp. 122-125.

  6. Surface-seismic imaging for nehrp soil profile classifications and earthquake hazards in urban areas

    Science.gov (United States)

    Williams, R.A.; Stephenson, W.J.; Odum, J.K.

    1998-01-01

    We acquired high-resolution seismic-refraction data on the ground surface in selected areas of the San Fernando Valley (SFV) to help explain the earthquake damage patterns and the variation in ground motion caused by the 17 January 1994 magnitude 6.7 Northridge earthquake. We used these data to determine the compressional- and shear-wave velocities (Vp and Vs) at 20 aftershock recording sites to 30-m depth ( V??s30, and V??p30). Two other sites, located next to boreholes with downhole Vp and Vs data, show that we imaged very similar seismic-vefocity structures in the upper 40 m. Overall, high site response appears to be associated with tow Vs in the near surface, but there can be a wide rangepf site amplifications for a given NEHRP soil type. The data suggest that for the SFV, if the V??s30 is known, we can determine whether the earthquake ground motion will be amplified above a factor of 2 relative to a local rock site.

  7. A statistical-textural-features based approach for classification of solid drugs using surface microscopic images.

    Science.gov (United States)

    Tahir, Fahima; Fahiem, Muhammad Abuzar

    2014-01-01

    The quality of pharmaceutical products plays an important role in pharmaceutical industry as well as in our lives. Usage of defective tablets can be harmful for patients. In this research we proposed a nondestructive method to identify defective and nondefective tablets using their surface morphology. Three different environmental factors temperature, humidity and moisture are analyzed to evaluate the performance of the proposed method. Multiple textural features are extracted from the surface of the defective and nondefective tablets. These textural features are gray level cooccurrence matrix, run length matrix, histogram, autoregressive model and HAAR wavelet. Total textural features extracted from images are 281. We performed an analysis on all those 281, top 15, and top 2 features. Top 15 features are extracted using three different feature reduction techniques: chi-square, gain ratio and relief-F. In this research we have used three different classifiers: support vector machine, K-nearest neighbors and naïve Bayes to calculate the accuracies against proposed method using two experiments, that is, leave-one-out cross-validation technique and train test models. We tested each classifier against all selected features and then performed the comparison of their results. The experimental work resulted in that in most of the cases SVM performed better than the other two classifiers.

  8. Guidance For The Proper Characterization And Classification Of Low Specific Activity Materials And Surface Contaminated Objects For Disposal

    International Nuclear Information System (INIS)

    Portsmouth, J.H.; Blackford, L.T.

    2012-01-01

    Regulatory concerns over the proper characterization of certain waste streams led CH2M HILL Plateau Remediation Company (CHPRC) to develop written guidance for personnel involved in Decontamination and Decommissioning (D and D) activities, facility management and Waste Management Representatives (WMRs) involved in the designation of wastes for disposal on and off the Hanford Site. It is essential that these waste streams regularly encountered in D and D operations are properly designated, characterized and classified prior to shipment to a Treatment, Storage or Disposal Facility (TSDF). Shipments of waste determined by the classification process as Low Specific Activity (LSA) or Surface Contaminated Objects (SCO) must also be compliant with all applicable U.S. Department of Transportation (DOE) regulations as well as Department of Energy (DOE) orders. The compliant shipment of these waste commodities is critical to the Hanford Central Plateau cleanup mission. Due to previous problems and concerns from DOE assessments, CHPRC internal critiques as well as DOT, a management decision was made to develop written guidance and procedures to assist CHPRC shippers and facility personnel in the proper classification of D and D waste materials as either LSA or SCO. The guidance provides a uniform methodology for the collection and documentation required to effectively characterize, classify and identify candidate materials for shipping operations. A primary focus is to ensure that waste materials generated from D and D and facility operations are compliant with the DOT regulations when packaged for shipment. At times this can be difficult as the current DOT regulations relative to the shipment of LSA and SCO materials are often not clear to waste generators. Guidance is often sought from NUREG 1608/RAMREG-003 (3): a guidance document that was jointly developed by the DOT and the Nuclear Regulatory Commission (NRC) and published in 1998. However, NUREG 1608 (3) is now thirteen

  9. Evaluating EMG Feature and Classifier Selection for Application to Partial-Hand Prosthesis Control

    Directory of Open Access Journals (Sweden)

    Adenike A. Adewuyi

    2016-10-01

    Full Text Available Pattern recognition-based myoelectric control of upper limb prostheses has the potential to restore control of multiple degrees of freedom. Though this control method has been extensively studied in individuals with higher-level amputations, few studies have investigated its effectiveness for individuals with partial-hand amputations. Most partial-hand amputees retain a functional wrist and the ability of pattern recognition-based methods to correctly classify hand motions from different wrist positions is not well studied. In this study, focusing on partial-hand amputees, we evaluate (1 the performance of non-linear and linear pattern recognition algorithms and (2 the performance of optimal EMG feature subsets for classification of four hand motion classes in different wrist positions for 16 non-amputees and 4 amputees. Our results show that linear discriminant analysis and linear and non-linear artificial neural networks perform significantly better than the quadratic discriminant analysis for both non-amputees and partial-hand amputees. For amputees, including information from multiple wrist positions significantly decreased error (p<0.001 but no further significant decrease in error occurred when more than 4, 2, or 3 positions were included for the extrinsic (p=0.07, intrinsic (p=0.06, or combined extrinsic and intrinsic muscle EMG (p=0.08, respectively. Finally, we found that a feature set determined by selecting optimal features from each channel outperformed the commonly used time domain (p<0.001 and time domain/autoregressive feature sets (p<0.01. This method can be used as a screening filter to select the features from each channel that provide the best classification of hand postures across different wrist positions.

  10. A frequency and pulse-width co-modulation strategy for transcutaneous neuromuscular electrical stimulation based on sEMG time-domain features

    Science.gov (United States)

    Zhou, Yu-Xuan; Wang, Hai-Peng; Bao, Xue-Liang; Lü, Xiao-Ying; Wang, Zhi-Gong

    2016-02-01

    Objective. Surface electromyography (sEMG) is often used as a control signal in neuromuscular electrical stimulation (NMES) systems to enhance the voluntary control and proprioceptive sensory feedback of paralyzed patients. Most sEMG-controlled NMES systems use the envelope of the sEMG signal to modulate the stimulation intensity (current amplitude or pulse width) with a constant frequency. The aims of this study were to develop a strategy that co-modulates frequency and pulse width based on features of the sEMG signal and to investigate the torque-reproduction performance and the level of fatigue resistance achieved with our strategy. Approach. We examined the relationships between wrist torque and two stimulation parameters (frequency and pulse width) and between wrist torque and two sEMG time-domain features (mean absolute value (MAV) and number of slope sign changes (NSS)) in eight healthy volunteers. By using wrist torque as an intermediate variable, customized and generalized transfer functions were constructed to convert the two features of the sEMG signal into the two stimulation parameters, thereby establishing a MAV/NSS dual-coding (MNDC) algorithm. Wrist torque reproduction performance was assessed by comparing the torque generated by the algorithms with that originally recorded during voluntary contractions. Muscle fatigue was assessed by measuring the decline percentage of the peak torque and by comparing the torque time integral of the response to test stimulation trains before and after fatigue sessions. Main Results. The MNDC approach could produce a wrist torque that closely matched the voluntary wrist torque. In addition, a smaller decay in the wrist torque was observed after the MNDC-coded fatigue stimulation was applied than after stimulation using pulse-width modulation alone. Significance. Compared with pulse-width modulation stimulation strategies that are based on sEMG detection, the MNDC strategy is more effective for both voluntary muscle

  11. EMG patterns during assisted walking in the exoskeleton

    Directory of Open Access Journals (Sweden)

    Francesca eSylos-Labini

    2014-06-01

    Full Text Available Neuroprosthetic technology and robotic exoskeletons are being developed to facilitate stepping, reduce muscle efforts and promote motor recovery. Nevertheless, the guidance forces of an exoskeleton may influence the sensory inputs, sensorimotor interactions and resulting muscle activity patterns during stepping. The aim of this study was to report the muscle activation patterns in a sample of intact and injured subjects while walking with a robotic exoskeleton and, in particular, to quantify the level of muscle activity during assisted gait. We recorded electromyographic (EMG activity of different leg and arm muscles during overground walking in an exoskeleton in six healthy individuals and four spinal cord injury (SCI participants. In SCI patients, EMG activity of the upper limb muscles was augmented while activation of leg muscles was typically small. Contrary to our expectations, however, in neurologically intact subjects, EMG activity of leg muscles was similar or even larger during exoskeleton-assisted walking compared to normal overground walking. In addition, significant variations in the EMG waveforms were found across different walking conditions. The most variable pattern was observed in the hamstring muscles. Overall, the results are consistent with a non-linear reorganization of the locomotor output when using the robotic stepping devices. The findings may contribute to our understanding of human-machine interactions and adaptation of locomotor activity patterns.

  12. EMG based FES for post-stroke rehabilitation

    Science.gov (United States)

    Piyus, Ceethal K.; Anjaly Cherian, V.; Nageswaran, Sharmila

    2017-11-01

    Annually, 15 million in world population experiences stroke. Nearly 9 million stroke survivors every year experience mild to severe disability. The loss of upper extremity function in stroke survivors still remains a major rehabilitation challenge. The proposed EMG Abstract—Annually, 15 million in world population experiences stroke. Nearly 9 million stroke survivors every year experience mild to severe disability. The loss of upper extremity function in stroke survivors still remains a major rehabilitation challenge. The proposed EMG based FES system can be used for effective upper limb motor re-education in post stroke upper limb rehabilitation. The governing feature of the designed system is its synchronous activation, in which the FES stimulation is dependent on the amplitude of the EMG signal acquired from the unaffected upper limb muscle of the hemiplegic patient. This proportionate operation eliminates the undesirable damage to the patient’s skin by generating stimulus in proportion to voluntary EMG signals. This feature overcomes the disadvantages of currently available manual motor re-education systems. This model can be used in home-based post stroke rehabilitation, to effectively improve the upper limb functions.

  13. Trapezius muscle EMG as predictor of mental stress

    NARCIS (Netherlands)

    Wijsman, J.L.P; Grundlehner, B.; Penders, J.; Hermens, Hermanus J.

    Stress is a growing problem in society and can cause musculoskeletal complaints. It would be useful to measure stress for prevention of stress-related health problems. An experiment is described in which EMG signals of the upper trapezius muscle were measured with a wireless system during three

  14. Effects of load on good morning kinematics and EMG activity

    Directory of Open Access Journals (Sweden)

    Andrew David Vigotsky

    2015-01-01

    Full Text Available Many strength and conditioning coaches utilize the good morning (GM to strengthen the hamstrings and spinal erectors. However, little research exists on its electromyography (EMG activity and kinematics, and how these variables change as a function of load. The purpose of this investigation was to examine how estimated hamstring length, integrated EMG (IEMG activity of the hamstrings and spinal erectors, and kinematics of the lumbar spine, hip, knee, and ankle are affected by changes in load. Fifteen trained male participants (age = 24.6 ± 5.3 years; body mass = 84.7 ± 11.3 kg; height = 180.9 ± 6.8 cm were recruited for this study. Participants performed five sets of the GM, utilizing 50, 60, 70, 80, and 90% of one-repetition maximum (1RM in a randomized fashion. IEMG activity of hamstrings and spinal erectors tended to increase with load. Knee flexion increased with load on all trials. Estimated hamstring length decreased with load. However, lumbar flexion, hip flexion, and plantar flexion experienced no remarkable changes between trials. These data provide insight as to how changing the load of the GM affects EMG activity, kinematic variables, and estimated hamstring length. Implications for hamstring injury prevention are discussed. More research is needed for further insight as to how load affects EMG activity and kinematics of other exercises.

  15. EMG patterns during assisted walking in the exoskeleton

    Science.gov (United States)

    Sylos-Labini, Francesca; La Scaleia, Valentina; d'Avella, Andrea; Pisotta, Iolanda; Tamburella, Federica; Scivoletto, Giorgio; Molinari, Marco; Wang, Shiqian; Wang, Letian; van Asseldonk, Edwin; van der Kooij, Herman; Hoellinger, Thomas; Cheron, Guy; Thorsteinsson, Freygardur; Ilzkovitz, Michel; Gancet, Jeremi; Hauffe, Ralf; Zanov, Frank; Lacquaniti, Francesco; Ivanenko, Yuri P.

    2014-01-01

    Neuroprosthetic technology and robotic exoskeletons are being developed to facilitate stepping, reduce muscle efforts, and promote motor recovery. Nevertheless, the guidance forces of an exoskeleton may influence the sensory inputs, sensorimotor interactions and resulting muscle activity patterns during stepping. The aim of this study was to report the muscle activation patterns in a sample of intact and injured subjects while walking with a robotic exoskeleton and, in particular, to quantify the level of muscle activity during assisted gait. We recorded electromyographic (EMG) activity of different leg and arm muscles during overground walking in an exoskeleton in six healthy individuals and four spinal cord injury (SCI) participants. In SCI patients, EMG activity of the upper limb muscles was augmented while activation of leg muscles was typically small. Contrary to our expectations, however, in neurologically intact subjects, EMG activity of leg muscles was similar or even larger during exoskeleton-assisted walking compared to normal overground walking. In addition, significant variations in the EMG waveforms were found across different walking conditions. The most variable pattern was observed in the hamstring muscles. Overall, the results are consistent with a non-linear reorganization of the locomotor output when using the robotic stepping devices. The findings may contribute to our understanding of human-machine interactions and adaptation of locomotor activity patterns. PMID:24982628

  16. 3D-printing soft sEMG sensing structures

    NARCIS (Netherlands)

    Wolterink, Gerjan; Sanders, Remco; Muijzer, Frodo; van Beijnum, Bert-Jan; Krijnen, Gijs

    2017-01-01

    This paper describes the development and characterization of soft and flexible 3D-printed sEMG electrodes. The electrodes are printed in one go on a low cost consumer multi-material FDM printer. The printed structures do not need any further production steps to give them conductive properties.

  17. EMG Processing Based Measures of Fatigue Assessment during Manual Lifting

    Directory of Open Access Journals (Sweden)

    E. F. Shair

    2017-01-01

    Full Text Available Manual lifting is one of the common practices used in the industries to transport or move objects to a desired place. Nowadays, even though mechanized equipment is widely available, manual lifting is still considered as an essential way to perform material handling task. Improper lifting strategies may contribute to musculoskeletal disorders (MSDs, where overexertion contributes as the highest factor. To overcome this problem, electromyography (EMG signal is used to monitor the workers’ muscle condition and to find maximum lifting load, lifting height and number of repetitions that the workers are able to handle before experiencing fatigue to avoid overexertion. Past researchers have introduced several EMG processing techniques and different EMG features that represent fatigue indices in time, frequency, and time-frequency domain. The impact of EMG processing based measures in fatigue assessment during manual lifting are reviewed in this paper. It is believed that this paper will greatly benefit researchers who need a bird’s eye view of the biosignal processing which are currently available, thus determining the best possible techniques for lifting applications.

  18. EMG Processing Based Measures of Fatigue Assessment during Manual Lifting

    Science.gov (United States)

    Marhaban, M. H.; Abdullah, A. R.

    2017-01-01

    Manual lifting is one of the common practices used in the industries to transport or move objects to a desired place. Nowadays, even though mechanized equipment is widely available, manual lifting is still considered as an essential way to perform material handling task. Improper lifting strategies may contribute to musculoskeletal disorders (MSDs), where overexertion contributes as the highest factor. To overcome this problem, electromyography (EMG) signal is used to monitor the workers' muscle condition and to find maximum lifting load, lifting height and number of repetitions that the workers are able to handle before experiencing fatigue to avoid overexertion. Past researchers have introduced several EMG processing techniques and different EMG features that represent fatigue indices in time, frequency, and time-frequency domain. The impact of EMG processing based measures in fatigue assessment during manual lifting are reviewed in this paper. It is believed that this paper will greatly benefit researchers who need a bird's eye view of the biosignal processing which are currently available, thus determining the best possible techniques for lifting applications. PMID:28303251

  19. EMG Biofeedback Training Versus Systematic Desensitization for Test Anxiety Reduction

    Science.gov (United States)

    Romano, John L.; Cabianca, William A.

    1978-01-01

    Biofeedback training to reduce test anxiety among university students was investigated. Biofeedback training with systematic desensitization was compared to an automated systematic desensitization program not using EMG feedback. Biofeedback training is a useful technique for reducing test anxiety, but not necessarily more effective than systematic…

  20. A method for discrimination of noise and EMG signal regions recorded during rhythmic behaviors.

    Science.gov (United States)

    Ying, Rex; Wall, Christine E

    2016-12-08

    Analyses of muscular activity during rhythmic behaviors provide critical data for biomechanical studies. Electrical potentials measured from muscles using electromyography (EMG) require discrimination of noise regions as the first step in analysis. An experienced analyst can accurately identify the onset and offset of EMG but this process takes hours to analyze a short (10-15s) record of rhythmic EMG bursts. Existing computational techniques reduce this time but have limitations. These include a universal threshold for delimiting noise regions (i.e., a single signal value for identifying the EMG signal onset and offset), pre-processing using wide time intervals that dampen sensitivity for EMG signal characteristics, poor performance when a low frequency component (e.g., DC offset) is present, and high computational complexity leading to lack of time efficiency. We present a new statistical method and MATLAB script (EMG-Extractor) that includes an adaptive algorithm to discriminate noise regions from EMG that avoids these limitations and allows for multi-channel datasets to be processed. We evaluate the EMG-Extractor with EMG data on mammalian jaw-adductor muscles during mastication, a rhythmic behavior typified by low amplitude onsets/offsets and complex signal pattern. The EMG-Extractor consistently and accurately distinguishes noise from EMG in a manner similar to that of an experienced analyst. It outputs the raw EMG signal region in a form ready for further analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. TextureCam Field Test Results from the Mojave Desert, California: Autonomous Instrument Classification of Sediment and Rock Surfaces

    Science.gov (United States)

    Castano, R.; Abbey, W. J.; Bekker, D. L.; Cabrol, N. A.; Francis, R.; Manatt, K.; Ortega, K.; Thompson, D. R.; Wagstaff, K.

    2013-12-01

    TextureCam is an intelligent camera that uses integrated image analysis to classify sediment and rock surfaces into basic visual categories. This onboard image understanding can improve the autonomy of exploration spacecraft during the long periods when they are out of contact with operators. This could increase the number of science activities performed in each command cycle by, for example, autonomously targeting science features of opportunity with narrow field of view remote sensing, identifying clean surfaces for autonomous placement of arm-mounted instruments, or by detecting high value images for prioritized downlink. TextureCam incorporates image understanding directly into embedded hardware with a Field Programmable Gate Array (FPGA). This allows the instrument to perform the classification in real time without taxing the primary spacecraft computing resources. We use a machine learning approach in which operators train a statistical model of surface appearance using examples from previously acquired images. A random forest model extrapolates from these training cases, using the statistics of small image patches to characterize the texture of each pixel independently. Applying this model to each pixel in a new image yields a map of surface units. We deployed a prototype instrument in the Cima Volcanic Fields during a series of experiments in May 2013. We imaged each environment with a tripod-mounted RGB camera connected directly to the FPGA board for real time processing. Our first scenario assessed ground surface cover on open terrain atop a weathered volcanic flow. We performed a transect consisting of 16 forward-facing images collected at 1m intervals. We trained the system to categorize terrain into four classes: sediment, basalt cobbles, basalt pebbles, and basalt with iron oxide weathering. Accuracy rates with regards to the fraction of the actual feature that was labeled correctly by the automated system were calculated. Lower accuracy rates were

  2. EMG BioanalyzerBR para a análise de sinais eletromiográficos na deglutição EMG BioanalyzerBR for analyzing electromyographic signals when swallowing

    Directory of Open Access Journals (Sweden)

    Paulo Feodrippe

    2012-06-01

    Full Text Available OBJETIVO: descrever as etapas de construção do EMG BioanalyzerBR (versão 1.0 e demonstrar a sua aplicabilidade na análise de parâmetros fornecidos pela eletromiografia de superfície (EMGs. MÉTODOS: trata-se de um estudo descritivo do software de análise desenvolvido para analisar parâmetros obtidos na eletromiografia de superfície de músculos envolvidos na deglutição. Este software foi escrito em um ambiente de desenvolvimento utilizado por pesquisadores do mundo todo, de fácil acessibilidade e programação: o SCILAB. RESULTADOS: esta ferramenta se mostrou eficaz para a análise e transferência de dados nos registros curtos, contendo em média 10s de duração, porém para registros mais longos com duração maior que 20s apresentou falhas que não prejudicaram o cálculo após algumas tentativas. CONCLUSÃO: apesar das dificuldades, O EMG BioanalyzerBR possibilitou a realização das marcações canal por canal e quantas marcações fossem necessárias de forma simultânea,e desta forma a tabulação dos dados ficou mais rápida e com margem de falhas humanas reduzidas, porém com necessidade de aprimoramentos para a versão 2.0.PURPOSE: to describe the construction phases of EMG BioanalyzerBR (version 1.0 and demonstrate its applicability in analyzing parameters provided by surface electromyography (EMG. METHOD: it is a descriptive analysis software developed in order to analyze the parameters obtained in surface electromyography of muscles involved in swallowing. This software was written in a development environment used by worldwide researchers, with easy accessibility and programming: Scilab. RESULTS: this tool has proved effective for analyzing transferring short data records, having on average 10 seconds duration, but for with longest periods above 20s there were some failures that did not harm the calculation after a few tries. CONCLUSION: despite the difficulties, EMG BioanalyzerBR fostered the development of channel

  3. A critical period of corticomuscular and EMG-EMG coherence detection in healthy infants aged 9-25weeks

    DEFF Research Database (Denmark)

    Ritterband-Rosenbaum, Anina; Herskind, Anna; Li, Xi

    2017-01-01

    The early postnatal development of functional corticospinal connections in human infants is not fully clarified. We used EEG and EMG to investigate the development of corticomuscular and intramuscular coherence as indicators of functional corticospinal connectivity in healthy infants aged 1-66 we...

  4. Boundary element analysis of the directional sensitivity of the concentric EMG electrode.

    Science.gov (United States)

    Henneberg, K A; Plonsey, R

    1993-07-01

    Assessment of the motor unit architecture based on concentric electrode motor unit potentials requires a thorough understanding of the recording characteristics of the concentric EMG electrode. Previous simulation studies have attempted to include the effect of EMG electrodes on the recorded waveforms by uniformly averaging the tissue potential at the coordinates of one- or two-dimensional electrode models. By employing the boundary element method, this paper improves earlier models of the concentric EMG electrode by including an accurate geometric representation of the electrode, as well as the mutual electrical influence between the electrode surfaces. A three-dimensional sensitivity function is defined from which information about the preferential direction of sensitivity, blind spots, phase changes, rate of attenuation, and range of pick-up radius can be derived. The study focuses on the intrinsic features linked to the geometry of the electrode. The results show that the cannula perturbs the potential distribution significantly. The core and the cannula electrodes measure potentials of the same order of magnitude in all of the pick-up range, except adjacent to the central wire, where the latter dominates the sensitivity function. The preferential directions of sensitivity are determined by the amount of geometric offset between the individual sensitivity functions of the core and the cannula. The sensitivity function also reveals a complicated pattern of phase changes in the pick-up range. Potentials from fibers located behind the tip or along the cannula are recorded with reversed polarity compared to those located in front of the tip. Rotation of the electrode about its axis was found to alter the duration, the peak-to-peak amplitude, and the rise time of waveforms recorded from a moving dipole.

  5. Wireless sEMG-Based Body-Machine Interface for Assistive Technology Devices.

    Science.gov (United States)

    Fall, Cheikh Latyr; Gagnon-Turcotte, Gabriel; Dube, Jean-Francois; Gagne, Jean Simon; Delisle, Yanick; Campeau-Lecours, Alexandre; Gosselin, Clement; Gosselin, Benoit

    2017-07-01

    Assistive technology (AT) tools and appliances are being more and more widely used and developed worldwide to improve the autonomy of people living with disabilities and ease the interaction with their environment. This paper describes an intuitive and wireless surface electromyography (sEMG) based body-machine interface for AT tools. Spinal cord injuries at C5-C8 levels affect patients' arms, forearms, hands, and fingers control. Thus, using classical AT control interfaces (keypads, joysticks, etc.) is often difficult or impossible. The proposed system reads the AT users' residual functional capacities through their sEMG activity, and converts them into appropriate commands using a threshold-based control algorithm. It has proven to be suitable as a control alternative for assistive devices and has been tested with the JACO arm, an articulated assistive device of which the vocation is to help people living with upper-body disabilities in their daily life activities. The wireless prototype, the architecture of which is based on a 3-channel sEMG measurement system and a 915-MHz wireless transceiver built around a low-power microcontroller, uses low-cost off-the-shelf commercial components. The embedded controller is compared with JACO's regular joystick-based interface, using combinations of forearm, pectoral, masseter, and trapeze muscles. The measured index of performance values is 0.88, 0.51, and 0.41 bits/s, respectively, for correlation coefficients with the Fitt's model of 0.75, 0.85, and 0.67. These results demonstrate that the proposed controller offers an attractive alternative to conventional interfaces, such as joystick devices, for upper-body disabled people using ATs such as JACO.

  6. EMG analysis in 78 cases with motor neuron disease

    Institute of Scientific and Technical Information of China (English)

    Zhang Qiubin

    2000-01-01

    This paper analysed the FMGs of 78 cases with the motor neuron disease(MND). The EMG of all patients showed following characteristics that the average duration of wave prolonged, the average voltage increased and it was found that fibrillation and fasciculatton potentials appeared spontaneously. The fibrillation potential of ENG waa related to course of disease. In the patients whose course of disease was short, the fibri llation potential increased obviously, while in the cases of chronic MND, It usually decreased. The motor nerve conduction velocity of most pa tients (41%) reduced, however, the sensory nerve conduction velocity was normal but two. We reviewed some references about EMG of the motor neuron disease and discussed their characteristics and mechanism

  7. Generalized approach to bilateral control for EMG driven exoskeleton

    Directory of Open Access Journals (Sweden)

    Gradetsky Valery

    2017-01-01

    Full Text Available The paper discusses a generalized approach to bilateral control for EMG driven exoskeleton systems. In this paper we consider a semi-automatic mechatronic system that is controlled via human muscle activity (EMG level. The problem is to understand how the movement of the exoskeleton effects on the control. The considered system can be described in terms of bilateral control. This means the existence of force feedback from the object via the exoskeleton links and drives to operator. The simulation of the considered model was held on the MATLAB Simulink. The mathematical model of the bilateral system with exoskeleton and operator was developed. Transient functions for different dynamic parameters were obtained. It was shown that force feedback is essential for the R&D of such systems.

  8. A comparison of two gluteus maximus EMG maximum voluntary isometric contraction positions

    Directory of Open Access Journals (Sweden)

    Bret Contreras

    2015-09-01

    Full Text Available Background. The purpose of this study was to compare the peak electromyography (EMG of the most commonly-used position in the literature, the prone bent-leg (90° hip extension against manual resistance applied to the distal thigh (PRONE, to a novel position, the standing glute squeeze (SQUEEZE.Methods. Surface EMG electrodes were placed on the upper and lower gluteus maximus of thirteen recreationally active females (age = 28.9 years; height = 164 cm; body mass = 58.2 kg, before three maximum voluntary isometric contraction (MVIC trials for each position were obtained in a randomized, counterbalanced fashion.Results. No statistically significant (p < 0.05 differences were observed between PRONE (upper: 91.94%; lower: 94.52% and SQUEEZE (upper: 92.04%; lower: 85.12% for both the upper and lower gluteus maximus. Neither the PRONE nor SQUEEZE was more effective between all subjects.Conclusions. In agreement with other studies, no single testing position is ideal for every participant. Therefore, it is recommended that investigators employ multiple MVIC positions, when possible, to ensure accuracy. Future research should investigate a variety of gluteus maximus MVIC positions in heterogeneous samples.

  9. EMG and tibial shock upon the first attempt at barefoot running.

    Science.gov (United States)

    Olin, Evan D; Gutierrez, Gregory M

    2013-04-01

    As a potential means to decrease their risk of injury, many runners are transitioning into barefoot running. Habitually shod runners tend to heel-strike (SHS), landing on their heel first, while barefoot runners tend to mid-foot or toe-strike (BTS), landing flat-footed or on the ball of their foot before bringing down the rest of the foot including the heel. This study compared muscle activity, tibial shock, and knee flexion angle in subjects between shod and barefoot conditions. Eighteen habitually SHS recreational runners ran for 3 separate 7-minute trials, including SHS, barefoot heel-strike (BHS), and BTS conditions. EMG, tibial shock, and knee flexion angle were monitored using bipolar surface electrodes, an accelerometer, and an electrogoniometer, respectively. A one-way MANOVA for repeated measures was conducted and several significant changes were noted between SHS and BTS, including significant increases in average EMG of the medial gastrocnemius (p=.05), average and peak tibial shock (pknee flexion angle (pinjurious, these data indicate that habitually SHS runners who choose to transition into a BTS technique must undertake the process cautiously. Copyright © 2012 Elsevier B.V. All rights reserved.

  10. THE EFFECTIVENESS OF EMG BIOFEEDBACK ON HAND FUNCTION IN SUBJECTS WITH STROKE

    Directory of Open Access Journals (Sweden)

    S. Sethana

    2014-10-01

    Full Text Available Introduction: Stroke is an event caused by the interruption of the blood supply to the brain, usually because a blood vessel bursts or blocked by a clot. Biofeedback can be defined as the technique of using equipment usually electronic to reveal to human beings about some of their internal physiological events normal and abnormal in form of auditory and visual signals. Method: The stroke patients diagnosed by neurologist were recruited from physiotherapy department and inpatients from neurology and general wards of SVIMS hospital, Tirupathi Andhra Pradesh. In the present study 30 subjects were randomly assigned to 15 experimental and 15 control groups. The subject was made to sit comfortably and the Surfaces electrodes were placed on Extensor carpi radialis, Extensor digitorum communis muscle belly and for 30minutes patient voluntarily contracts until signals displayed on screen for which visually and auditory cues are given. In control group placebo EMG where machine is turned away & has no cues. Both groups received CONVENTIONAL PHYSIOTHERAPY; for 30 minutes at a Frequency: 1 hour per day for 5days in a week, for 6weeks. Results: There was statistically significant (p<0.05 improvement in both variables from baseline to 6thweek in experimental group compared to control group. Conclusion: Our study demonstrates the potential benefits of EMG BF in improving hand function in subjects with stroke.

  11. An EMG-Controlled Robotic Hand Exoskeleton for Bilateral Rehabilitation.

    Science.gov (United States)

    Leonardis, Daniele; Barsotti, Michele; Loconsole, Claudio; Solazzi, Massimiliano; Troncossi, Marco; Mazzotti, Claudio; Castelli, Vincenzo Parenti; Procopio, Caterina; Lamola, Giuseppe; Chisari, Carmelo; Bergamasco, Massimo; Frisoli, Antonio

    2015-01-01

    This paper presents a novel electromyography (EMG)-driven hand exoskeleton for bilateral rehabilitation of grasping in stroke. The developed hand exoskeleton was designed with two distinctive features: (a) kinematics with intrinsic adaptability to patient's hand size, and (b) free-palm and free-fingertip design, preserving the residual sensory perceptual capability of touch during assistance in grasping of real objects. In the envisaged bilateral training strategy, the patient's non paretic hand acted as guidance for the paretic hand in grasping tasks. Grasping force exerted by the non paretic hand was estimated in real-time from EMG signals, and then replicated as robotic assistance for the paretic hand by means of the hand-exoskeleton. Estimation of the grasping force through EMG allowed to perform rehabilitation exercises with any, non sensorized, graspable objects. This paper presents the system design, development, and experimental evaluation. Experiments were performed within a group of six healthy subjects and two chronic stroke patients, executing robotic-assisted grasping tasks. Results related to performance in estimation and modulation of the robotic assistance, and to the outcomes of the pilot rehabilitation sessions with stroke patients, positively support validity of the proposed approach for application in stroke rehabilitation.

  12. Evaluation of EMG processing techniques using Information Theory.

    Science.gov (United States)

    Farfán, Fernando D; Politti, Julio C; Felice, Carmelo J

    2010-11-12

    Electromyographic signals can be used in biomedical engineering and/or rehabilitation field, as potential sources of control for prosthetics and orthotics. In such applications, digital processing techniques are necessary to follow efficient and effectively the changes in the physiological characteristics produced by a muscular contraction. In this paper, two methods based on information theory are proposed to evaluate the processing techniques. These methods determine the amount of information that a processing technique is able to extract from EMG signals. The processing techniques evaluated with these methods were: absolute mean value (AMV), RMS values, variance values (VAR) and difference absolute mean value (DAMV). EMG signals from the middle deltoid during abduction and adduction movement of the arm in the scapular plane was registered, for static and dynamic contractions. The optimal window length (segmentation), abduction and adduction movements and inter-electrode distance were also analyzed. Using the optimal segmentation (200 ms and 300 ms in static and dynamic contractions, respectively) the best processing techniques were: RMS, AMV and VAR in static contractions, and only the RMS in dynamic contractions. Using the RMS of EMG signal, variations in the amount of information between the abduction and adduction movements were observed. Although the evaluation methods proposed here were applied to standard processing techniques, these methods can also be considered as alternatives tools to evaluate new processing techniques in different areas of electrophysiology.

  13. Evaluation of EMG processing techniques using Information Theory

    Directory of Open Access Journals (Sweden)

    Felice Carmelo J

    2010-11-01

    Full Text Available Abstract Background Electromyographic signals can be used in biomedical engineering and/or rehabilitation field, as potential sources of control for prosthetics and orthotics. In such applications, digital processing techniques are necessary to follow efficient and effectively the changes in the physiological characteristics produced by a muscular contraction. In this paper, two methods based on information theory are proposed to evaluate the processing techniques. Methods These methods determine the amount of information that a processing technique is able to extract from EMG signals. The processing techniques evaluated with these methods were: absolute mean value (AMV, RMS values, variance values (VAR and difference absolute mean value (DAMV. EMG signals from the middle deltoid during abduction and adduction movement of the arm in the scapular plane was registered, for static and dynamic contractions. The optimal window length (segmentation, abduction and adduction movements and inter-electrode distance were also analyzed. Results Using the optimal segmentation (200 ms and 300 ms in static and dynamic contractions, respectively the best processing techniques were: RMS, AMV and VAR in static contractions, and only the RMS in dynamic contractions. Using the RMS of EMG signal, variations in the amount of information between the abduction and adduction movements were observed. Conclusions Although the evaluation methods proposed here were applied to standard processing techniques, these methods can also be considered as alternatives tools to evaluate new processing techniques in different areas of electrophysiology.

  14. Comparison between sEMG and force as control interfaces to support planar arm movements in adults with Duchenne: a feasibility study.

    Science.gov (United States)

    Lobo-Prat, Joan; Nizamis, Kostas; Janssen, Mariska M H P; Keemink, Arvid Q L; Veltink, Peter H; Koopman, Bart F J M; Stienen, Arno H A

    2017-07-12

    Adults with Duchenne muscular dystrophy (DMD) can benefit from devices that actively support their arm function. A critical component of such devices is the control interface as it is responsible for the human-machine interaction. Our previous work indicated that surface electromyography (sEMG) and force-based control with active gravity and joint-stiffness compensation were feasible solutions for the support of elbow movements (one degree of freedom). In this paper, we extend the evaluation of sEMG- and force-based control interfaces to simultaneous and proportional control of planar arm movements (two degrees of freedom). Three men with DMD (18-23 years-old) with different levels of arm function (i.e. Brooke scores of 4, 5 and 6) performed a series of line-tracing tasks over a tabletop surface using an experimental active arm support. The arm movements were controlled using three control methods: sEMG-based control, force-based control with stiffness compensation (FSC), and force-based control with no compensation (FNC). The movement performance was evaluated in terms of percentage of task completion, tracing error, smoothness and speed. For subject S1 (Brooke 4) FNC was the preferred method and performed better than FSC and sEMG. FNC was not usable for subject S2 (Brooke 5) and S3 (Brooke 6). Subject S2 presented significantly lower movement speed with sEMG than with FSC, yet he preferred sEMG since FSC was perceived to be too fatiguing. Subject S3 could not successfully use neither of the two force-based control methods, while with sEMG he could reach almost his entire workspace. Movement performance and subjective preference of the three control methods differed with the level of arm function of the participants. Our results indicate that all three control methods have to be considered in real applications, as they present complementary advantages and disadvantages. The fact that the two weaker subjects (S2 and S3) experienced the force-based control

  15. Extraction and Analysis of Mega Cities’ Impervious Surface on Pixel-based and Object-oriented Support Vector Machine Classification Technology: A case of Bombay

    Science.gov (United States)

    Yu, S. S.; Sun, Z. C.; Sun, L.; Wu, M. F.

    2017-02-01

    The object of this paper is to study the impervious surface extraction method using remote sensing imagery and monitor the spatiotemporal changing patterns of mega cities. Megacity Bombay was selected as the interesting area. Firstly, the pixel-based and object-oriented support vector machine (SVM) classification methods were used to acquire the land use/land cover (LULC) products of Bombay in 2010. Consequently, the overall accuracy (OA) and overall Kappa (OK) of the pixel-based method were 94.97% and 0.96 with a running time of 78 minutes, the OA and OK of the object-oriented method were 93.72% and 0.94 with a running time of only 17s. Additionally, OA and OK of the object-oriented method after a post-classification were improved up to 95.8% and 0.94. Then, the dynamic impervious surfaces of Bombay in the period 1973-2015 were extracted and the urbanization pattern of Bombay was analysed. Results told that both the two SVM classification methods could accomplish the impervious surface extraction, but the object-oriented method should be a better choice. Urbanization of Bombay experienced a fast extending during the past 42 years, implying a dramatically urban sprawl of mega cities in the developing countries along the One Belt and One Road (OBOR).

  16. Multichannel noninvasive human-machine interface via stretchable µm thick sEMG patches for robot manipulation

    Science.gov (United States)

    Zhou, Ying; Wang, Youhua; Liu, Runfeng; Xiao, Lin; Zhang, Qin; Huang, YongAn

    2018-01-01

    Epidermal electronics (e-skin) emerging in recent years offer the opportunity to noninvasively and wearably extract biosignals from human bodies. The conventional processes of e-skin based on standard microelectronic fabrication processes and a variety of transfer printing methods, nevertheless, unquestionably constrains the size of the devices, posing a serious challenge to collecting signals via skin, the largest organ in the human body. Herein we propose a multichannel noninvasive human-machine interface (HMI) using stretchable surface electromyography (sEMG) patches to realize a robot hand mimicking human gestures. Time-efficient processes are first developed to manufacture µm thick large-scale stretchable devices. With micron thickness, the stretchable µm thick sEMG patches show excellent conformability with human skin and consequently comparable electrical performance with conventional gel electrodes. Combined with the large-scale size, the multichannel noninvasive HMI via stretchable µm thick sEMG patches successfully manipulates the robot hand with eight different gestures, whose precision is as high as conventional gel electrodes array.

  17. Does a SLAP lesion affect shoulder muscle recruitment as measured by EMG activity during a rugby tackle?

    Directory of Open Access Journals (Sweden)

    Herrington Lee C

    2010-02-01

    Full Text Available Abstract Background The study objective was to assess the influence of a SLAP lesion on onset of EMG activity in shoulder muscles during a front on rugby football tackle within professional rugby players. Methods Mixed cross-sectional study evaluating between and within group differences in EMG onset times. Testing was carried out within the physiotherapy department of a university sports medicine clinic. The test group consisted of 7 players with clinically diagnosed SLAP lesions, later verified on arthroscopy. The reference group consisted of 15 uninjured and full time professional rugby players from within the same playing squad. Controlled tackles were performed against a tackle dummy. Onset of EMG activity was assessed from surface EMG of Pectorialis Major, Biceps Brachii, Latissimus Dorsi, Serratus Anterior and Infraspinatus muscles relative to time of impact. Analysis of differences in activation timing between muscles and limbs (injured versus non-injured side and non injured side versus matched reference group. Results Serratus Anterior was activated prior to all other muscles in all (P = 0.001-0.03 subjects. In the SLAP injured shoulder Biceps was activated later than in the non-injured side. Onset times of all muscles of the non-injured shoulder in the injured player were consistently earlier compared with the reference group. Whereas, within the injured shoulder, all muscle activation timings were later than in the reference group. Conclusions This study shows that in shoulders with a SLAP lesion there is a trend towards delay in activation time of Biceps and other muscles with the exception of an associated earlier onset of activation of Serratus anterior, possibly due to a coping strategy to protect glenohumeral stability and thoraco-scapular stability. This trend was not statistically significant in all cases

  18. Does a SLAP lesion affect shoulder muscle recruitment as measured by EMG activity during a rugby tackle?

    Science.gov (United States)

    Horsley, Ian G; Herrington, Lee C; Rolf, Christer

    2010-02-25

    The study objective was to assess the influence of a SLAP lesion on onset of EMG activity in shoulder muscles during a front on rugby football tackle within professional rugby players. Mixed cross-sectional study evaluating between and within group differences in EMG onset times. Testing was carried out within the physiotherapy department of a university sports medicine clinic. The test group consisted of 7 players with clinically diagnosed SLAP lesions, later verified on arthroscopy. The reference group consisted of 15 uninjured and full time professional rugby players from within the same playing squad. Controlled tackles were performed against a tackle dummy. Onset of EMG activity was assessed from surface EMG of Pectorialis Major, Biceps Brachii, Latissimus Dorsi, Serratus Anterior and Infraspinatus muscles relative to time of impact. Analysis of differences in activation timing between muscles and limbs (injured versus non-injured side and non injured side versus matched reference group). Serratus Anterior was activated prior to all other muscles in all (P = 0.001-0.03) subjects. In the SLAP injured shoulder Biceps was activated later than in the non-injured side. Onset times of all muscles of the non-injured shoulder in the injured player were consistently earlier compared with the reference group. Whereas, within the injured shoulder, all muscle activation timings were later than in the reference group. This study shows that in shoulders with a SLAP lesion there is a trend towards delay in activation time of Biceps and other muscles with the exception of an associated earlier onset of activation of Serratus anterior, possibly due to a coping strategy to protect glenohumeral stability and thoraco-scapular stability. This trend was not statistically significant in all cases.

  19. An evaluation of the utility and limitations of counting motor unit action potentials in the surface electromyogram

    Science.gov (United States)

    Zhou, Ping; Zev Rymer, William

    2004-12-01

    The number of motor unit action potentials (MUAPs) appearing in the surface electromyogram (EMG) signal is directly related to motor unit recruitment and firing rates and therefore offers potentially valuable information about the level of activation of the motoneuron pool. In this paper, based on morphological features of the surface MUAPs, we try to estimate the number of MUAPs present in the surface EMG by counting the negative peaks in the signal. Several signal processing procedures are applied to the surface EMG to facilitate this peak counting process. The MUAP number estimation performance by this approach is first illustrated using the surface EMG simulations. Then, by evaluating the peak counting results from the EMG records detected by a very selective surface electrode, at different contraction levels of the first dorsal interosseous (FDI) muscles, the utility and limitations of such direct peak counts for MUAP number estimation in surface EMG are further explored.

  20. Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.

    Science.gov (United States)

    Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

    2016-04-01

    The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control)-an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees. Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts' law task and was compared to performance of eight subjects using parallel dual-site control. An offline analysis also evaluated how different types of training data affected prediction accuracy of linear regression control. The two control systems demonstrated similar overall performance; however, the linear regression method demonstrated improved performance for targets requiring use of all three DOFs, whereas parallel dual-site control demonstrated improved performance for targets that required use of only one DOF. Subjects using linear regression control could more easily activate multiple DOFs simultaneously, but often experienced unintended movements when trying to isolate individual DOFs. Offline analyses also suggested that the method used to train linear regression systems may influence controllability. Linear regression myoelectric control using intramuscular EMG provided an alternative to parallel dual-site control for 3-DOF simultaneous control at the wrist and hand. The two methods demonstrated different strengths in controllability, highlighting the tradeoff between providing simultaneous control and the ability to isolate individual DOFs when desired.

  1. Masticatory Muscle Sleep Background EMG Activity is Elevated in Myofascial TMD Patients

    Science.gov (United States)

    Raphael, Karen G.; Janal, Malvin N.; Sirois, David A.; Dubrovsky, Boris; Wigren, Pia E.; Klausner, Jack J.; Krieger, Ana C.; Lavigne, Gilles J.

    2013-01-01

    Despite theoretical speculation and strong clinical belief, recent research using laboratory polysomnographic (PSG) recording has provided new evidence that frequency of sleep bruxism (SB) masseter muscle events, including grinding or clenching of the teeth during sleep, is not increased for women with chronic myofascial temporomandibular disorder (TMD). The current case-control study compares a large sample of women suffering from chronic myofascial TMD (n=124) with a demographically matched control group without TMD (n=46) on sleep background electromyography (EMG) during a laboratory PSG study. Background EMG activity was measured as EMG root mean square (RMS) from the right masseter muscle after lights out. Sleep background EMG activity was defined as EMG RMS remaining after activity attributable to SB, other orofacial activity, other oromotor activity and movement artifacts were removed. Results indicated that median background EMG during these non SB-event periods was significantly higher (pcases exceeding control activity. Moreover, for TMD cases, background EMG was positively associated and SB event-related EMG was negatively associated with pain intensity ratings (0–10 numerical scale) on post sleep waking. These data provide the foundation for a new focus on small, but persistent, elevations in sleep EMG activity over the course of the night as a mechanism of pain induction or maintenance. PMID:24237356

  2. Numerical simulation of explosive magnetic cumulative generator EMG-720

    Energy Technology Data Exchange (ETDEWEB)

    Deryugin, Yu N; Zelenskij, D K; Kazakova, I F; Kargin, V I; Mironychev, P V; Pikar, A S; Popkov, N F; Ryaslov, E A; Ryzhatskova, E G [All-Russian Research Inst. of Experimental Physics, Sarov (Russian Federation)

    1997-12-31

    The paper discusses the methods and results of numerical simulations used in the development of a helical-coaxial explosive magnetic cumulative generator (EMG) with the stator up to 720 mm in diameter. In the process of designing, separate units were numerically modeled, as was the generator operation with a constant inductive-ohmic load. The 2-D processes of the armature acceleration by the explosion products were modeled as well as those of the formation of the sliding high-current contact between the armature and stator`s insulated turns. The problem of the armature integrity in the region of the detonation waves collision was numerically analyzed. 8 figs., 2 refs.

  3. Test of EMG-720 explosive magneto-cumulative generator

    Energy Technology Data Exchange (ETDEWEB)

    Popkov, N F; Pikar, A S; Ryaslov, E A [All-Russian Research Inst. of Experimental Physics, Sarov (Russian Federation); and others

    1997-12-31

    The results of testing of the 30 MJ explosive magnetocumulative generator EMG-720 are reported. This comparatively simple and inexpensive generator is destined for energizing a stationary electro-physical facility placed in a special explosion-protected bunker. The current increase coefficient and the energy increase factor of the generator are as high as 500 and 120, respectively. The generator operating time is 225 s, and its internal operating voltage is higher than 100 kV. (J.U.). 4 figs., 4 refs.

  4. Textile Electrodes Embedded in Clothing: A Practical Alternative to Traditional Surface Electromyography when Assessing Muscle Excitation during Functional Movements

    Directory of Open Access Journals (Sweden)

    Steffi L. Colyer, Polly M. McGuigan

    2018-03-01

    Full Text Available Textile electromyography (EMG electrodes embedded in clothing allow muscle excitation to be recorded in previously inaccessible settings; however, their ability to accurately and reliably measure EMG during dynamic tasks remains largely unexplored. To quantify the validity and reliability of textile electrodes, 16 recreationally active males completed two identical testing sessions, within which three functional movements (run, cycle and squat were performed twice: once wearing EMG shorts (measuring quadriceps, hamstrings and gluteals myoelectric activity and once with surface EMG electrodes attached to the vastus lateralis, biceps femoris and gluteus maximus. EMG signals were identically processed to provide average rectified EMG (normalized to walking and excitation length. Results were compared across measurement systems and demonstrated good agreement between the magnitude of muscle excitation when EMG activity was lower, but agreement was poorer when excitation was higher. The length of excitation bursts was consistently longer when measured using textile vs. surface EMG electrodes. Comparable between-session (day-to-day repeatability was found for average rectified EMG (mean coefficient of variation, CV: 42.6 and 41.2% and excitation length (CV: 12.9 and 9.8% when using textile and surface EMG, respectively. Additionally, similar within-session repeatability (CV was recorded for average rectified EMG (13.8 and 14.1% and excitation length (13.0 and 12.7% for textile and surface electrodes, respectively. Generally, textile EMG electrodes appear to be capable of providing comparable muscle excitation information and reproducibility to surface EMG during dynamic tasks. Textile EMG shorts could therefore be a practical alternative to traditional laboratory-based methods allowing muscle excitation information to be collected in more externally-valid training environments.

  5. Acute Warm-up Effects in Submaximal Athletes: An EMG Study of Skilled Violinists.

    Science.gov (United States)

    McCrary, J Matt; Halaki, Mark; Sorkin, Evgeny; Ackermann, Bronwen J

    2016-02-01

    Warm-up is commonly recommended for injury prevention and performance enhancement across all activities, yet this recommendation is not supported by evidence for repetitive submaximal activities such as instrumental music performance. The objective of this study is to quantify the effects of cardiovascular, core muscle, and musical warm-ups on muscle activity levels, musical performance, and subjective experience in skilled violinists. Fifty-five undergraduate, postgraduate, or professional violinists performed five randomly ordered 45-s musical excerpts of varying physical demands both before and after a randomly assigned 15-min, moderate-intensity cardiovascular, core muscle, musical (technical violin exercises), or inactive control warm-up protocol. Surface EMG data were obtained for 16 muscles of the trunk, shoulders, and right arm during each musical performance. Sound recording and perceived exertion (RPE) data were also obtained. Sound recordings were randomly ordered and rated for performance quality by blinded adjudicators. Questionnaire data regarding participant pain sites and fitness levels were used to stratify participants according to pain and fitness levels. Data were analyzed using two- and three-factor ANCOVA (surface EMG and sound recording) and Wilcoxon matched pairs tests (RPE). None of the three warm-up protocols had significant effects on muscle activity levels (P ≥ 0.10). Performance quality did not significantly increase (P ≥ 0.21). RPE significantly decreased (P warm-up for each of the three experimental warm-ups; control condition RPE did not significantly decrease (P > 0.23). Acute physiological and musical benefits from cardiovascular, core muscle, and musical warm-ups in skilled violinists are limited to decreases in RPE. This investigation provides data from the performing arts in support of sports medical evidence suggesting that warm-up only effectively enhances maximal strength and power performance.

  6. Classifying Classifications

    DEFF Research Database (Denmark)

    Debus, Michael S.

    2017-01-01

    This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

  7. Large Scale Automatic Analysis and Classification of Roof Surfaces for the Installation of Solar Panels Using a Multi-Sensor Aerial Platform

    Directory of Open Access Journals (Sweden)

    Luis López-Fernández

    2015-09-01

    Full Text Available A low-cost multi-sensor aerial platform, aerial trike, equipped with visible and thermographic sensors is used for the acquisition of all the data needed for the automatic analysis and classification of roof surfaces regarding their suitability to harbor solar panels. The geometry of a georeferenced 3D point cloud generated from visible images using photogrammetric and computer vision algorithms, and the temperatures measured on thermographic images are decisive to evaluate the areas, tilts, orientations and the existence of obstacles to locate the optimal zones inside each roof surface for the installation of solar panels. This information is complemented with the estimation of the solar irradiation received by each surface. This way, large areas may be efficiently analyzed obtaining as final result the optimal locations for the placement of solar panels as well as the information necessary (location, orientation, tilt, area and solar irradiation to estimate the productivity of a solar panel from its technical characteristics.

  8. Locomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton

    Science.gov (United States)

    Kinnaird, Catherine R.; Ferris, Daniel P.

    2013-01-01

    Locomotor adaptation in humans is not well understood. To provide insight into the neural reorganization that occurs following a significant disruption to one's learned neuromuscular map relating a given motor command to its resulting muscular action, we tied the mechanical action of a robotic exoskeleton to the electromyography (EMG) profile of the soleus muscle during walking. The powered exoskeleton produced an ankle dorsiflexion torque proportional to soleus muscle recruitment thus limiting the soleus' plantar flexion torque capability. We hypothesized that neurologically intact subjects would alter muscle activation patterns in response to the antagonistic exoskeleton by decreasing soleus recruitment. Subjects practiced walking with the exoskeleton for two 30-min sessions. The initial response to the perturbation was to “fight” the resistive exoskeleton by increasing soleus activation. By the end of training, subjects had significantly reduced soleus recruitment resulting in a gait pattern with almost no ankle push-off. In addition, there was a trend for subjects to reduce gastrocnemius recruitment in proportion to the soleus even though only the soleus EMG was used to control the exoskeleton. The results from this study demonstrate the ability of the nervous system to recalibrate locomotor output in response to substantial changes in the mechanical output of the soleus muscle and associated sensory feedback. This study provides further evidence that the human locomotor system of intact individuals is highly flexible and able to adapt to achieve effective locomotion in response to a broad range of neuromuscular perturbations. PMID:23307949

  9. Locomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton.

    Science.gov (United States)

    Gordon, Keith E; Kinnaird, Catherine R; Ferris, Daniel P

    2013-04-01

    Locomotor adaptation in humans is not well understood. To provide insight into the neural reorganization that occurs following a significant disruption to one's learned neuromuscular map relating a given motor command to its resulting muscular action, we tied the mechanical action of a robotic exoskeleton to the electromyography (EMG) profile of the soleus muscle during walking. The powered exoskeleton produced an ankle dorsiflexion torque proportional to soleus muscle recruitment thus limiting the soleus' plantar flexion torque capability. We hypothesized that neurologically intact subjects would alter muscle activation patterns in response to the antagonistic exoskeleton by decreasing soleus recruitment. Subjects practiced walking with the exoskeleton for two 30-min sessions. The initial response to the perturbation was to "fight" the resistive exoskeleton by increasing soleus activation. By the end of training, subjects had significantly reduced soleus recruitment resulting in a gait pattern with almost no ankle push-off. In addition, there was a trend for subjects to reduce gastrocnemius recruitment in proportion to the soleus even though only the soleus EMG was used to control the exoskeleton. The results from this study demonstrate the ability of the nervous system to recalibrate locomotor output in response to substantial changes in the mechanical output of the soleus muscle and associated sensory feedback. This study provides further evidence that the human locomotor system of intact individuals is highly flexible and able to adapt to achieve effective locomotion in response to a broad range of neuromuscular perturbations.

  10. Grid investments in a Nordic perspective. Report to EMG

    Energy Technology Data Exchange (ETDEWEB)

    2010-05-15

    In a letter of 20 November 2008, the Electricity Market Group (EMG) under the Nordic Council of Ministers requested NordREG to carry out an assignment related to transmission network investments in the Nordic countries. The assignment to NordREG was divided into two tasks; to map the differences in the legislation and licensing processes in the Nordic countries and to analyse these differences and possible ways of financing common network investment projects. In the second half of 2009 the consultant Econ Poeyry was engaged to support in the finalisation of this project, mainly concerning possibilities for Nordic financing. The final text is however the sole responsibility of the task force. A draft version of the final report was delivered to EMG in December 2009. At the same time the report was sent to the Nordic TSOs together with an invitation to a workshop at Gardermoen on 26 January 2010. The comments from the TSOs are included in appendix 2 of the report

  11. Intention detection of gait initiation using EMG and kinematic data.

    Science.gov (United States)

    Wentink, E C; Beijen, S I; Hermens, H J; Rietman, J S; Veltink, P H

    2013-02-01

    Gait initiation in transfemoral amputees (TFA) is different from non-amputees. This is mainly caused by the lack of stability and push-off from the prosthetic leg. Adding control and artificial push-off to the prosthesis may therefore be beneficial to TFA. In this study the feasibility of real-time intention detection of gait initiation was determined by mimicking the TFA situation in non-amputees. EMG and inertial sensor data was measured in 10 non-amputees. Only data available in TFA was used to determine if gait initiation can be predicted in time to control a transfemoral prosthesis to generate push-off and stability. Toe-off and heel-strike of the leading limb are important parameters to be detected, to control a prosthesis and to time push-off. The results show that toe-off and heel-strike of the leading limb can be detected using EMG and kinematic data in non-amputees 130-260 ms in advance. This leaves enough time to control a prosthesis. Based on these results we hypothesize that similar results can be found in TFA, allowing for adequate control of a prosthesis during gait initiation. Copyright © 2012 Elsevier B.V. All rights reserved.

  12. Ventilatory threshold during incremental running can be estimated using EMG shorts

    International Nuclear Information System (INIS)

    Tikkanen, Olli; Vilavuo, Toivo; Finni, Taija; Hu, Min; Cheng, Sulin; Tolvanen, Pekka

    2012-01-01

    The present study examined whether shorts with textile electromyographic (EMG) electrodes can be used to detect second ventilatory threshold (V T2 ) during incremental treadmill running. Thirteen recreationally active (REC) and eight endurance athletes were measured for EMG, heart rate, blood lactate and respiratory gases during VO 2max test (3 min ramps, 1 km ⋅ h −1 increments). V T2 , onset of blood lactate accumulation (OBLA) and EMG threshold (EMG T ) were determined. In athletes, OBLA occurred at 56 ± 6 mL ⋅ kg −1  ⋅ min −1 , V T2 occurred at 59 ± 6 mL ⋅ kg −1  ⋅ min −1 , and EMG T at 62 ± 6 mL ⋅ kg −1  ⋅ min −1 without significant differences between methods (analysis of variance: ANOVA). In REC participants, OBLA occurred at 40 ± 10 mL ⋅ kg −1  ⋅ min −1 , V T2 occurred at 43 ± 7 mL ⋅ kg −1  ⋅ min −1 , and EMG T at 41 ± 9 mL ⋅ kg −1  ⋅ min −1 without significant differences between methods (ANOVA). For the entire group, correlation between EMG T and V T2 was 0.86 (P < 0.001) and 0.84 (P < 0.001) between EMG T and OBLA. Limits of agreement between EMG T and V T2 were narrower in athletes than in REC participants. Thus, it is concluded that estimation of V T2 using EMG T in athletes is more valid than in REC participants. In practice, experienced runners could use online feedback from EMG garments to monitor whether their running intensity is near V T2 . (paper)

  13. Ventilatory threshold during incremental running can be estimated using EMG shorts.

    Science.gov (United States)

    Tikkanen, Olli; Hu, Min; Vilavuo, Toivo; Tolvanen, Pekka; Cheng, Sulin; Finni, Taija

    2012-04-01

    The present study examined whether shorts with textile electromyographic (EMG) electrodes can be used to detect second ventilatory threshold (V(T2)) during incremental treadmill running. Thirteen recreationally active (REC) and eight endurance athletes were measured for EMG, heart rate, blood lactate and respiratory gases during VO(2max) test (3 min ramps, 1 km·h(-1) increments). V(T)(2), onset of blood lactate accumulation (OBLA) and EMG threshold (EMG(T)) were determined. In athletes, OBLA occurred at 56 ± 6 mL·kg(-1)·min(-1), V(T2) occurred at 59 ± 6 mL·kg(-1)·min(-1), and EMG(T) at 62 ± 6 mL·kg(-1)·min(-1) without significant differences between methods (analysis of variance: ANOVA). In REC participants, OBLA occurred at 40 ± 10 mL·kg(-1)·min(-1), V(T2) occurred at 43 ± 7 mL·kg(-1)·min(-1), and EMG(T) at 41 ± 9 mL·kg(-1)·min(-1) without significant differences between methods (ANOVA). For the entire group, correlation between EMG(T) and V(T2) was 0.86 (P < 0.001) and 0.84 (P < 0.001) between EMG(T) and OBLA. Limits of agreement between EMG(T) and V(T2) were narrower in athletes than in REC participants. Thus, it is concluded that estimation of V(T2) using EMG(T) in athletes is more valid than in REC participants. In practice, experienced runners could use online feedback from EMG garments to monitor whether their running intensity is near V(T2). © 2012 Institute of Physics and Engineering in Medicine

  14. Recursive automatic classification algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Bauman, E V; Dorofeyuk, A A

    1982-03-01

    A variational statement of the automatic classification problem is given. The dependence of the form of the optimal partition surface on the form of the classification objective functional is investigated. A recursive algorithm is proposed for maximising a functional of reasonably general form. The convergence problem is analysed in connection with the proposed algorithm. 8 references.

  15. Physiological modules for generating discrete and rhythmic movements: component analysis of EMG signals.

    Science.gov (United States)

    Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana Maria; Dan, Bernard; Cheron, Guy; McIntyre, Joseph

    2014-01-01

    A central question in Neuroscience is that of how the nervous system generates the spatiotemporal commands needed to realize complex gestures, such as handwriting. A key postulate is that the central nervous system (CNS) builds up complex movements from a set of simpler motor primitives or control modules. In this study we examined the control modules underlying the generation of muscle activations when performing different types of movement: discrete, point-to-point movements in eight different directions and continuous figure-eight movements in both the normal, upright orientation and rotated 90°. To test for the effects of biomechanical constraints, movements were performed in the frontal-parallel or sagittal planes, corresponding to two different nominal flexion/abduction postures of the shoulder. In all cases we measured limb kinematics and surface electromyographic activity (EMG) signals for seven different muscles acting around the shoulder. We first performed principal component analysis (PCA) of the EMG signals on a movement-by-movement basis. We found a surprisingly consistent pattern of muscle groupings across movement types and movement planes, although we could detect systematic differences between the PCs derived from movements performed in each shoulder posture and between the principal components associated with the different orientations of the figure. Unexpectedly we found no systematic differences between the figure eights and the point-to-point movements. The first three principal components could be associated with a general co-contraction of all seven muscles plus two patterns of reciprocal activation. From these results, we surmise that both "discrete-rhythmic movements" such as the figure eight, and discrete point-to-point movement may be constructed from three different fundamental modules, one regulating the impedance of the limb over the time span of the movement and two others operating to generate movement, one aligned with the

  16. EMG and oxygen uptake responses during slow and fast ramp exercise in humans.

    Science.gov (United States)

    Scheuermann, Barry W; Tripse McConnell, Joyce H; Barstow, Thomas J

    2002-01-01

    This study examined the relationship between muscle recruitment patterns using surface electromyography (EMG) and the excess O(2) uptake (Ex.V(O(2))) that accompanies slow (SR, 8 W min(-1)) but not fast (FR, 64 W min(-1)) ramp increases in work rate (WR) during exercise on a cycle ergometer. Nine subjects (2 females) participated in this study (25 +/- 2 years, +/- S.E.M.). EMG was obtained from the vastus lateralis and medialis and analysed in the time (root mean square, RMS) and frequency (median power frequency, MDPF) domain. Results for each muscle were averaged to provide an overall response and expressed relative to a maximal voluntary contraction (%MVC). Delta.V(O(2))/DeltaWR was calculated for exercise below (S(1)) and above (S(2)) the lactate threshold (LT) using linear regression. The increase in RMS relative to the increase in WR for exercise below the LT (DeltaRMS/DeltaWR-S(1)) was determined using linear regression. Due to non-linearities in RMS above the LT, DeltaRMS/DeltaWR-S(2) is reported as the difference in RMS (DeltaRMS) and the difference in WR (DeltaWR) at end-exercise and the LT. SR was associated with a higher (P exercise is not associated with the recruitment of additional motor units since Ex.V(O(2)) was observed during SR only. Compared to the progressive decrease in MDPF observed during FR, the MDPF remained relatively constant during SR suggesting that either (i) there was no appreciable recruitment of the less efficient type II muscle fibres, at least in addition to those recruited initially at the onset of exercise, or (ii) the decrease in MDPF associated with fatigue was offset by the addition of a higher frequency of type II fibres recruited to replace the fatigued motor units.

  17. TIME-OF-DAY EFFECTS ON EMG PARAMETERS DURING THE WINGATE TEST IN BOYS

    Directory of Open Access Journals (Sweden)

    Hichem Souissi

    2012-09-01

    Full Text Available In boys, muscle power and strength fluctuate with time-of-day with morning nadirs and afternoon maximum values. However, the exact underlying mechanisms of this daily variation are not studied yet. Thus, the purpose of this study was to examine the time-of-day effects on electromyographic (EMG parameters changes during a Wingate test in boys. Twenty-two boys performed a 30-s Wingate test (measurement of muscle power and fatigue at 07:00 and 17:00-h on separate days. Surface EMG activity was recorded in the Vastus lateralis, rectus femoris and vastus medialis muscles throughout the test and analyzed over a 5-s span. The root-mean-square (RMS and mean-power-frequency (MPF were calculated. Neuromuscular efficiency (NME was estimated from the ratio of power to RMS. Muscle power (8.22 ± 0.92 vs. 8.75 ± 0.99 W·kg-1 for peak power and 6.96 ± 0. 72 vs. 7.31 ± 0.77 W·kg-1 for mean power, p < 0.001 and fatigue (30.27 ± 7.98 vs. 34.5 ± 10. 15 %, p < 0.05 during the Wingate test increased significantly from morning to evening. Likewise, MPF (102.14 ± 18.15 vs. 92.38 ± 12.39 Hz during the first 5-s, p < 0.001 and NME (4.78 ± 1.7 vs. 3.88 ± 0.79 W·mV-1 during the first 5-s, p < 0.001 were higher in the evening than the morning; but no significant time-of-day effect was noticed for RMS. Taken together, these results suggest that peripheral mechanisms are more likely the cause of the child's diurnal variations of muscle power and fatigue during the Wingate test

  18. An open and configurable embedded system for EMG pattern recognition implementation for artificial arms.

    Science.gov (United States)

    Jun Liu; Fan Zhang; Huang, He Helen

    2014-01-01

    Pattern recognition (PR) based on electromyographic (EMG) signals has been developed for multifunctional artificial arms for decades. However, assessment of EMG PR control for daily prosthesis use is still limited. One of the major barriers is the lack of a portable and configurable embedded system to implement the EMG PR control. This paper aimed to design an open and configurable embedded system for EMG PR implementation so that researchers can easily modify and optimize the control algorithms upon our designed platform and test the EMG PR control outside of the lab environments. The open platform was built on an open source embedded Linux Operating System running a high-performance Gumstix board. Both the hardware and software system framework were openly designed. The system was highly flexible in terms of number of inputs/outputs and calibration interfaces used. Such flexibility enabled easy integration of our embedded system with different types of commercialized or prototypic artificial arms. Thus far, our system was portable for take-home use. Additionally, compared with previously reported embedded systems for EMG PR implementation, our system demonstrated improved processing efficiency and high system precision. Our long-term goals are (1) to develop a wearable and practical EMG PR-based control for multifunctional artificial arms, and (2) to quantify the benefits of EMG PR-based control over conventional myoelectric prosthesis control in a home setting.

  19. Intelligent Noise Removal from EMG Signal Using Focused Time-Lagged Recurrent Neural Network

    Directory of Open Access Journals (Sweden)

    S. N. Kale

    2009-01-01

    Full Text Available Electromyography (EMG signals can be used for clinical/biomedical application and modern human computer interaction. EMG signals acquire noise while traveling through tissue, inherent noise in electronics equipment, ambient noise, and so forth. ANN approach is studied for reduction of noise in EMG signal. In this paper, it is shown that Focused Time-Lagged Recurrent Neural Network (FTLRNN can elegantly solve to reduce the noise from EMG signal. After rigorous computer simulations, authors developed an optimal FTLRNN model, which removes the noise from the EMG signal. Results show that the proposed optimal FTLRNN model has an MSE (Mean Square Error as low as 0.000067 and 0.000048, correlation coefficient as high as 0.99950 and 0.99939 for noise signal and EMG signal, respectively, when validated on the test dataset. It is also noticed that the output of the estimated FTLRNN model closely follows the real one. This network is indeed robust as EMG signal tolerates the noise variance from 0.1 to 0.4 for uniform noise and 0.30 for Gaussian noise. It is clear that the training of the network is independent of specific partitioning of dataset. It is seen that the performance of the proposed FTLRNN model clearly outperforms the best Multilayer perceptron (MLP and Radial Basis Function NN (RBF models. The simple NN model such as the FTLRNN with single-hidden layer can be employed to remove noise from EMG signal.

  20. Origin of the low-level EMG during the silent period following transcranial magnetic stimulation

    DEFF Research Database (Denmark)

    Butler, Jane E; Petersen, Nicolas C; Herbert, Robert D

    2012-01-01

    OBJECTIVE: The cortical silent period refers to a period of near silence in the electromyogram (EMG) after transcranial magnetic stimulation (TMS) of the motor cortex during contraction. However, low-level EMG of unknown origin is often present. We hypothesised that it arises through spinal...

  1. Effect of a pelvic belt on EMG activity during manual load lifting

    Directory of Open Access Journals (Sweden)

    Marcelo Pinto Pereira

    2009-04-01

    Full Text Available Manual lifting (ML capacity is still a matter of concern for industry administrators and electromyography (EMG seems to be a good alternative for the evaluation of muscles involved in this task. However, the reliability of these measures is very important. Thus, the objective of this study was to evaluate the influence of a pelvic belt on EMG activity of the erector spinus (ES and rectus femoralis (RF muscles during ML and during maximal voluntary contractions (MVC of trunk extension performed before (baseline and after ML. In addition, the variabilityin the EMG signal normalized by the following three different methods was evaluated: peak EMG activity, mean EMG activity, and EMG activity obtained during MVC. Eight volunteers performed ML of 15% and 25% of their body weight for 1 minute in the presence or absence of a pelvic belt. The coefficient of variation (CV of the EMG signal obtained for the ES and RF muscles was calculated during ML. Load cell traction values and the electromyographic variables RMS, median frequency, mean power frequency and total power of the ES muscle were obtained during MVC. The results showed lower CV (smaller variability when the EMG signal was normalized by peak activity, with this method thus being preferable. During MVC, only the load cell traction value differed from baseline after ML of 25% body weight without the pelvic belt (p=0.035, a finding suggesting rapid recovery of ES muscle after ML for 1 minute.

  2. Advanced biofeedback from surface electromyography signals using fuzzy system

    DEFF Research Database (Denmark)

    Samani, Afshin; Holtermann, Andreas; Søgaard, Karen

    2010-01-01

    The aims of this study were to develop a fuzzy inference-based biofeedback system and investigate its effects when inducing active (shoulder elevation) and passive (relax) pauses on the trapezius muscle electromyographic (EMG) activity during computer work. Surface EMG signals were recorded from...

  3. Prediction of isometric motor tasks and effort levels based on high-density EMG in patients with incomplete spinal cord injury

    Science.gov (United States)

    Jordanić, Mislav; Rojas-Martínez, Mónica; Mañanas, Miguel Angel; Francesc Alonso, Joan

    2016-08-01

    Objective. The development of modern assistive and rehabilitation devices requires reliable and easy-to-use methods to extract neural information for control of devices. Group-specific pattern recognition identifiers are influenced by inter-subject variability. Based on high-density EMG (HD-EMG) maps, our research group has already shown that inter-subject muscle activation patterns exist in a population of healthy subjects. The aim of this paper is to analyze muscle activation patterns associated with four tasks (flexion/extension of the elbow, and supination/pronation of the forearm) at three different effort levels in a group of patients with incomplete Spinal Cord Injury (iSCI). Approach. Muscle activation patterns were evaluated by the automatic identification of these four isometric tasks along with the identification of levels of voluntary contractions. Two types of classifiers were considered in the identification: linear discriminant analysis and support vector machine. Main results. Results show that performance of classification increases when combining features extracted from intensity and spatial information of HD-EMG maps (accuracy = 97.5%). Moreover, when compared to a population with injuries at different levels, a lower variability between activation maps was obtained within a group of patients with similar injury suggesting stronger task-specific and effort-level-specific co-activation patterns, which enable better prediction results. Significance. Despite the challenge of identifying both the four tasks and the three effort levels in patients with iSCI, promising results were obtained which support the use of HD-EMG features for providing useful information regarding motion and force intention.

  4. Positive fEMG Patterns with Ambiguity in Paintings.

    Science.gov (United States)

    Jakesch, Martina; Goller, Juergen; Leder, Helmut

    2017-01-01

    Whereas ambiguity in everyday life is often negatively evaluated, it is considered key in art appreciation. In a facial EMG study, we tested whether the positive role of visual ambiguity in paintings is reflected in a continuous affective evaluation on a subtle level. We presented ambiguous (disfluent) and non-ambiguous (fluent) versions of Magritte paintings and found that M. Zygomaticus major activation was higher and M. corrugator supercilii activation was lower for ambiguous than for non-ambiguous versions. Our findings reflect a positive continuous affective evaluation to visual ambiguity in paintings over the 5 s presentation time. We claim that this finding is indirect evidence for the hypothesis that visual stimuli classified as art, evoke a safe state for indulging into experiencing ambiguity, challenging the notion that processing fluency is generally related to positive affect.

  5. A novel biometric authentication approach using ECG and EMG signals.

    Science.gov (United States)

    Belgacem, Noureddine; Fournier, Régis; Nait-Ali, Amine; Bereksi-Reguig, Fethi

    2015-05-01

    Security biometrics is a secure alternative to traditional methods of identity verification of individuals, such as authentication systems based on user name and password. Recently, it has been found that the electrocardiogram (ECG) signal formed by five successive waves (P, Q, R, S and T) is unique to each individual. In fact, better than any other biometrics' measures, it delivers proof of subject's being alive as extra information which other biometrics cannot deliver. The main purpose of this work is to present a low-cost method for online acquisition and processing of ECG signals for person authentication and to study the possibility of providing additional information and retrieve personal data from an electrocardiogram signal to yield a reliable decision. This study explores the effectiveness of a novel biometric system resulting from the fusion of information and knowledge provided by ECG and EMG (Electromyogram) physiological recordings. It is shown that biometrics based on these ECG/EMG signals offers a novel way to robustly authenticate subjects. Five ECG databases (MIT-BIH, ST-T, NSR, PTB and ECG-ID) and several ECG signals collected in-house from volunteers were exploited. A palm-based ECG biometric system was developed where the signals are collected from the palm of the subject through a minimally intrusive one-lead ECG set-up. A total of 3750 ECG beats were used in this work. Feature extraction was performed on ECG signals using Fourier descriptors (spectral coefficients). Optimum-Path Forest classifier was used to calculate the degree of similarity between individuals. The obtained results from the proposed approach look promising for individuals' authentication.

  6. To What Extent Is Mean EMG Frequency during Gait a Reflection of Functional Muscle Strength in Children with Cerebral Palsy?

    Science.gov (United States)

    Van Gestel, L.; Wambacq, H.; Aertbelien, E.; Meyns, P.; Bruyninckx, H.; Bar-On, L.; Molenaers, G.; De Cock, P.; Desloovere, K.

    2012-01-01

    The aim of the current paper was to analyze the potential of the mean EMG frequency, recorded during 3D gait analysis (3DGA), for the evaluation of functional muscle strength in children with cerebral palsy (CP). As walking velocity is known to also influence EMG frequency, it was investigated to which extent the mean EMG frequency is a reflection…

  7. Classification of high-resolution multi-swath hyperspectral data using Landsat 8 surface reflectance data as a calibration target and a novel histogram based unsupervised classification technique to determine natural classes from biophysically relevant fit parameters

    Science.gov (United States)

    McCann, C.; Repasky, K. S.; Morin, M.; Lawrence, R. L.; Powell, S. L.

    2016-12-01

    Compact, cost-effective, flight-based hyperspectral imaging systems can provide scientifically relevant data over large areas for a variety of applications such as ecosystem studies, precision agriculture, and land management. To fully realize this capability, unsupervised classification techniques based on radiometrically-calibrated data that cluster based on biophysical similarity rather than simply spectral similarity are needed. An automated technique to produce high-resolution, large-area, radiometrically-calibrated hyperspectral data sets based on the Landsat surface reflectance data product as a calibration target was developed and applied to three subsequent years of data covering approximately 1850 hectares. The radiometrically-calibrated data allows inter-comparison of the temporal series. Advantages of the radiometric calibration technique include the need for minimal site access, no ancillary instrumentation, and automated processing. Fitting the reflectance spectra of each pixel using a set of biophysically relevant basis functions reduces the data from 80 spectral bands to 9 parameters providing noise reduction and data compression. Examination of histograms of these parameters allows for determination of natural splitting into biophysical similar clusters. This method creates clusters that are similar in terms of biophysical parameters, not simply spectral proximity. Furthermore, this method can be applied to other data sets, such as urban scenes, by developing other physically meaningful basis functions. The ability to use hyperspectral imaging for a variety of important applications requires the development of data processing techniques that can be automated. The radiometric-calibration combined with the histogram based unsupervised classification technique presented here provide one potential avenue for managing big-data associated with hyperspectral imaging.

  8. EMG biofeedback training in adult attention-deficit/hyperactivity disorder: An active (control) training?

    Science.gov (United States)

    Barth, Beatrix; Mayer, Kerstin; Strehl, Ute; Fallgatter, Andreas J; Ehlis, Ann-Christine

    2017-06-30

    The present study aimed at revealing neurophysiological effects induced by electromyography (EMG) based biofeedback, considered as a semi-active control condition in neurofeedback studies, in adult attention-deficit/hyperactivity disorder (ADHD) patients. 20 adult ADHD patients trained their muscle activity in the left and right supraspinatus muscle over the course of 30 EMG biofeedback sessions. Changes induced by the EMG feedback were evaluated at a clinical and neurophysiological level; additionally, the relation between changes in EEG activity recorded at the vertex over the training course and changes of symptom severity over the treatment course were assessed in order to investigate the mechanisms underlying clinical effects of EMG biofeedback. Participants showed significant behavioral improvements on a self-rating scale. There was a significant increase in alpha power, but no significant changes in the delta frequency range; changes in the theta and beta frequency range were not significant after adjustment for multiple comparisons. No statistically significant correlation was found between changes in EEG frequency bands and changes in ADHD symptoms. The current results assessed by means of a single-electrode EEG constitute a starting point regarding a clearer understanding of mechanisms underlying clinical effects of EMG biofeedback. Although we did not reveal systematic effects induced by EMG feedback on brain activity it remains an open question whether EMG biofeedback induces changes in brain regions or parameters we did not gather in the present study (e.g. motor cortex). Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Effect of a jig on EMG activity in different orofacial pain conditions.

    Science.gov (United States)

    Bodere, Celine; Woda, Alain

    2008-01-01

    The bite stop (jig) is commonly used in clinical practice. It has been recommended as a simple means to routinely record or provide centric relation closure and, more recently, to reduce migraines and tension-type headaches. However, the reason for the jig effect has yet to be explained. This study tested the hypothesis that it works through a decrease in masticatory muscle activity. The effect of a jig placed on the maxillary anterior teeth was investigated by recording the electromyographic (EMG) activity of the superficial masseter and anterior temporal muscles at postural position and when swallowing on the jig. EMG recordings were obtained from 2 groups of pain patients (myofascial and neuropathic) and from 2 groups of pain-free patients (disc derangement and controls) unaware of the role of dental occlusion treatments. EMG activity in postural position was higher in pain groups than in pain-free groups. The jig strongly but temporarily decreased the postural EMG activity for masseter muscles in all groups except for the neuropathic group and for temporal muscles in the myofascial group. The EMG activity when swallowing with the jig was reduced in control, disc derangement, and myofascial groups; however, EMG "hyperactivity" in the neuropathic pain group seemed to be locked. The decrease of postural EMG activity, especially in the myofascial group, was short lasting and cannot be considered as evidence to support the hypothesis of a long-term muscle relaxation jig effect. However, the results may uphold certain short-term clinical approaches.

  10. The effect of experimental stress and experimental occlusal interference on masseteric EMG activity.

    Science.gov (United States)

    McGlynn, F D; Bichajian, C; Tira, D E; Lundeen, H C; Mahan, P E; Nicholas, B V

    1989-01-01

    This experiment attempted to study the separate and combined effects of occlusal interference and transient stress on masseteric activity among eight nonclinical human subjects. Before each of two sessions, subjects were fitted with an occlusal interference or an occlusally inert (control) molar clasp. During each session they viewed horrific and idyllic videotapes while masseter EMG was recorded bilaterally. Electrodermal measures validated that the horrific videotapes were stressful. Studies showed that the occlusal variable worked less well. The EMG was elevated contralateral to both clasps and during videotape viewing. The EMG effects from videotape viewing were relatively pronounced without the occlusal interference. Research implications are discussed.

  11. Myopathic EMG findings and type II muscle fiber atrophy in patients with Lambert-Eaton myasthenic syndrome

    DEFF Research Database (Denmark)

    Crone, Clarissa; Christiansen, Ingelise; Vissing, John

    2013-01-01

    Lambert-Eaton myasthenic syndrome (LEMS) is a rare condition, which may mimic myopathy. A few reports have described that EMG in LEMS may show changes compatible with myopathy, and muscle biopsies have been described with type II as well as type I atrophy. The EMG results were, however, based on ...... on qualitative EMG examination and the histopathological methods were not always clear. The objective of this study was to investigate if the previous EMG findings could be confirmed with quantitative EMG (QEMG) and to describe muscle histology in LEMS.......Lambert-Eaton myasthenic syndrome (LEMS) is a rare condition, which may mimic myopathy. A few reports have described that EMG in LEMS may show changes compatible with myopathy, and muscle biopsies have been described with type II as well as type I atrophy. The EMG results were, however, based...

  12. The Potential of Using Landsat 7 Data for the Classification of Sea Ice Surface Conditions During Summer

    Science.gov (United States)

    Markus, Thorsten; Cavalieri, Donald J.; Ivanoff, Alvaro; Koblinsky, Chester J. (Technical Monitor)

    2001-01-01

    During spring and summer, the Surface of the Arctic sea ice cover undergoes rapid changes that greatly affect the surface albedo and significantly impact the further decay of the sea ice. These changes are primarily the development of a wet snow cover and the development of melt ponds. As melt pond diameters generally do not exceed a couple of meters, the spatial resolutions of sensors like AVHRR and MODIS are too coarse for their identification. Landsat 7, on the other hand, has a spatial resolution of 30 m (15 m for the pan-chromatic band). The different wavelengths (bands) from blue to near-infrared offer the potential to distinguish among different surface conditions. Landsat 7 data for the Baffin Bay region for June 2000 have been analyzed. The analysis shows that different surface conditions, such as wet snow and meltponded areas, have different signatures in the individual Landsat bands. Consistent with in-situ albedo measurements, melt ponds show up as blueish whereas dry and wet ice have a white to gray appearance in the Landsat true-color image. These spectral differences enable the distinction of melt ponds. The melt pond fraction for the scene studied in this paper was 37%.

  13. Beam-hardening correction by a surface fitting and phase classification by a least square support vector machine approach for tomography images of geological samples

    Science.gov (United States)

    Khan, F.; Enzmann, F.; Kersten, M.

    2015-12-01

    In X-ray computed microtomography (μXCT) image processing is the most important operation prior to image analysis. Such processing mainly involves artefact reduction and image segmentation. We propose a new two-stage post-reconstruction procedure of an image of a geological rock core obtained by polychromatic cone-beam μXCT technology. In the first stage, the beam-hardening (BH) is removed applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. The final BH-corrected image is extracted from the residual data, or the difference between the surface elevation values and the original grey-scale values. For the second stage, we propose using a least square support vector machine (a non-linear classifier algorithm) to segment the BH-corrected data as a pixel-based multi-classification task. A combination of the two approaches was used to classify a complex multi-mineral rock sample. The Matlab code for this approach is provided in the Appendix. A minor drawback is that the proposed segmentation algorithm may become computationally demanding in the case of a high dimensional training data set.

  14. Landsat classification of surface-water presence during multiple years to assess response of playa wetlands to climatic variability across the Great Plains Landscape Conservation Cooperative region

    Science.gov (United States)

    Manier, Daniel J.; Rover, Jennifer R.

    2018-02-15

    To improve understanding of the distribution of ecologically important, ephemeral wetland habitats across the Great Plains, the occurrence and distribution of surface water in playa wetland complexes were documented for four different years across the Great Plains Landscape Conservation Cooperative (GPLCC) region. This information is important because it informs land and wildlife managers about the timing and location of habitat availability. Data with an accurate timestamp that indicate the presence of water, the percent of the area inundated with water, and the spatial distribution of playa wetlands with water are needed for a host of resource inventory, monitoring, and research applications. For example, the distribution of inundated wetlands forms the spatial pattern of available habitat for resident shorebirds and water birds, stop-over habitats for migratory birds, connectivity and clustering of wetland habitats, and surface waters that recharge the Ogallala aquifer; there is considerable variability in the distribution of playa wetlands holding water through time. Documentation of these spatially and temporally intricate processes, here, provides data required to assess connections between inundation and multiple environmental drivers, such as climate, land use, soil, and topography. Climate drivers are understood to interact with land cover, land use and soil attributes in determining the amount of water that flows overland into playa wetlands. Results indicated significant spatial variability represented by differences in the percent of playas inundated among States within the GPLCC. Further, analysis-of-variance comparison of differences in inundation between years showed significant differences in all cases. Although some connections with seasonal moisture patterns may be observed, the complex spatial-temporal gradients of precipitation, temperature, soils, and land use need to be combined as covariates in multivariate models to effectively account for

  15. Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.

    Science.gov (United States)

    Karthick, P A; Ghosh, Diptasree Maitra; Ramakrishnan, S

    2018-02-01

    Surface electromyography (sEMG) based muscle fatigue research is widely preferred in sports science and occupational/rehabilitation studies due to its noninvasiveness. However, these signals are complex, multicomponent and highly nonstationary with large inter-subject variations, particularly during dynamic contractions. Hence, time-frequency based machine learning methodologies can improve the design of automated system for these signals. In this work, the analysis based on high-resolution time-frequency methods, namely, Stockwell transform (S-transform), B-distribution (BD) and extended modified B-distribution (EMBD) are proposed to differentiate the dynamic muscle nonfatigue and fatigue conditions. The nonfatigue and fatigue segments of sEMG signals recorded from the biceps brachii of 52 healthy volunteers are preprocessed and subjected to S-transform, BD and EMBD. Twelve features are extracted from each method and prominent features are selected using genetic algorithm (GA) and binary particle swarm optimization (BPSO). Five machine learning algorithms, namely, naïve Bayes, support vector machine (SVM) of polynomial and radial basis kernel, random forest and rotation forests are used for the classification. The results show that all the proposed time-frequency distributions (TFDs) are able to show the nonstationary variations of sEMG signals. Most of the features exhibit statistically significant difference in the muscle fatigue and nonfatigue conditions. The maximum number of features (66%) is reduced by GA and BPSO for EMBD and BD-TFD respectively. The combination of EMBD- polynomial kernel based SVM is found to be most accurate (91% accuracy) in classifying the conditions with the features selected using GA. The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions. Particularly, the combination of EMBD- polynomial kernel based SVM could be used to

  16. Portable EMG devices, Biofeedback and Contingent Electrical Stimulation applications in Bruxism

    DEFF Research Database (Denmark)

    Castrillon, Eduardo

    Portable EMG devices, Biofeedback and Contingent Electrical Stimulation applications in Bruxism Eduardo Enrique, Castrillon Watanabe, DDS, MSc, PhD Section of Orofacial Pain and Jaw Function, Department of Dentistry, Aarhus University, Aarhus, Denmark; Scandinavian Center for Orofacial Neuroscience...... Summary: Bruxism is a parafunctional activity, which involves the masticatory muscles and probably it is as old as human mankind. Different methods such as portable EMG devices have been proposed to diagnose and understand the pathophysiology of bruxism. Biofeedback / contingent electrical stimulation...... characteristics make it complicated to assess bruxism using portable EMG devices. The possibility to assess bruxism like EMG activity on a portable device made it possible to use biofeedback and CES approaches in order to treat / manage bruxism. The available scientific information about CES effects on bruxism...

  17. EMG System for Production of Methane From Carbon Dioxide, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Sustainable Innovations, LLC, is developing an Electrochemical Methane Generator (EMG), which comprises a novel method of converting CO2 and H2O to hydrocarbon fuels...

  18. sEMG-based joint force control for an upper-limb power-assist exoskeleton robot.

    Science.gov (United States)

    Li, Zhijun; Wang, Baocheng; Sun, Fuchun; Yang, Chenguang; Xie, Qing; Zhang, Weidong

    2014-05-01

    This paper investigates two surface electromyogram (sEMG)-based control strategies developed for a power-assist exoskeleton arm. Different from most of the existing position control approaches, this paper develops force control methods to make the exoskeleton robot behave like humans in order to provide better assistance. The exoskeleton robot is directly attached to a user's body and activated by the sEMG signals of the user's muscles, which reflect the user's motion intention. In the first proposed control method, the forces of agonist and antagonist muscles pair are estimated, and their difference is used to produce the torque of the corresponding joints. In the second method, linear discriminant analysis-based classifiers are introduced as the indicator of the motion type of the joints. Then, the classifier's outputs together with the estimated force of corresponding active muscle determine the torque control signals. Different from the conventional approaches, one classifier is assigned to each joint, which decreases the training time and largely simplifies the recognition process. Finally, the extensive experiments are conducted to illustrate the effectiveness of the proposed approaches.

  19. The effect of hip abduction on the EMG activity of vastus medialis obliquus, vastus lateralis longus and vastus lateralis obliquus in healthy subjects

    Directory of Open Access Journals (Sweden)

    Arakaki Juliano

    2006-07-01

    Full Text Available Abstract Study design Controlled laboratory study. Objectives The purposes of this paper were to investigate (d whether vastus medialis obliquus (VMO, vastus lateralis longus (VLL and vastus lateralis obliquus (VLO EMG activity can be influenced by hip abduction performed by healthy subjects. Background Some clinicians contraindicate hip abduction for patellofemoral patients (with based on the premise that hip abduction could facilitate the VLL muscle activation leading to a VLL and VMO imbalance Methods and measures Twenty-one clinically healthy subjects were involved in the study, 10 women and 11 men (aged X = 23.3 ± 2.9. The EMG signals were collected using a computerized EMG VIKING II, with 8 channels and three pairs of surface electrodes. EMG activity was obtained from MVIC knee extension at 90° of flexion in a seated position and MVIC hip abduction at 0° and 30° with patients in side-lying position with the knee in full extension. The data were normalized in the MVIC knee extension at 50° of flexion in a seated position, and were submitted to ANOVA test with subsequent application of the Bonferroni multiple comparisons analysis test. The level of significance was defined as p ≤ 0.05. Results The VLO muscle demonstrated a similar pattern to the VMO muscle showing higher EMG activity in MVIC knee extension at 90° of flexion compared with MVIC hip abduction at 0° and 30° of abduction for male (p Conclusion The results showed that no selective EMG activation was observed when comparison was made between the VMO, VLL and VLO muscles while performing MVIC hip abduction at 0° and 30° of abduction and MVIC knee extension at 90° of flexion in both male and female subjects. Our findings demonstrate that hip abduction do not facilitated VLL and VLO activity in relation to the VMO, however, this study included only healthy subjects performing maximum voluntary isometric contraction contractions, therefore much remains to be discovered by

  20. The recovery of repeated-sprint exercise is associated with PCr resynthesis, while muscle pH and EMG amplitude remain depressed.

    Directory of Open Access Journals (Sweden)

    Alberto Mendez-Villanueva

    Full Text Available The physiological equivalents of power output maintenance and recovery during repeated-sprint exercise (RSE remain to be fully elucidated. In an attempt to improve our understanding of the determinants of RSE performance we therefore aimed to determine its recovery following exhaustive exercise (which affected intramuscular and neural factors concomitantly with those of intramuscular concentrations of adenosine triphosphate [ATP], phosphocreatine [PCr] and pH values and electromyography (EMG activity (a proxy for net motor unit activity changes. Eight young men performed 10, 6-s all-out sprints on a cycle ergometer, interspersed with 30 s of recovery, followed, after 6 min of passive recovery, by five 6-s sprints, again interspersed by 30 s of passive recovery. Biopsies of the vastus lateralis were obtained at rest, immediately after the first 10 sprints and after 6 min of recovery. EMG activity of the vastus lateralis was obtained from surface electrodes throughout exercise. Total work (TW, [ATP], [PCr], pH and EMG amplitude decreased significantly throughout the first ten sprints (P<0.05. After 6 min of recovery, TW during sprint 11 recovered to 86.3±7.7% of sprint 1. ATP and PCr were resynthesized to 92.6±6.0% and 85.3±10.3% of the resting value, respectively, but muscle pH and EMG amplitude remained depressed. PCr resynthesis was correlated with TW done in sprint 11 (r = 0.79, P<0.05 and TW done during sprints 11 to 15 (r = 0.67, P<0.05. There was a ∼2-fold greater decrease in the TW/EMG ratio in the last five sprints (sprint 11 to 15 than in the first five sprints (sprint 1 to 5 resulting in a disproportionate decrease in mechanical power (i.e., TW in relation to EMG. Thus, we conclude that the inability to produce power output during repeated sprints is mostly mediated by intramuscular fatigue signals probably related with the control of PCr metabolism.

  1. Helical EMG module with explosive current opening switches

    International Nuclear Information System (INIS)

    Chernyshev, V.K.; Vakhrushev, V.V.; Volkov, G.I.; Ivanov, V.A.; Fetisov, I.K.

    1990-01-01

    To carry out the experimental work to study plasma properties, electromagnetic sources with 10 6 to 10 8 J of stored energy delivered to the load in microsecond time, are required. Among the current electromagnetic storage devices, the explosive magnetic generators (EMG) are of the largest energy capacity. The disadvantages of this type of generators is relatively long time (ten of microseconds) of electromagnetic energy cumulation in the deformable circuit. To reduce the time of energy transfer to the load to a microsecond range the switching scheme is generally used, where the cumulation circuit and that of the load are separated and connected in parallel via a switching element (opening switch) providing generation of desired power. In this paper, some ways and means of designing opening switches to generate high current pulses have been investigated. The opening switches to generate high current pulses have been investigated. The opening switches which operation is based on mechanic destruction of the conductor using high explosive, have the highest and most reliable performance. The authors have explored the mechanic disruption of a thin conductor (foil), the technique based on throwing the foil at the ribbed barrier of electric insulator material. The report presents the data obtained in studying the operation of this type of opening switch having cylindrical shape, 200 mm in diameter and 200 mm long, designed for generation of 5.5 MA current pulse in the load

  2. Development of a concept-based EMG-based speller

    Directory of Open Access Journals (Sweden)

    Robertas Damasevicius

    2015-01-01

    Full Text Available La computación fisiológica es un p aradigma de la computación qu e usa los datos de los usuarios como entradas durante las tarea s computacionales en un Ambiente de vidacotidianasoportado po rco mputadores (AAL. Monitoreando, an alizando y respondiendo a dic has entradas, los Sistemas de Computación Fisiológica pueden respon der al estado cognitivo, emocional y físico de los usuarios. Un caso particular es el de la interface de Computación Neuronal (NCI, que usa señales eléctricas para manejar la actividad muscular del usuario establecioendo una comunicación d irecta entre el usuario y el c omputador. Se present una taxonomía de parametros de aplicación de deletreo, proponiendo un modelo de PCS y describiendo el desarr ollo de un deletreador basado en EMG. Se analiza y desarrolla unaaplicación con un sistema basa do en letras tradicionales y u na interfaz visual. Finalmente, se evalua el desempeño y usabil idad del sistemadesarrollado.

  3. Estimation of distal arm joint angles from EMG and shoulder orientation for transhumeral prostheses.

    Science.gov (United States)

    Akhtar, Aadeel; Aghasadeghi, Navid; Hargrove, Levi; Bretl, Timothy

    2017-08-01

    In this paper, we quantify the extent to which shoulder orientation, upper-arm electromyography (EMG), and forearm EMG are predictors of distal arm joint angles during reaching in eight subjects without disability as well as three subjects with a unilateral transhumeral amputation and targeted reinnervation. Prior studies have shown that shoulder orientation and upper-arm EMG, taken separately, are predictors of both elbow flexion/extension and forearm pronation/supination. We show that, for eight subjects without disability, shoulder orientation and upper-arm EMG together are a significantly better predictor of both elbow flexion/extension during unilateral (R 2 =0.72) and mirrored bilateral (R 2 =0.72) reaches and of forearm pronation/supination during unilateral (R 2 =0.77) and mirrored bilateral (R 2 =0.70) reaches. We also show that adding forearm EMG further improves the prediction of forearm pronation/supination during unilateral (R 2 =0.82) and mirrored bilateral (R 2 =0.75) reaches. In principle, these results provide the basis for choosing inputs for control of transhumeral prostheses, both by subjects with targeted motor reinnervation (when forearm EMG is available) and by subjects without target motor reinnervation (when forearm EMG is not available). In particular, we confirm that shoulder orientation and upper-arm EMG together best predict elbow flexion/extension (R 2 =0.72) for three subjects with unilateral transhumeral amputations and targeted motor reinnervation. However, shoulder orientation alone best predicts forearm pronation/supination (R 2 =0.88) for these subjects, a contradictory result that merits further study. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Steering a Tractor by Means of an EMG-Based Human-Machine Interface

    Directory of Open Access Journals (Sweden)

    Sergio Alonso-Garcia

    2011-07-01

    Full Text Available An electromiographic (EMG-based human-machine interface (HMI is a communication pathway between a human and a machine that operates by means of the acquisition and processing of EMG signals. This article explores the use of EMG-based HMIs in the steering of farm tractors. An EPOC, a low-cost human-computer interface (HCI from the Emotiv Company, was employed. This device, by means of 14 saline sensors, measures and processes EMG and electroencephalographic (EEG signals from the scalp of the driver. In our tests, the HMI took into account only the detection of four trained muscular events on the driver’s scalp: eyes looking to the right and jaw opened, eyes looking to the right and jaw closed, eyes looking to the left and jaw opened, and eyes looking to the left and jaw closed. The EMG-based HMI guidance was compared with manual guidance and with autonomous GPS guidance. A driver tested these three guidance systems along three different trajectories: a straight line, a step, and a circumference. The accuracy of the EMG-based HMI guidance was lower than the accuracy obtained by manual guidance, which was lower in turn than the accuracy obtained by the autonomous GPS guidance; the computed standard deviations of error to the desired trajectory in the straight line were 16 cm, 9 cm, and 4 cm, respectively. Since the standard deviation between the manual guidance and the EMG-based HMI guidance differed only 7 cm, and this difference is not relevant in agricultural steering, it can be concluded that it is possible to steer a tractor by an EMG-based HMI with almost the same accuracy as with manual steering.

  5. Processing of Natural Signals like EMG for Person Identification using NUFB-GMM

    OpenAIRE

    Suresh M; P G Krishnamohan; Mallikarjun S Holi

    2014-01-01

    Physiological signals like Electrocardiogram(ECG) and Electroencephalogram(EEG), including deoxyribonucleic acid(DNA) are person specific and distinct for different persons. The motor unit firing pattern, motor unit recruitment order and characteristics of muscle changing from person to person, and therefore Electromyogram (EMG) can be used for person identification. EMG records obtained from a single channel data acquisition system are used to develop person identification system. Non-unifor...

  6. Improved Gender Recognition during Stepping Activity for Rehab Application Using the Combinatorial Fusion Approach of EMG and HRV

    Directory of Open Access Journals (Sweden)

    Nor Aziyatul Izni Mohd Rosli

    2017-03-01

    Full Text Available Gender recognition is trivial for a physiotherapist, but it is considered a challenge for computers. The electromyography (EMG and heart rate variability (HRV were utilized in this work for gender recognition during exercise using a stepper. The relevant features were extracted and selected. The selected features were then fused to automatically predict gender recognition. However, the feature selection for gender classification became a challenge to ensure better accuracy. Thus, in this paper, a feature selection approach based on both the performance and the diversity between the two features from the rank-score characteristic (RSC function in a combinatorial fusion approach (CFA (Hsu et al. was employed. Then, the features from the selected feature sets were fused using a CFA. The results were then compared with other fusion techniques such as naive bayes (NB, decision tree (J48, k-nearest neighbor (KNN and support vector machine (SVM. Besides, the results were also compared with previous researches in gender recognition. The experimental results showed that the CFA was efficient and effective for feature selection. The fusion method was also able to improve the accuracy of the gender recognition rate. The CFA provides much better gender classification results which is 94.51% compared to Barani’s work (90.34%, Nazarloo’s work (92.50%, and other classifiers.

  7. A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series

    OpenAIRE

    Chambon, Stanislas; Galtier, Mathieu; Arnal, Pierrick; Wainrib, Gilles; Gramfort, Alexandre

    2017-01-01

    Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30s of signal a sleep stage, based on the visual inspection of signals such as electroencephalograms (EEG), electrooculograms (EOG), electrocardiograms (ECG) and electromyograms (EMG). We introduce here the first deep learning approach for sleep stage classification that learns end-to-end without computing spectrograms or...

  8. Bilinear modeling of EMG signals to extract user-independent features for multiuser myoelectric interface.

    Science.gov (United States)

    Matsubara, Takamitsu; Morimoto, Jun

    2013-08-01

    In this study, we propose a multiuser myoelectric interface that can easily adapt to novel users. When a user performs different motions (e.g., grasping and pinching), different electromyography (EMG) signals are measured. When different users perform the same motion (e.g., grasping), different EMG signals are also measured. Therefore, designing a myoelectric interface that can be used by multiple users to perform multiple motions is difficult. To cope with this problem, we propose for EMG signals a bilinear model that is composed of two linear factors: 1) user dependent and 2) motion dependent. By decomposing the EMG signals into these two factors, the extracted motion-dependent factors can be used as user-independent features. We can construct a motion classifier on the extracted feature space to develop the multiuser interface. For novel users, the proposed adaptation method estimates the user-dependent factor through only a few interactions. The bilinear EMG model with the estimated user-dependent factor can extract the user-independent features from the novel user data. We applied our proposed method to a recognition task of five hand gestures for robotic hand control using four-channel EMG signals measured from subject forearms. Our method resulted in 73% accuracy, which was statistically significantly different from the accuracy of standard nonmultiuser interfaces, as the result of a two-sample t -test at a significance level of 1%.

  9. Influence on muscle oxygenation to EMG parameters at different skeletal muscle contraction

    Science.gov (United States)

    Zhang, Li; Song, Gaoqing

    2010-02-01

    The purpose of this study is to investigate the influence of muscle oxygenation on EMG parameters during isometric and incremental exercises and to observe the relationship between EMG parameters and muscle oxygenation. Twelve rowers took part in the tests. Near infrared spectrometer was utilized for measurements of muscle oxygenation on lateral quadriceps. sEMG measurement is performed for EMG parameters during isometric and incremental exercises. Results indicated that Oxy-Hb decrease significantly correlated with IEMG, E/T ratio and frequency of impulse signal during 1/3 MVC and 2/3 MVC isometric exercise, and it is also correlated with IEMG, E/T ratio and frequency of impulse signal. Increase of IEMG occurred at the time after Oxy-Hb decrease during incremental exercise and highly correlated with BLa. It is concluded that no matter how heavy the intensity is, Oxy-Hb dissociation may play an important role in affecting EMG parameters of muscle fatigue during isometric exercise. 2) EMG parameters may be influenced by Oxy-Hb dissociation and blood lactate concentration during dynamic exercise.

  10. Learning an EMG Controlled Game: Task-Specific Adaptations and Transfer.

    Science.gov (United States)

    van Dijk, Ludger; van der Sluis, Corry K; van Dijk, Hylke W; Bongers, Raoul M

    2016-01-01

    Video games that aim to improve myoelectric control (myogames) are gaining popularity and are often part of the rehabilitation process following an upper limb amputation. However, direct evidence for their effect on prosthetic skill is limited. This study aimed to determine whether and how myogaming improves EMG control and whether performance improvements transfer to a prosthesis-simulator task. Able-bodied right-handed participants (N = 28) were randomly assigned to 1 of 2 groups. The intervention group was trained to control a video game (Breakout-EMG) using the myosignals of wrist flexors and extensors. Controls played a regular Mario computer game. Both groups trained 20 minutes a day for 4 consecutive days. Before and after training, two tests were conducted: one level of the Breakout-EMG game, and grasping objects with a prosthesis-simulator. Results showed a larger increase of in-game accuracy for the Breakout-EMG group than for controls. The Breakout-EMG group moreover showed increased adaptation of the EMG signal to the game. No differences were found in using a prosthesis-simulator. This study demonstrated that myogames lead to task-specific myocontrol skills. Transfer to a prosthesis task is therefore far from easy. We discuss several implications for future myogame designs.

  11. EMG analysis tuned for determining the timing and level of activation in different motor units.

    Science.gov (United States)

    Lee, Sabrina S M; Miara, Maria de Boef; Arnold, Allison S; Biewener, Andrew A; Wakeling, James M

    2011-08-01

    Recruitment patterns and activation dynamics of different motor units greatly influence the temporal pattern and magnitude of muscle force development, yet these features are not often considered in muscle models. The purpose of this study was to characterize the recruitment and activation dynamics of slow and fast motor units from electromyographic (EMG) recordings and twitch force profiles recorded directly from animal muscles. EMG and force data from the gastrocnemius muscles of seven goats were recorded during in vivo tendon-tap reflex and in situ nerve stimulation experiments. These experiments elicited EMG signals with significant differences in frequency content (p<0.001). The frequency content was characterized using wavelet and principal components analysis, and optimized wavelets with centre frequencies, 149.94 Hz and 323.13 Hz, were obtained. The optimized wavelets were used to calculate the EMG intensities and, with the reconstructed twitch force profiles, to derive transfer functions for slow and fast motor units that estimate the activation state of the muscle from the EMG signal. The resulting activation-deactivation time constants gave r values of 0.98-0.99 between the activation state and the force profiles. This work establishes a framework for developing improved muscle models that consider the intrinsic properties of slow and fast fibres within a mixed muscle, and that can more accurately predict muscle force output from EMG. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. Characterization and Classification of Mesenchymal Stem Cells in Several Species Using Surface Markers for Cell Therapy Purposes.

    Science.gov (United States)

    Ghaneialvar, Hori; Soltani, Leila; Rahmani, Hamid Reza; Lotfi, Abbas Sahebghadam; Soleimani, Masoud

    2018-01-01

    Mesenchymal stem cells are multipotent cells capable of replicating as undifferentiated cells, and have the potential of differentiating into mesenchymal tissue lineages such as osteocytes, adipocytes and chondrocytes. Such lineages can then be used in cell therapy. The aim of present study was to characterize bone marrow derived mesenchymal stem cells in four different species, including: sheep, goat, human and mouse. Human bone-marrow mesenchymal stem cells were purchased, those of sheep and goat were isolated from fetal bone marrow, and those of mouse were collected by washing bone cavity of femur and tibia with DMEM/F12. Using flow-cytometry, they were characterized by CD surface antigens. Furthermore, cells of third passage were examined for their osteogenic and adipogenic differentiation potential by oil red and alizarin red staining respectively. According to the results, CD markers studied in the four groups of mesenchymal stem cells showed a different expression. Goat and sheep expressed CD44 and CD166, and weakly expressed CD34, CD45, CD105 and CD90. Similarly, human and mouse mesenchymal cells expressed CD44, CD166, CD105 and CD90 whereas the expression of CD34 and CD45 was negative. In conclusion, although all mesenchymal stem cells display plastic adherence and tri-lineage differentiation, not all express the same panel of surface antigens described for human mesenchymal stem cells. Additional panel of CD markers are necessary to characterize regenerative potential and possible application of these stem cells in regenerative medicine and implantology.

  13. EMG and Kinematic Responses to Unexpected Slips After Slip Training in Virtual Reality

    Science.gov (United States)

    Parijat, Prakriti; Lockhart, Thurmon E.

    2015-01-01

    The objective of the study was to design a virtual reality (VR) training to induce perturbation in older adults similar to a slip and examine the effect of the training on kinematic and muscular responses in older adults. Twenty-four older adults were involved in a laboratory study and randomly assigned to two groups (virtual reality training and control). Both groups went through three sessions including baseline slip, training, and transfer of training on slippery surface. The training group experienced twelve simulated slips using a visual perturbation induced by tilting a virtual reality scene while walking on the treadmill and the control group completed normal walking during the training session. Kinematic, kinetic, and EMG data were collected during all the sessions. Results demonstrated the proactive adjustments such as increased trunk flexion at heel contact after training. Reactive adjustments included reduced time to peak activations of knee flexors, reduced knee coactivation, reduced time to trunk flexion, and reduced trunk angular velocity after training. In conclusion, the study findings indicate that the VR training was able to generate a perturbation in older adults that evoked recovery reactions and such motor skill can be transferred to the actual slip trials. PMID:25296401

  14. A soft robotic exomusculature glove with integrated sEMG sensing for hand rehabilitation.

    Science.gov (United States)

    Delph, Michael A; Fischer, Sarah A; Gauthier, Phillip W; Luna, Carlos H Martinez; Clancy, Edward A; Fischer, Gregory S

    2013-06-01

    Stroke affects 750,000 people annually, and 80% of stroke survivors are left with weakened limbs and hands. Repetitive hand movement is often used as a rehabilitation technique in order to regain hand movement and strength. In order to facilitate this rehabilitation, a robotic glove was designed to aid in the movement and coordination of gripping exercises. This glove utilizes a cable system to open and close a patients hand. The cables are actuated by servomotors, mounted in a backpack weighing 13.2 lbs including battery power sources. The glove can be controlled in terms of finger position and grip force through switch interface, software program, or surface myoelectric (sEMG) signal. The primary control modes of the system provide: active assistance, active resistance and a preprogrammed mode. This project developed a working prototype of the rehabilitative robotic glove which actuates the fingers over a full range of motion across one degree-of-freedom, and is capable of generating a maximum 15N grip force.

  15. The Application of Spectral Analysis of Surface Wave (SASW) Method as a New Rock Mass Classification Technique in Engineering Geology

    International Nuclear Information System (INIS)

    Abdul Rahim Samsuddin; Abdul Ghani Rafek; Umar Hamzah; Suharsono; Khairul Anuar Mohd Nayan

    2008-01-01

    Spectral analysis of surface waves (SASW) is a seismic method that uses the dispersive characteristics of Rayleigh waves propagating through layered material to evaluate S-wave velocity profile. The SASW is an in situ non intrusive method for geotechnical site characterization which is cost effective as compared to the conventional drilling method. In this study, a total of 20 stations from 13 sites were selected. A software (WINSASW 2.0) was used for the inversion process to produce S-wave velocity versus depth profiles. These profiles were then separately analyzed in relation to several engineering rock mass geological parameters such as stiffness, rock quality designation (RQD), anisotropy and the excavability properties. The analysis of the SASW data was based on the assumption that the rock mass is an isotropic homogeneous material with various intensity of discontinuity which influenced the velocity of surface wave propagation within the rock mass. Measurement of dynamic soil properties was carried out employing the shear wave velocities and the N values of the Standard Penetration Test (N SPT ) from borehole data. A new linear equation V s = 4.44 N SPT + 213.84 which relates S-wave and N SPT was deduced. An empirical equation is also proposed to calculate Rock Quality Designation (RQD) values based on S-wave velocity derived from SASW and that of ultrasonic tests. The result of this equation was found to be less than 10% in comparison to the RQD obtained from actual borehole data. An isotropic analysis of the rock mass was carried out using S-wave velocities derived from SASW measurements in four directions. The plots of S-wave - ultrasonic velocity ratio versus ultrasonic velocity were used to evaluate the excavability properties of rock mass. Five classes of rock mass excavability curves were finally proposed in relation to easy digging, easy ripping, hard ripping, hydraulic breaking and blasting. (author)

  16. Peak medial (but not lateral) hamstring activity is significantly lower during stance phase of running. An EMG investigation using a reduced gravity treadmill.

    Science.gov (United States)

    Hansen, Clint; Einarson, Einar; Thomson, Athol; Whiteley, Rodney

    2017-09-01

    The hamstrings are seen to work during late swing phase (presumably to decelerate the extending shank) then during stance phase (presumably stabilizing the knee and contributing to horizontal force production during propulsion) of running. A better understanding of this hamstring activation during running may contribute to injury prevention and performance enhancement (targeting the specific role via specific contraction mode). Twenty active adult males underwent surface EMG recordings of their medial and lateral hamstrings while running on a reduced gravity treadmill. Participants underwent 36 different conditions for combinations of 50%-100% altering bodyweight (10% increments) & 6-16km/h (2km/h increments, i.e.: 36 conditions) for a minimum of 6 strides of each leg (maximum 32). EMG was normalized to the peak value seen for each individual during any stride in any trial to describe relative activation levels during gait. Increasing running speed effected greater increases in EMG for all muscles than did altering bodyweight. Peak EMG for the lateral hamstrings during running trials was similar for both swing and stance phase whereas the medial hamstrings showed an approximate 20% reduction during stance compared to swing phase. It is suggested that the lateral hamstrings work equally hard during swing and stance phase however the medial hamstrings are loaded slightly less every stance phase. Likely this helps explain the higher incidence of lateral hamstring injury. Hamstring injury prevention and rehabilitation programs incorporating running should consider running speed as more potent stimulus for increasing hamstring muscle activation than impact loading. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Using gastrocnemius sEMG and plasma α-synuclein for the prediction of freezing of gait in Parkinson's disease patients.

    Directory of Open Access Journals (Sweden)

    Xiao-Ying Wang

    Full Text Available Freezing of gait (FOG is a complicated gait disturbance in Parkinson's disease (PD and a relevant subclinical predictor algorithm is lacking. The main purpose of this study is to explore the potential value of surface electromyograph (sEMG and plasma α-synuclein levels as predictors of the FOG seen in PD. 21 PD patients and 15 normal controls were recruited. Motor function was evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS and Freezing of gait questionnaire (FOG-Q. Simultaneously, gait analysis was also performed using VICON capture system in PD patients and sEMG data was recorded as well. Total plasma α-synuclein was quantitatively assessed by Luminex assay in all participants. Recruited PD patients were classified into two groups: PD patients with FOG (PD+FOG and without FOG (PD-FOG, based on clinical manifestation, the results of the FOG-Q and VICON capture system. PD+FOG patients displayed higher FOG-Q scores, decreased walking speed, smaller step length, smaller stride length and prolonged double support time compared to the PD-FOG in the gait trial. sEMG data indicated that gastrocnemius activity in PD+FOG patients was significantly reduced compared to PD-FOG patients. In addition, plasma α-synuclein levels were significantly decreased in the PD+FOG group compared to control group; however, no significant difference was found between the PD+FOG and PD-FOG groups. Our study revealed that gastrocnemius sEMG could be used to evaluate freezing gait in PD patients, while plasma α-synuclein might discriminate freezing of gait in PD patients from normal control, though no difference was found between the PD+FOG and PD-FOG groups.

  18. MODELLING THE RELATIONSHIP BETWEEN LAND SURFACE TEMPERATURE AND LANDSCAPE PATTERNS OF LAND USE LAND COVER CLASSIFICATION USING MULTI LINEAR REGRESSION MODELS

    Directory of Open Access Journals (Sweden)

    A. M. Bernales

    2016-06-01

    Full Text Available The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC and land surface temperature (LST. Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric “Effective mesh size” was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas and looking for common predictors between LSTs of these two different farming periods.

  19. EEG?EMG polygraphic study of dystonia and myoclonus in a case of Creutzfeldt?Jakob disease ?

    OpenAIRE

    Hashimoto, Takao; Iwahashi, Teruaki; Ishii, Wataru; Yamamoto, Kanji; Ikeda, Shu-ichi

    2015-01-01

    We report on a patient with sporadic Creutzfeldt–Jakob disease (CJD) who showed dystonia, periodic myoclonus, and periodic sharp wave complexes (PSWCs) on EEG. The EEG–EMG polygraphic study revealed that dystonia appeared without relation to periodic myoclonus and PSWCs and that dystonia EMGs were strongly suppressed after periodic myoclonus EMGs. These findings suggest that dystonia has a pathogenesis different from that of periodic myoclonus and PSWCs, but dystonia and periodic myoclonus ma...

  20. A stretchable electrode array for non-invasive, skin-mounted measurement of electrocardiography (ECG), electromyography (EMG) and electroencephalography (EEG).

    Science.gov (United States)

    Ma, Rui; Kim, Dae-Hyeong; McCormick, Martin; Coleman, Todd; Rogers, John

    2010-01-01

    This paper reports a class of stretchable electrode array capable of intimate, conformal integration onto the curvilinear surfaces of skin on the human body. The designs employ conventional metallic conductors but in optimized mechanical layouts, on soft, thin elastomeric substrates. These devices exhibit an ability to record spontaneous EEG activity even without conductive electrolyte gels, with recorded alpha rhythm responses that are 40% stronger than those collected using conventional tin electrodes and gels under otherwise similar conditions. The same type of device can also measure high quality ECG and EMG signals. The results suggest broad utility for skin-mounted measurements of electrical activity in the body, with advantages in signal levels, wearability and modes of integration compared to alternatives.

  1. Curved Microneedle Array-Based sEMG Electrode for Robust Long-Term Measurements and High Selectivity

    Directory of Open Access Journals (Sweden)

    Minjae Kim

    2015-07-01

    Full Text Available Surface electromyography is widely used in many fields to infer human intention. However, conventional electrodes are not appropriate for long-term measurements and are easily influenced by the environment, so the range of applications of sEMG is limited. In this paper, we propose a flexible band-integrated, curved microneedle array electrode for robust long-term measurements, high selectivity, and easy applicability. Signal quality, in terms of long-term usability and sensitivity to perspiration, was investigated. Its motion-discriminating performance was also evaluated. The results show that the proposed electrode is robust to perspiration and can maintain a high-quality measuring ability for over 8 h. The proposed electrode also has high selectivity for motion compared with a commercial wet electrode and dry electrode.

  2. Evaluation of the use of partition coefficients and molecular surface properties as predictors of drug absorption: a provisional biopharmaceutical classification of the list of national essential medi

    Directory of Open Access Journals (Sweden)

    NU Rahman

    2011-05-01

    Full Text Available Background and the purpose of the study: Partition coefficients (log D and log P and molecular surface area (PSA are potential predictors of the intestinal permeability of drugs. The aim of this investigation was to evaluate and compare these intestinal permeability indicators.   Methods: Aqueous solubility data were obtained from literature or calculated using ACD/Labs and ALOGPS. Permeability data were predicted based on log P, log D at pH 6.0 (log D6.0, and PSA.  Results: Metoprolol's log P, log D6.0 and a PSA of <65 Å correctly predicted 55.9%, 50.8% and 54.2% of permeability classes, respectively. Labetalol's log P, log D6.0, and PSA correctly predicted 54.2%, 64.4% and 61% of permeability classes, respectively. Log D6.0 correlated well (81% with Caco-2 permeability (Papp. Of the list of national essential medicines, 135 orally administered drugs were classified into biopharmaceutical classification system (BCS. Of these, 57 (42.2%, 28 (20.7%, 44 (32.6%, and 6 (4.4% were class I, II, III and IV respectively. Conclusion: Log D6.0 showed better prediction capability than log P. Metoprolol as permeability internal standard was more conservative than labetalol.

  3. Analysis of scapular muscle EMG activity in patients with idiopathic neck pain: a systematic review.

    Science.gov (United States)

    Castelein, Birgit; Cools, Ann; Bostyn, Emma; Delemarre, Jolien; Lemahieu, Trees; Cagnie, Barbara

    2015-04-01

    It is proposed that altered scapular muscle function can contribute to abnormal loading of the cervical spine. However, it is not clear if patients with idiopathic neck pain show altered activity of the scapular muscles. The aim of this paper was to systematically review the literature regarding the differences or similarities in scapular muscle activity, measured by electromyography ( = EMG), between patients with chronic idiopathic neck pain compared to pain-free controls. Case-control (neck pain/healthy) studies investigating scapular muscle EMG activity (amplitude, timing and fatigue parameters) were searched in Pubmed and Web of Science. 25 articles were included in the systematic review. During rest and activities below shoulder height, no clear differences in mean Upper Trapezius ( = UT) EMG activity exist between patients with idiopathic neck pain and a healthy control group. During overhead activities, no conclusion for scapular EMG amplitude can be drawn as a large variation of results were reported. Adaptation strategies during overhead tasks are not the same between studies. Only one study investigated timing of the scapular muscles and found a delayed onset and shorter duration of the SA during elevation in patients with idiopathic neck pain. For scapular muscle fatigue, no definite conclusions can be made as a wide variation and conflicting results are reported. Further high quality EMG research on scapular muscles (broader than the UT) is necessary to understand/draw conclusions on how scapular muscles react in the presence of idiopathic neck pain. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Embodied simulation as part of affective evaluation processes: task dependence of valence concordant EMG activity.

    Science.gov (United States)

    Weinreich, André; Funcke, Jakob Maria

    2014-01-01

    Drawing on recent findings, this study examines whether valence concordant electromyography (EMG) responses can be explained as an unconditional effect of mere stimulus processing or as somatosensory simulation driven by task-dependent processing strategies. While facial EMG over the Corrugator supercilii and the Zygomaticus major was measured, each participant performed two tasks with pictures of album covers. One task was an affective evaluation task and the other was to attribute the album covers to one of five decades. The Embodied Emotion Account predicts that valence concordant EMG is more likely to occur if the task necessitates a somatosensory simulation of the evaluative meaning of stimuli. Results support this prediction with regard to Corrugator supercilii in that valence concordant EMG activity was only present in the affective evaluation task but not in the non-evaluative task. Results for the Zygomaticus major were ambiguous. Our findings are in line with the view that EMG activity is an embodied part of the evaluation process and not a mere physical outcome.

  5. A Control Strategy with Tactile Perception Feedback for EMG Prosthetic Hand

    Directory of Open Access Journals (Sweden)

    Changcheng Wu

    2015-01-01

    Full Text Available To improve the control effectiveness and make the prosthetic hand not only controllable but also perceivable, an EMG prosthetic hand control strategy was proposed in this paper. The control strategy consists of EMG self-learning motion recognition, backstepping controller with stiffness fuzzy observation, and force tactile representation. EMG self-learning motion recognition is used to reduce the influence on EMG signals caused by the uncertainty of the contacting position of the EMG sensors. Backstepping controller with stiffness fuzzy observation is used to realize the position control and grasp force control. Velocity proportional control in free space and grasp force tracking control in restricted space can be realized by the same controller. The force tactile representation helps the user perceive the states of the prosthetic hand. Several experiments were implemented to verify the effect of the proposed control strategy. The results indicate that the proposed strategy has effectiveness. During the experiments, the comments of the participants show that the proposed strategy is a better choice for amputees because of the improved controllability and perceptibility.

  6. Measuring leg movements during sleep using accelerometry: comparison with EMG and piezo-electric scored events.

    Science.gov (United States)

    Terrill, Philip I; Leong, Matthew; Barton, Katrina; Freakley, Craig; Downey, Carl; Vanniekerk, Mark; Jorgensen, Greg; Douglas, James

    2013-01-01

    Periodic Limb Movements during Sleep (PLMS) can cause significant disturbance to sleep, resulting in daytime sleepiness and reduced quality of life. In conventional clinical practice, PLMS are measured using overnight electromyogram (EMG) of the tibialis anterior muscle, although historically they have also been measured using piezo-electric gauges placed over the muscle. However, PLMS counts (PLM index) do not correlate well with clinical symptomology. In this study, we propose that because EMG and piezo derived signals measure muscle activation rather than actual movement, they may count events with no appreciable movement of the limb and therefore no contribution to sleep disturbance. The aim of this study is thus to determine the percentage of clinically scored limb movements which are not associated with movement of the great toe measured using accelerometry. 9 participants were studied simultaneously with an overnight diagnostic polysomnogram (including EMG and piezo instrumentation of the right leg) and high temporal resolution accelerometry of the right great toe. Limb movements were scored, and peak acceleration during each scored movement was quantified. Across the participant population, 54.9% (range: 26.7-76.3) and 39.0% (range: 4.8-69.6) of limb movements scored using piezo and EMG instrumentation respectively, were not associated with toe movement measured with accelerometry. If sleep disturbance is the consequence of the limb movements, these results may explain why conventional piezo or EMG derived PLMI is poorly correlated with clinical symptomology.

  7. Evaluation of methods for extraction of the volitional EMG in dynamic hybrid muscle activation

    Directory of Open Access Journals (Sweden)

    Mizrahi Joseph

    2006-11-01

    Full Text Available Abstract Background Hybrid muscle activation is a modality used for muscle force enhancement, in which muscle contraction is generated from two different excitation sources: volitional and external, by means of electrical stimulation (ES. Under hybrid activation, the overall EMG signal is the combination of the volitional and ES-induced components. In this study, we developed a computational scheme to extract the volitional EMG envelope from the overall dynamic EMG signal, to serve as an input signal for control purposes, and for evaluation of muscle forces. Methods A "synthetic" database was created from in-vivo experiments on the Tibialis Anterior of the right foot to emulate hybrid EMG signals, including the volitional and induced components. The database was used to evaluate the results obtained from six signal processing schemes, including seven different modules for filtration, rectification and ES component removal. The schemes differed from each other by their module combinations, as follows: blocking window only, comb filter only, blocking window and comb filter, blocking window and peak envelope, comb filter and peak envelope and, finally, blocking window, comb filter and peak envelope. Results and conclusion The results showed that the scheme including all the modules led to an excellent approximation of the volitional EMG envelope, as extracted from the hybrid signal, and underlined the importance of the artifact blocking window module in the process. The results of this work have direct implications on the development of hybrid muscle activation rehabilitation systems for the enhancement of weakened muscles.

  8. Classification of amyotrophic lateral sclerosis disease based on convolutional neural network and reinforcement sample learning algorithm.

    Science.gov (United States)

    Sengur, Abdulkadir; Akbulut, Yaman; Guo, Yanhui; Bajaj, Varun

    2017-12-01

    Electromyogram (EMG) signals contain useful information of the neuromuscular diseases like amyotrophic lateral sclerosis (ALS). ALS is a well-known brain disease, which can progressively degenerate the motor neurons. In this paper, we propose a deep learning based method for efficient classification of ALS and normal EMG signals. Spectrogram, continuous wavelet transform (CWT), and smoothed pseudo Wigner-Ville distribution (SPWVD) have been employed for time-frequency (T-F) representation of EMG signals. A convolutional neural network is employed to classify these features. In it, Two convolution layers, two pooling layer, a fully connected layer and a lost function layer is considered in CNN architecture. The CNN architecture is trained with the reinforcement sample learning strategy. The efficiency of the proposed implementation is tested on publicly available EMG dataset. The dataset contains 89 ALS and 133 normal EMG signals with 24 kHz sampling frequency. Experimental results show 96.80% accuracy. The obtained results are also compared with other methods, which show the superiority of the proposed method.

  9. Suppression of EMG activity by transcranial magnetic stimulation in human subjects during walking

    DEFF Research Database (Denmark)

    Petersen, Nicolas Caesar; Butler, Jane E; Marchand-Pauvert, Veronique

    2001-01-01

    1. The involvement of the motor cortex during human walking was evaluated using transcranial magnetic stimulation (TMS) of the motor cortex at a variety of intensities. Recordings of EMG activity in tibialis anterior (TA) and soleus muscles during walking were rectified and averaged. 2. TMS of low...... intensity (below threshold for a motor-evoked potential, MEP) produced a suppression of ongoing EMG activity during walking. The average latency for this suppression was 40.0 +/- 1.0 ms. At slightly higher intensities of stimulation there was a facilitation of the EMG activity with an average latency of 29.......5 +/- 1.0 ms. As the intensity of the stimulation was increased the facilitation increased in size and eventually a MEP was clear in individual sweeps. 3. In three subjects TMS was replaced by electrical stimulation over the motor cortex. Just below MEP threshold there was a clear facilitation at short...

  10. Simulation of facial expressions using person-specific sEMG signals controlling a biomechanical face model.

    Science.gov (United States)

    Eskes, Merijn; Balm, Alfons J M; van Alphen, Maarten J A; Smeele, Ludi E; Stavness, Ian; van der Heijden, Ferdinand

    2018-01-01

    Functional inoperability in advanced oral cancer is difficult to assess preoperatively. To assess functions of lips and tongue, biomechanical models are required. Apart from adjusting generic models to individual anatomy, muscle activation patterns (MAPs) driving patient-specific functional movements are necessary to predict remaining functional outcome. We aim to evaluate how volunteer-specific MAPs derived from surface electromyographic (sEMG) signals control a biomechanical face model. Muscle activity of seven facial muscles in six volunteers was measured bilaterally with sEMG. A triple camera set-up recorded 3D lip movement. The generic face model in ArtiSynth was adapted to our needs. We controlled the model using the volunteer-specific MAPs. Three activation strategies were tested: activating all muscles [Formula: see text], selecting the three muscles showing highest muscle activity bilaterally [Formula: see text]-this was calculated by taking the mean of left and right muscles and then selecting the three with highest variance-and activating the muscles considered most relevant per instruction [Formula: see text], bilaterally. The model's lip movement was compared to the actual lip movement performed by the volunteers, using 3D correlation coefficients [Formula: see text]. The correlation coefficient between simulations and measurements with [Formula: see text] resulted in a median [Formula: see text] of 0.77. [Formula: see text] had a median [Formula: see text] of 0.78, whereas with [Formula: see text] the median [Formula: see text] decreased to 0.45. We demonstrated that MAPs derived from noninvasive sEMG measurements can control movement of the lips in a generic finite element face model with a median [Formula: see text] of 0.78. Ultimately, this is important to show the patient-specific residual movement using the patient's own MAPs. When the required treatment tools and personalisation techniques for geometry and anatomy become available, this may

  11. Evoked EMG-based torque prediction under muscle fatigue in implanted neural stimulation

    Science.gov (United States)

    Hayashibe, Mitsuhiro; Zhang, Qin; Guiraud, David; Fattal, Charles

    2011-10-01

    In patients with complete spinal cord injury, fatigue occurs rapidly and there is no proprioceptive feedback regarding the current muscle condition. Therefore, it is essential to monitor the muscle state and assess the expected muscle response to improve the current FES system toward adaptive force/torque control in the presence of muscle fatigue. Our team implanted neural and epimysial electrodes in a complete paraplegic patient in 1999. We carried out a case study, in the specific case of implanted stimulation, in order to verify the corresponding torque prediction based on stimulus evoked EMG (eEMG) when muscle fatigue is occurring during electrical stimulation. Indeed, in implanted stimulation, the relationship between stimulation parameters and output torques is more stable than external stimulation in which the electrode location strongly affects the quality of the recruitment. Thus, the assumption that changes in the stimulation-torque relationship would be mainly due to muscle fatigue can be made reasonably. The eEMG was proved to be correlated to the generated torque during the continuous stimulation while the frequency of eEMG also decreased during fatigue. The median frequency showed a similar variation trend to the mean absolute value of eEMG. Torque prediction during fatigue-inducing tests was performed based on eEMG in model cross-validation where the model was identified using recruitment test data. The torque prediction, apart from the potentiation period, showed acceptable tracking performances that would enable us to perform adaptive closed-loop control through implanted neural stimulation in the future.

  12. Engagement and EMG in serious gaming : Experimenting with sound and dynamics in the levee patroller training game

    NARCIS (Netherlands)

    Schuurink, E.L.; Houtkamp, J.; Toet, A.

    2008-01-01

    We measured the effects of sound and visual dynamic elements on user experience of a serious game, with special interest in engagement and arousal. Engagement was measured through questionnaires and arousal through the SAM and electromyography (EMG). We adopted the EMG of the corrugator (frown

  13. The utility of EMG interference pattern analysis in botulinum toxin treatment of torticollis: A randomised, controlled and blinded study

    DEFF Research Database (Denmark)

    Werdelin, L; Dalager, T; Fuglsang-Frederiksen, Anders

    2011-01-01

    OBJECTIVE: The significance of electromyography (EMG) guidance in botulinum toxin (BT) treatment has been much debated. The aim of this study was to evaluate if EMG guidance in the treatment of torticollis in BT-naive patients had a better outcome than treatment after clinical evaluation alone...

  14. Non-stationarity and power spectral shifts in EMG activity reflect motor unit recruitment in rat diaphragm muscle.

    Science.gov (United States)

    Seven, Yasin B; Mantilla, Carlos B; Zhan, Wen-Zhi; Sieck, Gary C

    2013-01-15

    We hypothesized that a shift in diaphragm muscle (DIAm) EMG power spectral density (PSD) to higher frequencies reflects recruitment of more fatigable fast-twitch motor units and motor unit recruitment is reflected by EMG non-stationarity. DIAm EMG was recorded in anesthetized rats during eupnea, hypoxia-hypercapnia (10% O(2)-5% CO(2)), airway occlusion, and sneezing (maximal DIAm force). Although power in all frequency bands increased progressively across motor behaviors, PSD centroid frequency increased only during sneezing (pmotor units were recruited during different motor behaviors. Motor units augmented their discharge frequencies progressively beyond the non-stationary period; yet, EMG signal became stationary. In conclusion, non-stationarity of DIAm EMG reflects the period of motor unit recruitment, while a shift in the PSD towards higher frequencies reflects recruitment of more fatigable fast-twitch motor units. Copyright © 2012 Elsevier B.V. All rights reserved.

  15. Determination of optimal whole body vibration amplitude and frequency parameters with plyometric exercise and its influence on closed-chain lower extremity acute power output and EMG activity in resistance trained males

    Science.gov (United States)

    Hughes, Nikki J.

    The optimal combination of Whole body vibration (WBV) amplitude and frequency has not been established. Purpose. To determine optimal combination of WBV amplitude and frequency that will enhance acute mean and peak power (MP and PP) output EMG activity in the lower extremity muscles. Methods. Resistance trained males (n = 13) completed the following testing sessions: On day 1, power spectrum testing of bilateral leg press (BLP) movement was performed on the OMNI. Days 2 and 3 consisted of WBV testing with either average (5.8 mm) or high (9.8 mm) amplitude combined with either 0 (sham control), 10, 20, 30, 40 and 50 Hz frequency. Bipolar surface electrodes were placed on the rectus femoris (RF), vastus lateralis (VL), bicep femoris (BF) and gastrocnemius (GA) muscles for EMG analysis. MP and PP output and EMG activity of the lower extremity were assessed pre-, post-WBV treatments and after sham-controls on the OMNI while participants performed one set of five repetitions of BLP at the optimal resistance determined on Day 1. Results. No significant differences were found between pre- and sham-control on MP and PP output and on EMG activity in RF, VL, BF and GA. Completely randomized one-way ANOVA with repeated measures demonstrated no significant interaction of WBV amplitude and frequency on MP and PP output and peak and mean EMGrms amplitude and EMG rms area under the curve. RF and VL EMGrms area under the curve significantly decreased (p plyometric exercise does not induce alterations in subsequent MP and PP output and EMGrms activity of the lower extremity. Future studies need to address the time of WBV exposure and magnitude of external loads that will maximize strength and/or power output.

  16. 10 CFR 61.55 - Waste classification.

    Science.gov (United States)

    2010-01-01

    ... REGULATORY COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE Technical Requirements for Land Disposal Facilities § 61.55 Waste classification. (a) Classification of waste for near surface disposal—(1) Considerations. Determination of the classification of radioactive waste involves two...

  17. Surface electromyographic amplitude does not identify differences in neural drive to synergistic muscles.

    Science.gov (United States)

    Martinez-Valdes, Eduardo; Negro, Francesco; Falla, Deborah; De Nunzio, Alessandro Marco; Farina, Dario

    2018-04-01

    Surface electromyographic (EMG) signal amplitude is typically used to compare the neural drive to muscles. We experimentally investigated this association by studying the motor unit (MU) behavior and action potentials in the vastus medialis (VM) and vastus lateralis (VL) muscles. Eighteen participants performed isometric knee extensions at four target torques [10, 30, 50, and 70% of the maximum torque (MVC)] while high-density EMG signals were recorded from the VM and VL. The absolute EMG amplitude was greater for VM than VL ( P differences in EMG amplitude can be due to both differences in the neural drive and in the size of the MU action potentials, we indirectly inferred the neural drives received by the two muscles by estimating the synaptic inputs received by the corresponding motor neuron pools. For this purpose, we analyzed the increase in discharge rate from recruitment to target torque for motor units matched by recruitment threshold in the two muscles. This analysis indicated that the two muscles received similar levels of neural drive. Nonetheless, the size of the MU action potentials was greater for VM than VL ( P difference explained most of the differences in EMG amplitude between the two muscles (~63% of explained variance). These results indicate that EMG amplitude, even following normalization, does not reflect the neural drive to synergistic muscles. Moreover, absolute EMG amplitude is mainly explained by the size of MU action potentials. NEW & NOTEWORTHY Electromyographic (EMG) amplitude is widely used to compare indirectly the strength of neural drive received by synergistic muscles. However, there are no studies validating this approach with motor unit data. Here, we compared between-muscles differences in surface EMG amplitude and motor unit behavior. The results clarify the limitations of surface EMG to interpret differences in neural drive between muscles.

  18. EMG activities and plantar pressures during ski jumping take-off on three different sized hills.

    Science.gov (United States)

    Virmavirta, M; Perttunen, J; Komi, P V

    2001-04-01

    Different profiles of ski jumping hills have been assumed to make the initiation of take-off difficult especially when moving from one hill to another. Neuromuscular adaptation of ski jumpers to the different jumping hills was examined by measuring muscle activation and plantar pressure of the primary take-off muscles on three different sized hills. Two young ski jumpers volunteered as subjects and they performed several trials from each hill (K-35 m, K-65 m and K-90 m) with the same electromyographic (EMG) electrode and insole pressure transducer set-up. The results showed that the differences in plantar pressure and EMGs between the jumping hills were smaller than expected for both jumpers. The small changes in EMG amplitudes between the hills support the assumption that the take-off was performed with the same intensity on different jumping hills and the timing of the gluteus EMG demonstrates well the similarity of the muscle activation on different hills. On the basis of the results obtained it seems that ski jumping training on small hills does not disturb the movement patterns for bigger hills and can also be helpful for special take-off training with low speed.

  19. Automatic apparatus for measuring thermophysical quantities controlled by calculator EMG 666

    International Nuclear Information System (INIS)

    Kubicar, L.; Illekova, E.

    1984-01-01

    Automatic system for measuring thermal diffusivity, thermal conductivity and heat capacity of samples is described. Measurements are performed by the pulse method in the temperature range from -150 to 1500 deg C. The measuring CAMAC equipment connected with the EMG 666 computer. Data processing is carried out by 100-400 measurement points (measuring cycle) for the whole temperature range

  20. Vastus lateralis single motor unit EMG at the same absolute torque production at different knee angles

    NARCIS (Netherlands)

    Altenburg, T.M.; de Haan, A.; Verdijk, P.W.; van Mechelen, W.; de Ruiter, C.J.

    2009-01-01

    Single motor unit electromyographic (EMG) activity of the knee extensors was investigated at different knee angles with subjects (n = 10) exerting the same absolute submaximal isometric torque at each angle. Measurements were made over a 20° range around the optimum angle for torque production

  1. Control of leg movements driven by EMG activity of shoulder muscles

    Directory of Open Access Journals (Sweden)

    Valentina eLa Scaleia

    2014-10-01

    Full Text Available During human walking there exists a functional neural coupling between arms and legs, and between cervical and lumbosacral pattern generators. Here we present a novel approach for associating the electromyographic (EMG activity from upper limb muscles with leg kinematics. Our methodology takes advantage of the high involvement of shoulder muscles in most locomotor-related movements and of the natural coordination between arms and legs. Nine healthy subjects were asked to walk at different constant and variable speeds (3-5 km/h, while EMG activity of shoulder (deltoid muscles and the kinematics of walking were recorded. To ensure a high level of EMG activity in deltoid, the subjects performed slightly larger arm swinging than they usually do. The temporal structure of the burst-like EMG activity was used to predict the spatiotemporal kinematic pattern of the forthcoming step. A comparison of actual and predicted stride leg kinematics showed a high degree of correspondence (r>0.9. This algorithm has been also implemented in pilot experiments for controlling avatar walking in a virtual reality setup and an exoskeleton during overground stepping. The proposed approach may have important implications for the design of human-machine interfaces and neuroprosthetic technologies such as those of assistive lower limb exoskeletons.

  2. Adaptive EMG noise reduction in ECG signals using noise level approximation

    Science.gov (United States)

    Marouf, Mohamed; Saranovac, Lazar

    2017-12-01

    In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.

  3. Oxygenation and EMG in the proximal and distal vastus lateralis during submaximal isometric knee extension

    DEFF Research Database (Denmark)

    Crenshaw, Albert G.; Bronee, Lars; Krag, Ida

    2010-01-01

    /or (2) fatigue development. Nine males performed 2-min sustained isometric knee extensions at 15% and 30% maximum voluntary contraction during which oxygenation and EMG were recorded simultaneously from proximal and distal locations of the vastus lateralis muscle. Near infrared spectroscopy variables...

  4. A new algorithm for ECG interference removal from single channel EMG recording.

    Science.gov (United States)

    Yazdani, Shayan; Azghani, Mahmood Reza; Sedaaghi, Mohammad Hossein

    2017-09-01

    This paper presents a new method to remove electrocardiogram (ECG) interference from electromyogram (EMG). This interference occurs during the EMG acquisition from trunk muscles. The proposed algorithm employs progressive image denoising (PID) algorithm and ensembles empirical mode decomposition (EEMD) to remove this type of interference. PID is a very recent method that is being used for denoising digital images mixed with white Gaussian noise. It detects white Gaussian noise by deterministic annealing. To the best of our knowledge, PID has never been used before, in the case of EMG and ECG separation or in other 1D signal denoising applications. We have used it according to this fact that amplitude of the EMG signal can be modeled as white Gaussian noise using a filter with time-variant properties. The proposed algorithm has been compared to the other well-known methods such as HPF, EEMD-ICA, Wavelet-ICA and PID. The results show that the proposed algorithm outperforms the others, on the basis of three evaluation criteria used in this paper: Normalized mean square error, Signal to noise ratio and Pearson correlation.

  5. Quantitative evaluation of muscle relaxation induced by Kundalini yoga with the help of EMG integrator.

    Science.gov (United States)

    Narayan, R; Kamat, A; Khanolkar, M; Kamat, S; Desai, S R; Dhume, R A

    1990-10-01

    The present work is aimed to quantify the degree of relaxation of muscle under the effects of Kundalini Yoga with the help of EMG integrator. The data collected from 8 individuals (4 males 4 females) on the degree of muscle relaxation at the end of meditation revealed a significantly decreased muscle activity amounting to 58% of the basal level in both the sexes.

  6. EMG-Based Estimation of Limb Movement Using Deep Learning With Recurrent Convolutional Neural Networks.

    Science.gov (United States)

    Xia, Peng; Hu, Jie; Peng, Yinghong

    2017-10-25

    A novel model based on deep learning is proposed to estimate kinematic information for myoelectric control from multi-channel electromyogram (EMG) signals. The neural information of limb movement is embedded in EMG signals that are influenced by all kinds of factors. In order to overcome the negative effects of variability in signals, the proposed model employs the deep architecture combining convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The EMG signals are transformed to time-frequency frames as the input to the model. The limb movement is estimated by the model that is trained with the gradient descent and backpropagation procedure. We tested the model for simultaneous and proportional estimation of limb movement in eight healthy subjects and compared it with support vector regression (SVR) and CNNs on the same data set. The experimental studies show that the proposed model has higher estimation accuracy and better robustness with respect to time. The combination of CNNs and RNNs can improve the model performance compared with using CNNs alone. The model of deep architecture is promising in EMG decoding and optimization of network structures can increase the accuracy and robustness. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  7. Effect of toe extension on EMG of triceps surae muscles during isometric dorsiflexion.

    Science.gov (United States)

    Siddiqi, Ariba; Arjunan, Sridhar P; Kumar, Dinesh

    2016-12-01

    The protocol for estimating force of contraction by triceps surae (TS) muscles requires the immobilization of the ankle during dorsiflexion and plantar flexion. However, large variability in the results has been observed. To identify the cause of this variability, experiments were conducted where ankle dorsiflexion force and electromyogram (EMG) of the TS were recorded under two conditions: (i) toes were strapped and (ii) toes were unstrapped, with all other conditions such as immobilization of the ankle remaining unchanged. The root mean square (RMS) of the EMG and the force were analyzed and one-tail Student's t-test was performed for significance between the two conditions. The RMS of the EMG from TS muscles was found to be significantly higher (~55%) during dorsiflexion with toes unstrapped compared with when the toes were strapped. The torque corresponding to dorsiflexion was also higher with toes unstrapped. Our study has shown that it is important to strap the toes when measuring the torque at the ankle and EMG of the TS muscles.

  8. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  9. Contributions to muscle force and EMG by combined neural excitation and electrical stimulation

    Science.gov (United States)

    Crago, Patrick E.; Makowski, Nathaniel S.; Cole, Natalie M.

    2014-10-01

    Objective. Stimulation of muscle for research or clinical interventions is often superimposed on ongoing physiological activity without a quantitative understanding of the impact of the stimulation on the net muscle activity and the physiological response. Experimental studies show that total force during stimulation is less than the sum of the isolated voluntary and stimulated forces, but the occlusion mechanism is not understood. Approach. We develop a model of efferent motor activity elicited by superimposing stimulation during a physiologically activated contraction. The model combines action potential interactions due to collision block, source resetting, and refractory periods with previously published models of physiological motor unit recruitment, rate modulation, force production, and EMG generation in human first dorsal interosseous muscle to investigate the mechanisms and effectiveness of stimulation on the net muscle force and EMG. Main results. Stimulation during a physiological contraction demonstrates partial occlusion of force and the neural component of the EMG, due to action potential interactions in motor units activated by both sources. Depending on neural and stimulation firing rates as well as on force-frequency properties, individual motor unit forces can be greater, smaller, or unchanged by the stimulation. In contrast, voluntary motor unit EMG potentials in simultaneously stimulated motor units show progressive occlusion with increasing stimulus rate. The simulations predict that occlusion would be decreased by a reverse stimulation recruitment order. Significance. The results are consistent with and provide a mechanistic interpretation of previously published experimental evidence of force occlusion. The models also predict two effects that have not been reported previously—voluntary EMG occlusion and the advantages of a proximal stimulation site. This study provides a basis for the rational design of both future experiments and clinical

  10. Real-time simultaneous and proportional myoelectric control using intramuscular EMG

    Science.gov (United States)

    Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

    2014-12-01

    Objective. Myoelectric prostheses use electromyographic (EMG) signals to control movement of prosthetic joints. Clinically available myoelectric control strategies do not allow simultaneous movement of multiple degrees of freedom (DOFs); however, the use of implantable devices that record intramuscular EMG signals could overcome this constraint. The objective of this study was to evaluate the real-time simultaneous control of three DOFs (wrist rotation, wrist flexion/extension, and hand open/close) using intramuscular EMG. Approach. We evaluated task performance of five able-bodied subjects in a virtual environment using two control strategies with fine-wire EMG: (i) parallel dual-site differential control, which enabled simultaneous control of three DOFs and (ii) pattern recognition control, which required sequential control of DOFs. Main results. Over the course of the experiment, subjects using parallel dual-site control demonstrated increased use of simultaneous control and improved performance in a Fitts’ Law test. By the end of the experiment, performance using parallel dual-site control was significantly better (up to a 25% increase in throughput) than when using sequential pattern recognition control for tasks requiring multiple DOFs. The learning trends with parallel dual-site control suggested that further improvements in performance metrics were possible. Subjects occasionally experienced difficulty in performing isolated single-DOF movements with parallel dual-site control but were able to accomplish related Fitts’ Law tasks with high levels of path efficiency. Significance. These results suggest that intramuscular EMG, used in a parallel dual-site configuration, can provide simultaneous control of a multi-DOF prosthetic wrist and hand and may outperform current methods that enforce sequential control.

  11. EMG Versus Torque Control of Human-Machine Systems: Equalizing Control Signal Variability Does not Equalize Error or Uncertainty.

    Science.gov (United States)

    Johnson, Reva E; Kording, Konrad P; Hargrove, Levi J; Sensinger, Jonathon W

    2017-06-01

    In this paper we asked the question: if we artificially raise the variability of torque control signals to match that of EMG, do subjects make similar errors and have similar uncertainty about their movements? We answered this question using two experiments in which subjects used three different control signals: torque, torque+noise, and EMG. First, we measured error on a simple target-hitting task in which subjects received visual feedback only at the end of their movements. We found that even when the signal-to-noise ratio was equal across EMG and torque+noise control signals, EMG resulted in larger errors. Second, we quantified uncertainty by measuring the just-noticeable difference of a visual perturbation. We found that for equal errors, EMG resulted in higher movement uncertainty than both torque and torque+noise. The differences suggest that performance and confidence are influenced by more than just the noisiness of the control signal, and suggest that other factors, such as the user's ability to incorporate feedback and develop accurate internal models, also have significant impacts on the performance and confidence of a person's actions. We theorize that users have difficulty distinguishing between random and systematic errors for EMG control, and future work should examine in more detail the types of errors made with EMG control.

  12. The effect of isolating the paretic limb on weight-bearing distribution and EMG activity during squats in hemiplegic and healthy individuals.

    Science.gov (United States)

    Lee, Dong-Kyu; An, Duk-Hyun; Yoo, Won-Gyu; Hwang, Byong-Yong; Kim, Tae-Ho; Oh, Jae-Seop

    2017-05-01

    Neural reorganization for movement therapy after a stroke is thought to be an important mechanism that facilitates motor recovery. However, there is a lack of evidence for the effectiveness of exercise programs in improving the lower limbs. We investigated the immediate effect of isolating the paretic limb using different foot positions ((i) foot parallel; both feet parallel, (ii) foot asymmetry; paretic foot backward by 10 cm, and (iii) foot lifting; nonparetic foot lifting by normalization to 25% of knee height) on weight-bearing distribution and electromyography (EMG) of the thigh muscle during squats. In total, 20 patients with hemiplegia and 16 healthy subjects randomly performed three squat conditions in which the knee joint was flexed to 30°. Weight distribution was measured using the BioRescue system. Muscle activity was measured using a surface EMG system. Patients with hemiplegia exhibited significantly decreased weight bearing on the paretic foot at 0° and 30° knee flexion compared with the nondominant foot of a healthy subject. The muscle activity of the quadriceps was significantly lower in patients with hemiplegia compared to healthy subjects. Weight bearing and EMG activity of the quadriceps femoris on the paretic or nondominant side significantly increased during a knee flexion of 30° with under the foot asymmetry and foot lifting positions compared with the parallel foot position. Isolating the paretic limb using the asymmetric foot positions and lifting of the foot during squats might help patients with hemiplegia to improve weight-bearing and achieve greater activation of the quadriceps muscle in the paretic limb.

  13. Neural mechanisms of intermuscular coherence: Implications for the rectification of surface electromyography

    NARCIS (Netherlands)

    Boonstra, T.W.; Breakspear, M.

    2012-01-01

    Oscillatory activity plays a crucial role in corticospinal control of muscle synergies and is widely investigated using corticospinal and intermuscular synchronization. However, the neurophysiological mechanisms that translate these rhythmic patterns into surface electromyography (EMG) are not well

  14. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  15. EEG–EMG polygraphic study of dystonia and myoclonus in a case of Creutzfeldt–Jakob disease

    Directory of Open Access Journals (Sweden)

    Takao Hashimoto

    2015-01-01

    Full Text Available We report on a patient with sporadic Creutzfeldt–Jakob disease (CJD who showed dystonia, periodic myoclonus, and periodic sharp wave complexes (PSWCs on EEG. The EEG–EMG polygraphic study revealed that dystonia appeared without relation to periodic myoclonus and PSWCs and that dystonia EMGs were strongly suppressed after periodic myoclonus EMGs. These findings suggest that dystonia has a pathogenesis different from that of periodic myoclonus and PSWCs, but dystonia and periodic myoclonus may be generated through the sensorimotor cortex in CJD.

  16. A hybrid BMI-based exoskeleton for paresis: EMG control for assisting arm movements.

    Science.gov (United States)

    Kawase, Toshihiro; Sakurada, Takeshi; Koike, Yasuharu; Kansaku, Kenji

    2017-02-01

    Brain-machine interface (BMI) technologies have succeeded in controlling robotic exoskeletons, enabling some paralyzed people to control their own arms and hands. We have developed an exoskeleton asynchronously controlled by EEG signals. In this study, to enable real-time control of the exoskeleton for paresis, we developed a hybrid system with EEG and EMG signals, and the EMG signals were used to estimate its joint angles. Eleven able-bodied subjects and two patients with upper cervical spinal cord injuries (SCIs) performed hand and arm movements, and the angles of the metacarpophalangeal (MP) joint of the index finger, wrist, and elbow were estimated from EMG signals using a formula that we derived to calculate joint angles from EMG signals, based on a musculoskeletal model. The formula was exploited to control the elbow of the exoskeleton after automatic adjustments. Four able-bodied subjects and a patient with upper cervical SCI wore an exoskeleton controlled using EMG signals and were required to perform hand and arm movements to carry and release a ball. Estimated angles of the MP joints of index fingers, wrists, and elbows were correlated well with the measured angles in 11 able-bodied subjects (correlation coefficients were 0.81  ±  0.09, 0.85  ±  0.09, and 0.76  ±  0.13, respectively) and the patients (e.g. 0.91  ±  0.01 in the elbow of a patient). Four able-bodied subjects successfully positioned their arms to adequate angles by extending their elbows and a joint of the exoskeleton, with root-mean-square errors  exoskeleton, successfully carried a ball to a goal in all 10 trials. A BMI-based exoskeleton for paralyzed arms and hands using real-time control was realized by designing a new method to estimate joint angles based on EMG signals, and these may be useful for practical rehabilitation and the support of daily actions.

  17. A hybrid BMI-based exoskeleton for paresis: EMG control for assisting arm movements

    Science.gov (United States)

    Kawase, Toshihiro; Sakurada, Takeshi; Koike, Yasuharu; Kansaku, Kenji

    2017-02-01

    Objective. Brain-machine interface (BMI) technologies have succeeded in controlling robotic exoskeletons, enabling some paralyzed people to control their own arms and hands. We have developed an exoskeleton asynchronously controlled by EEG signals. In this study, to enable real-time control of the exoskeleton for paresis, we developed a hybrid system with EEG and EMG signals, and the EMG signals were used to estimate its joint angles. Approach. Eleven able-bodied subjects and two patients with upper cervical spinal cord injuries (SCIs) performed hand and arm movements, and the angles of the metacarpophalangeal (MP) joint of the index finger, wrist, and elbow were estimated from EMG signals using a formula that we derived to calculate joint angles from EMG signals, based on a musculoskeletal model. The formula was exploited to control the elbow of the exoskeleton after automatic adjustments. Four able-bodied subjects and a patient with upper cervical SCI wore an exoskeleton controlled using EMG signals and were required to perform hand and arm movements to carry and release a ball. Main results. Estimated angles of the MP joints of index fingers, wrists, and elbows were correlated well with the measured angles in 11 able-bodied subjects (correlation coefficients were 0.81  ±  0.09, 0.85  ±  0.09, and 0.76  ±  0.13, respectively) and the patients (e.g. 0.91  ±  0.01 in the elbow of a patient). Four able-bodied subjects successfully positioned their arms to adequate angles by extending their elbows and a joint of the exoskeleton, with root-mean-square errors  exoskeleton, successfully carried a ball to a goal in all 10 trials. Significance. A BMI-based exoskeleton for paralyzed arms and hands using real-time control was realized by designing a new method to estimate joint angles based on EMG signals, and these may be useful for practical rehabilitation and the support of daily actions.

  18. The slow component of O(2) uptake is not accompanied by changes in muscle EMG during repeated bouts of heavy exercise in humans.

    Science.gov (United States)

    Scheuermann, B W; Hoelting, B D; Noble, M L; Barstow, T J

    2001-02-15

    1. We hypothesized that either the recruitment of additional muscle motor units and/or the progressive recruitment of less efficient fast-twitch muscle fibres was the predominant contributor to the additional oxygen uptake (VO2) observed during heavy exercise. Using surface electromyographic (EMG) techniques, we compared the VO2 response with the integrated EMG (iEMG) and mean power frequency (MPF) response of the vastus lateralis with the VO2 response during repeated bouts of moderate (below the lactate threshold, LT) intensity cycle ergometer exercise. 2. Seven male subjects (age 29 +/- 7 years, mean +/- S.D.) performed three transitions to a work rate (WR) corresponding to 90 % LT and two transitions to a work rate that would elicit a VO2 corresponding to 50 % of the difference between peak VO2 and the LT (i.e. Delta50 %, > LT1 and > LT2). 3. The VO2 slow component was significantly reduced by prior heavy intensity exercise (> LT1, 410 +/- 196 ml min(-1); > LT2, 230 +/- 191 ml min-1). The time constant (tau), amplitude (A) and gain (DeltaVO2/DeltaWR) of the primary VO2 response (phase II) were not affected by prior heavy exercise when a three-component, exponential model was used to describe the V2 response. 4. Integrated EMG and MPF remained relatively constant and at the same level throughout both > LT1 and > LT2 exercise and therefore were not associated with the VO2 slow component. 5. These data are consistent with the view that the increased O2 cost (i.e. VO2 slow component) associated with performing heavy exercise is coupled with a progressive increase in ATP requirements of the already recruited motor units rather than to changes in the recruitment pattern of slow versus fast-twitch motor units. Further, the lack of speeding of the kinetics of the primary VO2 component with prior heavy exercise, thought to represent the initial muscle VO2 response, are inconsistent with O2 delivery being the limiting factor in V > O2 kinetics during heavy exercise.

  19. Vastus lateralis surface and single motor unit EMG following submaximal shortening and lengthening contractions

    NARCIS (Netherlands)

    Altenburg, T.M.; de Ruiter, C.J.; Verdijk, P.W.L.; van Mechelen, W.; de Haan, A.

    2008-01-01

    A single shortening contraction reduces the force capacity of muscle fibers, whereas force capacity is enhanced following lengthening. However, how motor unit recruitment and discharge rate (muscle activation) are adapted to such changes in force capacity during submaximal contractions remains

  20. Interpreting Changes in Surface EMG Amplitude During High-Level Fatiguing Contractions of the Brachioradialis

    National Research Council Canada - National Science Library

    Lowery, M

    2001-01-01

    .... It is proposed that using these relationships, under conditions where motor unit recruitment and synchronization can be assumed to be negligible, such as at high force levels or in smaller muscles...

  1. Surface EMG signals in very late-stage of Duchenne muscular dystrophy : A case study

    NARCIS (Netherlands)

    Lobo Prat, J.; Janssen, Mariska M.H.P.; Koopman, Bart F.J.M.; Stienen, Arno H.A.; De Groot, Imelda J.M.

    2017-01-01

    Background: Robotic arm supports aim at improving the quality of life for adults with Duchenne muscular dystrophy (DMD) by augmenting their residual functional abilities. A critical component of robotic arm supports is the control interface, as is it responsible for the human-machine interaction.

  2. Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique

    Science.gov (United States)

    Abbaspour, S; Fallah, A

    2014-01-01

    Background: The electrocardiogram artifact is a major contamination in the electromyogram signals when electromyogram signal is recorded from upper trunk muscles and because of that the contaminated electromyogram is not useful. Objective: Removing electrocardiogram contamination from electromyogram signals. Methods: In this paper, the clean electromyogram signal, electrocardiogram artifact and electrocardiogram signal were recorded from leg muscles, the pectoralis major muscle of the left side and V4, respectively. After the pre-processing, contaminated electromyogram signal is simulated with a combination of clean electromyogram and electrocardiogram artifact. Then, contaminated electromyogram is cleaned using adaptive subtraction method. This method contains some steps; (1) QRS detection, (2) formation of electrocardiogram template by averaging the electrocardiogram complexes, (3) using low pass filter to remove undesirable artifacts, (4) subtraction. Results: Performance of our method is evaluated using qualitative criteria, power spectrum density and coherence and quantitative criteria signal to noise ratio, relative error and cross correlation. The result of signal to noise ratio, relative error and cross correlation is equal to 10.493, 0.04 and %97 respectively. Finally, there is a comparison between proposed method and some existing methods. Conclusion: The result indicates that adaptive subtraction method is somewhat effective to remove electrocardiogram artifact from contaminated electromyogram signal and has an acceptable result. PMID:25505766

  3. Maximal bite force and surface EMG in patients with myasthenia gravis

    NARCIS (Netherlands)

    Weijnen, FG; Wokke, JHJ; Kuks, JBM; van der Glas, HW; Bosman, F

    2000-01-01

    Masticatory muscle strength was quantified in patients with bulbar myasthenia gravis and compared with that of patients with ocular myasthenia gravis, patients in clinical remission (whether or not pharmacological) who previously suffered from bulbar myasthenia gravis, and healthy subjects. Maximal

  4. Compensatory neurofuzzy model for discrete data classification in biomedical

    Science.gov (United States)

    Ceylan, Rahime

    2015-03-01

    Biomedical data is separated to two main sections: signals and discrete data. So, studies in this area are about biomedical signal classification or biomedical discrete data classification. There are artificial intelligence models which are relevant to classification of ECG, EMG or EEG signals. In same way, in literature, many models exist for classification of discrete data taken as value of samples which can be results of blood analysis or biopsy in medical process. Each algorithm could not achieve high accuracy rate on classification of signal and discrete data. In this study, compensatory neurofuzzy network model is presented for classification of discrete data in biomedical pattern recognition area. The compensatory neurofuzzy network has a hybrid and binary classifier. In this system, the parameters of fuzzy systems are updated by backpropagation algorithm. The realized classifier model is conducted to two benchmark datasets (Wisconsin Breast Cancer dataset and Pima Indian Diabetes dataset). Experimental studies show that compensatory neurofuzzy network model achieved 96.11% accuracy rate in classification of breast cancer dataset and 69.08% accuracy rate was obtained in experiments made on diabetes dataset with only 10 iterations.

  5. Comparison of jaw muscle EMG activity in awake and sleep bruxers

    DEFF Research Database (Denmark)

    Castrillon, Eduardo; Dreyer Nielsen, Patricia; Haugland, Morten

    2015-01-01

    , Scandinavian Center for Orofacial Neuroscience (SCON), Aarhus, DENMARK; M. Haugland, DELTA, Copenhagen, DENMARK; W. Yachida, T. Arima, Hokkaido University, Hokkaido, JAPAN; Group Author Abstracts: ABSTRACT: Objectives: Background: Bruxism has two different circadian manifestations (awake and sleep) that have...... been proposed to have different underlying pathophysiology. Objectives: To compare the characteristics of multiple days EMG assessment of the anterior temporalis muscles between patients with self-reported awake bruxism, sleep bruxism and healthy individuals. Methods: Methods: Participants...... with possible sleep bruxism (n=9) or awake bruxism (n=9) bruxism were included in an open study and compared with healthy individuals during awake (n=9) and sleep (n=7) states. All participants were assessed for a minimum of 4 days (awake or sleep) with a portable single-channel EMG recorder. The outcome...

  6. EEG and EMG responses to emotion-evoking stimuli processed without conscious awareness.

    Science.gov (United States)

    Wexler, B E; Warrenburg, S; Schwartz, G E; Janer, L D

    1992-12-01

    Dichotic stimulus pairs were constructed with one word that was emotionally neutral and another that evoked either negative or positive feelings. Temporal and spectral overlap between the members of each pair was so great that the two words fused into a single auditory percept. Subjects were consciously aware of hearing only one word from most pairs; sometimes the emotion-evoking word was heard consciously, other times the neutral word was heard consciously. Subjects were instructed to let their thoughts wander in response to the word they heard, during which time EEG alpha activity over left and right frontal regions, and muscle activity (EMG) in the corrugator ("frowning") and zygomatic ("smiling") regions were recorded. Both EEG and EMG provided evidence of emotion-specific responses to stimuli that were processed without conscious awareness. Moreover both suggested relatively greater right hemisphere activity with unconscious rather than conscious processing.

  7. Random Forest-Based Recognition of Isolated Sign Language Subwords Using Data from Accelerometers and Surface Electromyographic Sensors.

    Science.gov (United States)

    Su, Ruiliang; Chen, Xiang; Cao, Shuai; Zhang, Xu

    2016-01-14

    Sign language recognition (SLR) has been widely used for communication amongst the hearing-impaired and non-verbal community. This paper proposes an accurate and robust SLR framework using an improved decision tree as the base classifier of random forests. This framework was used to recognize Chinese sign language subwords using recordings from a pair of portable devices worn on both arms consisting of accelerometers (ACC) and surface electromyography (sEMG) sensors. The experimental results demonstrated the validity of the proposed random forest-based method for recognition of Chinese sign language (CSL) subwords. With the proposed method, 98.25% average accuracy was obtained for the classification of a list of 121 frequently used CSL subwords. Moreover, the random forests method demonstrated a superior performance in resisting the impact of bad training samples. When the proportion of bad samples in the training set reached 50%, the recognition error rate of the random forest-based method was only 10.67%, while that of a single decision tree adopted in our previous work was almost 27.5%. Our study offers a practical way of realizing a robust and wearable EMG-ACC-based SLR systems.

  8. Comparison of conventional filtering and independent component analysis for artifact reduction in simultaneous gastric EMG and magnetogastrography from porcines.

    Science.gov (United States)

    Irimia, Andrei; Richards, William O; Bradshaw, L Alan

    2009-11-01

    In this study, we perform a comparative study of independent component analysis (ICA) and conventional filtering (CF) for the purpose of artifact reduction from simultaneous gastric EMG and magnetogastrography (MGG). EMG/MGG data were acquired from ten anesthetized pigs by obtaining simultaneous recordings using serosal electrodes (EMG) as well as with a superconducting quantum interference device biomagnetometer (MGG). The analysis of MGG waveforms using ICA and CF indicates that ICA is superior to the CF method in its ability to extract respiration and cardiac artifacts from MGG recordings. A signal frequency analysis of ICA- and CF-processed data was also undertaken using waterfall plots, and it was determined that the two methods produce qualitatively comparable results. Through the use of simultaneous EMG/MGG, we were able to demonstrate the accuracy and trustworthiness of our results by comparison and cross-validation within the framework of a porcine model.

  9. Locomotor training with body weight support in SCI : EMG improvement is more optimally expressed at a low testing speed

    NARCIS (Netherlands)

    Meyns, P.; Van de Crommert, H. W. A. A.; Rijken, H.; van Kuppevelt, D. H. J. M.; Duysens, J.

    2014-01-01

    Study design: Case series. Objectives: To determine the optimal testing speed at which the recovery of the EMG (electromyographic) activity should be assessed during and after body weight supported (BWS) locomotor training. Setting: Tertiary hospital, Sint Maartenskliniek, Nijmegen, The Netherlands.

  10. Adaptive Admittance Control for an Ankle Exoskeleton Using an EMG-Driven Musculoskeletal Model

    Directory of Open Access Journals (Sweden)

    Shaowei Yao

    2018-04-01

    Full Text Available Various rehabilitation robots have been employed to recover the motor function of stroke patients. To improve the effect of rehabilitation, robots should promote patient participation and provide compliant assistance. This paper proposes an adaptive admittance control scheme (AACS consisting of an admittance filter, inner position controller, and electromyography (EMG-driven musculoskeletal model (EDMM. The admittance filter generates the subject's intended motion according to the joint torque estimated by the EDMM. The inner position controller tracks the intended motion, and its parameters are adjusted according to the estimated joint stiffness. Eight healthy subjects were instructed to wear the ankle exoskeleton robot, and they completed a series of sinusoidal tracking tasks involving ankle dorsiflexion and plantarflexion. The robot was controlled by the AACS and a non-adaptive admittance control scheme (NAACS at four fixed parameter levels. The tracking performance was evaluated using the jerk value, position error, interaction torque, and EMG levels of the tibialis anterior (TA and gastrocnemius (GAS. For the NAACS, the jerk value and position error increased with the parameter levels, and the interaction torque and EMG levels of the TA tended to decrease. In contrast, the AACS could maintain a moderate jerk value, position error, interaction torque, and TA EMG level. These results demonstrate that the AACS achieves a good tradeoff between accurate tracking and compliant assistance because it can produce a real-time response to stiffness changes in the ankle joint. The AACS can alleviate the conflict between accurate tracking and compliant assistance and has potential for application in robot-assisted rehabilitation.

  11. Kinematic and EMG data during underwater dolphin kick change while synchronizing with or without synchronization of kick frequency with the beat of a metronome.

    Science.gov (United States)

    Yamakawa, Keisuke Kobayashi; Shimojo, Hirofumi; Takagi, Hideki; Tsubakimoto, Shozo; Sengoku, Yasuo

    2017-10-01

    We investigated the effects of synchronizing kick frequency with the beat of a metronome on kinematic and electromyographic (EMG) parameters during the underwater dolphin kick as a pilot study related to the research that entitled " Effect of increased kick frequency on propelling efficiency and muscular co-activation during underwater dolphin kick" (Yamakawa et al., 2017) [1]. Seven collegiate female swimmers participated in this experiment. The participants conducted two underwater dolphin kick trials: swimming freely at maximum effort, and swimming while synchronizing the kick frequency of maximum effort with the beat of a metronome. The kinematic parameters during the underwater dolphin kick were calculated by 2-D motion analysis, and surface electromyographic measurements were taken from six muscles (rectus abdominis, erector spinae, rectus femoris, biceps femoris, tibialis anterior, and gastrocnemius). The results revealed no significant differences in the kinematic and EMG parameters between trials of the two swimming techniques. Therefore, the action of synchronizing the kick frequency with the beat of a metronome did not affect movement or muscle activity during the underwater dolphin kick in this experiment.

  12. Kinematic and EMG data during underwater dolphin kick change while synchronizing with or without synchronization of kick frequency with the beat of a metronome

    Directory of Open Access Journals (Sweden)

    Keisuke Kobayashi Yamakawa

    2017-10-01

    Full Text Available We investigated the effects of synchronizing kick frequency with the beat of a metronome on kinematic and electromyographic (EMG parameters during the underwater dolphin kick as a pilot study related to the research that entitled “Effect of increased kick frequency on propelling efficiency and muscular co-activation during underwater dolphin kick” (Yamakawa et al., 2017 [1]. Seven collegiate female swimmers participated in this experiment. The participants conducted two underwater dolphin kick trials: swimming freely at maximum effort, and swimming while synchronizing the kick frequency of maximum effort with the beat of a metronome. The kinematic parameters during the underwater dolphin kick were calculated by 2-D motion analysis, and surface electromyographic measurements were taken from six muscles (rectus abdominis, erector spinae, rectus femoris, biceps femoris, tibialis anterior, and gastrocnemius. The results revealed no significant differences in the kinematic and EMG parameters between trials of the two swimming techniques. Therefore, the action of synchronizing the kick frequency with the beat of a metronome did not affect movement or muscle activity during the underwater dolphin kick in this experiment.

  13. Neuromuscular interfacing: establishing an EMG-driven model for the human elbow joint.

    Science.gov (United States)

    Pau, James W L; Xie, Shane S Q; Pullan, Andrew J

    2012-09-01

    Assistive devices aim to mitigate the effects of physical disability by aiding users to move their limbs or by rehabilitating through therapy. These devices are commonly embodied by robotic or exoskeletal systems that are still in development and use the electromyographic (EMG) signal to determine user intent. Not much focus has been placed on developing a neuromuscular interface (NI) that solely relies on the EMG signal, and does not require modifications to the end user's state to enhance the signal (such as adding weights). This paper presents the development of a flexible, physiological model for the elbow joint that is leading toward the implementation of an NI, which predicts joint motion from EMG signals for both able-bodied and less-abled users. The approach uses musculotendon models to determine muscle contraction forces, a proposed musculoskeletal model to determine total joint torque, and a kinematic model to determine joint rotational kinematics. After a sensitivity analysis and tuning using genetic algorithms, subject trials yielded an average root-mean-square error of 6.53° and 22.4° for a single cycle and random cycles of movement of the elbow joint, respectively. This helps us to validate the elbow model and paves the way toward the development of an NI.

  14. Development of Hand Grip Assistive Device Control System for Old People through Electromyography (EMG Signal Acquisitions

    Directory of Open Access Journals (Sweden)

    Khamis Herman

    2017-01-01

    Full Text Available The hand grip assistive device is a glove to assist old people who suffer from hand weakness in their daily life activities. The device earlier control system only use simple on and off switch. This required old people to use both hand to activate the device. The new control system of the hand grip assistive device was developed to allow single hand operation for old people. New control system take advantages of electromyography (EMG and flex sensor which was implemented to the device. It was programmed into active and semi-active mode operation. EMG sensors were placed on the forearm to capture EMG signal of Flexor Digitorum Profundus muscle to activate the device. Flex sensor was used to indicate the finger position and placed on top of the finger. The signal from both sensors then used to control the device. The new control system allowed single hand operation and designed to prevent user from over depended on the device by activating it through moving their fingers.

  15. Relationship among the myelography, MRI and EMG in young patients with low back pain or radiating pain

    International Nuclear Information System (INIS)

    Jang, Ji Youn; Kim, Dong Hun; Park, Young Jae

    2006-01-01

    We wanted to evaluate the relationship among the myelography, magnetic resonance imaging (MRI), and electromyography (EMG) findings in young patients with low back pain, and we wanted to assess the significance of the spinal geometric measurements as well as type of disc herniation seen on MRI. Forty-four young men with lower back pain were included, and they were all clinically suspected of suffering with lumbar disc herniation. All of them underwent myelography, MRI and EMG. We measured spinal geometry including the anteroposterior diameters of the central canal and thecal sac, the interlaminar distance, the width of the lateral recess and the thickness of the ligamentum flavum, and we evaluated for root deviation as well as disc herniation on the MRIs. We compared the types of disc herniation on MRI with the myelography and EMG findings. Also, we investigated the correlation of the spinal geometric measurements on MRI with the EMG and myelography findings. The types of disc herniation on MRI were not significantly related to the myelography (ρ = 0.298) and EMG findings (ρ = 0.372). The EMG findings were not related to either the myelography findings (ρ = 0.435) or the spinal geometric measurements (ρ > 0.05) on MRI. Nerve root compression that was noted on myelography was related to the thecal sac AP diameter (ρ = 0.016) and the width of the lateral recess (ρ = 0.011). There were no correlations between myelography and the findings of root deviation on MRI (ρ = 0.052). MRI can play an excellent diagnostic role for young patients with radiculopathy or lower back pain. It could increase the diagnostic accuracy if it is used in conjunction with myelography and EMG. The narrowing of thecal sac AP diameter and the width of lateral recess rather than the type of disc herniation on MRI were well correlated with the myelography and EMG findings

  16. Power optimization in body sensor networks: the case of an autonomous wireless EMG sensor powered by PV-cells.

    Science.gov (United States)

    Penders, J; Pop, V; Caballero, L; van de Molengraft, J; van Schaijk, R; Vullers, R; Van Hoof, C

    2010-01-01

    Recent advances in ultra-low-power circuits and energy harvesters are making self-powered body sensor nodes a reality. Power optimization at the system and application level is crucial in achieving ultra-low-power consumption for the entire system. This paper reviews system-level power optimization techniques, and illustrates their impact on the case of autonomous wireless EMG monitoring. The resulting prototype, an Autonomous wireless EMG sensor power by PV-cells, is presented.

  17. Does a SLAP lesion affect shoulder muscle recruitment as measured by EMG activity during a rugby tackle?

    OpenAIRE

    Herrington Lee C; Horsley Ian G; Rolf Christer

    2010-01-01

    Abstract Background The study objective was to assess the influence of a SLAP lesion on onset of EMG activity in shoulder muscles during a front on rugby football tackle within professional rugby players. Methods Mixed cross-sectional study evaluating between and within group differences in EMG onset times. Testing was carried out within the physiotherapy department of a university sports medicine clinic. The test group consisted of 7 players with clinically diagnosed SLAP lesions, later veri...

  18. Emociones en padres y madres con hijos diagnosticados de EMG que han cometido un acto delictivo violento

    OpenAIRE

    Martínez Fenoll, Carla

    2017-01-01

    Antecedentes: El diagnóstico de enfermedad mental grave (EMG) conlleva en los familiares la aparición de diversas emociones, especialmente negativas, que se relacionan directamente con un deterioro de su calidad de vida. Cuando la EMG se relaciona con un acto delictivo violento aumenta tanto la estigmatización de las personas que la padecen, como los cuidados requeridos por sus familiares, por lo que, en estos últimos, las emociones reportadas pueden ser diferentes y particulares. Objetivos: ...

  19. Influence of different attentional focus on EMG amplitude and contraction duration during the bench press at different speeds.

    Science.gov (United States)

    Calatayud, Joaquin; Vinstrup, Jonas; Jakobsen, Markus D; Sundstrup, Emil; Colado, Juan Carlos; Andersen, Lars L

    2018-05-01

    The purpose of this study was to investigate whether using different focus affects electromyographic (EMG) amplitude and contraction duration during bench press performed at explosive and controlled speeds. Eighteen young male individuals were familiarized with the procedure and performed the one-maximum repetition (1RM) test in the first session. In the second session, participants performed the bench press exercise at 50% of the 1RM with 3 different attentional focuses (regular focus on moving the load vs contracting the pectoralis vs contracting the triceps) at 2 speed conditions (controlled vs maximal speed). During the controlled speed condition, focusing on using either the pectoralis or the triceps muscles increased pectoralis normalized EMG (nEMG) by 6% (95% CI 3-8%; p = 0.0001) and 4% nEMG (95% CI 1-7%; p = 0.0096), respectively, compared with the regular focus condition. Triceps activity was increased by 4% nEMG (95% CI 0-7%; p = 0.0308) at the controlled speed condition during the triceps focus. During the explosive speed condition, the use of different focuses had no effect. The different attentional focus resulted in comparable contraction duration for the measured muscles when the exercise was performed explosively. Using internal focus to increase EMG amplitude seems to function only during conditions of controlled speed.

  20. Locomotor training with body weight support in SCI: EMG improvement is more optimally expressed at a low testing speed.

    Science.gov (United States)

    Meyns, P; Van de Crommert, H W A A; Rijken, H; van Kuppevelt, D H J M; Duysens, J

    2014-12-01

    Case series. To determine the optimal testing speed at which the recovery of the EMG (electromyographic) activity should be assessed during and after body weight supported (BWS) locomotor training. Tertiary hospital, Sint Maartenskliniek, Nijmegen, The Netherlands. Four participants with incomplete chronic SCI were included for BWS locomotor training; one AIS-C and three AIS-D (according to the ASIA (American Spinal Injury Association) Impairment Scale or AIS). All were at least 5 years after injury. The SCI participants were trained three times a week for a period of 6 weeks. They improved their locomotor function in terms of higher walking speed, less BWS and less assistance needed. To investigate which treadmill speed for EMG assessment reflects the functional improvement most adequately, all participants were assessed weekly using the same two speeds (0.5 and 1.5 km h(-1), referred to as low and high speed, respectively) for 6 weeks. The change in root mean square EMG (RMS EMG) was assessed in four leg muscles; biceps femoris, rectus femoris, gastrocnemius medialis and tibialis anterior. The changes in RMS EMG occurred at similar phases of the step cycle for both walking conditions, but these changes were larger when the treadmill was set at a low speed (0.5 km h(-1)). Improvement in gait is feasible with BWS treadmill training even long after injury. The EMG changes after treadmill training are more optimally expressed using a low rather than a high testing treadmill speed.

  1. Reliability of surface electromyography in the assessment of paraspinal muscle fatigue: an updated systematic review.

    Science.gov (United States)

    Mohseni Bandpei, Mohammad A; Rahmani, Nahid; Majdoleslam, Basir; Abdollahi, Iraj; Ali, Shabnam Shah; Ahmad, Ashfaq

    2014-09-01

    The purpose of this study was to review the literature to determine whether surface electromyography (EMG) is a reliable tool to assess paraspinal muscle fatigue in healthy subjects and in patients with low back pain (LBP). A literature search for the period of 2000 to 2012 was performed, using PubMed, ProQuest, Science Direct, EMBASE, OVID, CINAHL, and MEDLINE databases. Electromyography, reliability, median frequency, paraspinal muscle, endurance, low back pain, and muscle fatigue were used as keywords. The literature search yielded 178 studies using the above keywords. Twelve articles were selected according to the inclusion criteria of the study. In 7 of the 12 studies, the surface EMG was only applied in healthy subjects, and in 5 studies, the reliability of surface EMG was investigated in patients with LBP or a comparison with a control group. In all of these studies, median frequency was shown to be a reliable EMG parameter to assess paraspinal muscles fatigue. There was a wide variation among studies in terms of methodology, surface EMG parameters, electrode location, procedure, and homogeneity of the study population. The results suggest that there seems to be a convincing body of evidence to support the merit of surface EMG in the assessment of paraspinal muscle fatigue in healthy subject and in patients with LBP. Copyright © 2014 National University of Health Sciences. Published by Elsevier Inc. All rights reserved.

  2. An EMG-driven exoskeleton hand robotic training device on chronic stroke subjects: task training system for stroke rehabilitation.

    Science.gov (United States)

    Ho, N S K; Tong, K Y; Hu, X L; Fung, K L; Wei, X J; Rong, W; Susanto, E A

    2011-01-01

    An exoskeleton hand robotic training device is specially designed for persons after stroke to provide training on their impaired hand by using an exoskeleton robotic hand which is actively driven by their own muscle signals. It detects the stroke person's intention using his/her surface electromyography (EMG) signals from the hemiplegic side and assists in hand opening or hand closing functional tasks. The robotic system is made up of an embedded controller and a robotic hand module which can be adjusted to fit for different finger length. Eight chronic stroke subjects had been recruited to evaluate the effects of this device. The preliminary results showed significant improvement in hand functions (ARAT) and upper limb functions (FMA) after 20 sessions of robot-assisted hand functions task training. With the use of this light and portable robotic device, stroke patients can now practice more easily for the opening and closing of their hands at their own will, and handle functional daily living tasks at ease. A video is included together with this paper to give a demonstration of the hand robotic system on chronic stroke subjects and it will be presented in the conference. © 2011 IEEE

  3. Comparison of algorithms to quantify muscle fatigue in upper limb muscles based on sEMG signals.

    Science.gov (United States)

    Kahl, Lorenz; Hofmann, Ulrich G

    2016-11-01

    This work compared the performance of six different fatigue detection algorithms quantifying muscle fatigue based on electromyographic signals. Surface electromyography (sEMG) was obtained by an experiment from upper arm contractions at three different load levels from twelve volunteers. Fatigue detection algorithms mean frequency (MNF), spectral moments ratio (SMR), the wavelet method WIRM1551, sample entropy (SampEn), fuzzy approximate entropy (fApEn) and recurrence quantification analysis (RQA%DET) were calculated. The resulting fatigue signals were compared considering the disturbances incorporated in fatiguing situations as well as according to the possibility to differentiate the load levels based on the fatigue signals. Furthermore we investigated the influence of the electrode locations on the fatigue detection quality and whether an optimized channel set is reasonable. The results of the MNF, SMR, WIRM1551 and fApEn algorithms fell close together. Due to the small amount of subjects in this study significant differences could not be found. In terms of disturbances the SMR algorithm showed a slight tendency to out-perform the others. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

  4. Surface electromyography physiology, engineering and applications

    CERN Document Server

    Farina, Dario

    2016-01-01

    The book presents a quantitative approach to the study and use of noninvasively detected electromyographic (EMG) signals, as well as their numerous applications in various aspects of the life sciences. Surface Electromyography: Physiology, Engineering, and Applications is an update of Electromyography: Physiology, Engineering, and Noninvasive Applications (Wiley-IEEE Press, 2004) and focuses on the developments that have taken place over the last decade. The first nine chapters deal with the generation, detection, understanding, interpretation, and modeling of EMG signals. Detection technology, with particular focus on EMG imaging techniques that are based on two-dimensional electrode arrays are also included in the first half of the book. The latter 11 chapters deal with applications, which range fro monitoring muscle fatigue, electrically elicited contractions, posture analysis, prevention of work-related and child-delivery-related neuromuscular disorders, ergonomics, movement analysis, physical therapy, ex...

  5. A computational model to investigate the effect of pennation angle on surface electromyogram of Tibialis Anterior.

    Directory of Open Access Journals (Sweden)

    Diptasree Maitra Ghosh

    Full Text Available This study has described and experimentally validated the differential electrodes surface electromyography (sEMG model for tibialis anterior muscles during isometric contraction. This model has investigated the effect of pennation angle on the simulated sEMG signal. The results show that there is no significant effect of pennation angle in the range 0° to 20° to the single fibre action potential shape recorded on the skin surface. However, the changes with respect to pennation angle are observed in sEMG amplitude, frequency and fractal dimension. It is also observed that at different levels of muscle contractions there is similarity in the relationships with Root Mean Square, Median Frequency, and Fractal Dimension of the recorded and simulated sEMG signals.

  6. A Novel Feature Optimization for Wearable Human-Computer Interfaces Using Surface Electromyography Sensors

    Directory of Open Access Journals (Sweden)

    Han Sun

    2018-03-01

    Full Text Available The novel human-computer interface (HCI using bioelectrical signals as input is a valuable tool to improve the lives of people with disabilities. In this paper, surface electromyography (sEMG signals induced by four classes of wrist movements were acquired from four sites on the lower arm with our designed system. Forty-two features were extracted from the time, frequency and time-frequency domains. Optimal channels were determined from single-channel classification performance rank. The optimal-feature selection was according to a modified entropy criteria (EC and Fisher discrimination (FD criteria. The feature selection results were evaluated by four different classifiers, and compared with other conventional feature subsets. In online tests, the wearable system acquired real-time sEMG signals. The selected features and trained classifier model were used to control a telecar through four different paradigms in a designed environment with simple obstacles. Performance was evaluated based on travel time (TT and recognition rate (RR. The results of hardware evaluation verified the feasibility of our acquisition systems, and ensured signal quality. Single-channel analysis results indicated that the channel located on the extensor carpi ulnaris (ECU performed best with mean classification accuracy of 97.45% for all movement’s pairs. Channels placed on ECU and the extensor carpi radialis (ECR were selected according to the accuracy rank. Experimental results showed that the proposed FD method was better than other feature selection methods and single-type features. The combination of FD and random forest (RF performed best in offline analysis, with 96.77% multi-class RR. Online results illustrated that the state-machine paradigm with a 125 ms window had the highest maneuverability and was closest to real-life control. Subjects could accomplish online sessions by three sEMG-based paradigms, with average times of 46.02, 49.06 and 48.08 s

  7. The effectiveness of FES-evoked EMG potentials to assess muscle force and fatigue in individuals with spinal cord injury.

    Science.gov (United States)

    Ibitoye, Morufu Olusola; Estigoni, Eduardo H; Hamzaid, Nur Azah; Wahab, Ahmad Khairi Abdul; Davis, Glen M

    2014-07-14

    The evoked electromyographic signal (eEMG) potential is the standard index used to monitor both electrical changes within the motor unit during muscular activity and the electrical patterns during evoked contraction. However, technical and physiological limitations often preclude the acquisition and analysis of the signal especially during functional electrical stimulation (FES)-evoked contractions. Hence, an accurate quantification of the relationship between the eEMG potential and FES-evoked muscle response remains elusive and continues to attract the attention of researchers due to its potential application in the fields of biomechanics, muscle physiology, and rehabilitation science. We conducted a systematic review to examine the effectiveness of eEMG potentials to assess muscle force and fatigue, particularly as a biofeedback descriptor of FES-evoked contractions in individuals with spinal cord injury. At the outset, 2867 citations were identified and, finally, fifty-nine trials met the inclusion criteria. Four hypotheses were proposed and evaluated to inform this review. The results showed that eEMG is effective at quantifying muscle force and fatigue during isometric contraction, but may not be effective during dynamic contractions including cycling and stepping. Positive correlation of up to r = 0.90 (p peak-to-peak amplitude of the eEMG and the decline in the force output during fatiguing isometric contractions has been reported. In the available prediction models, the performance index of the eEMG signal to estimate the generated muscle force ranged from 3.8% to 34% for 18 s to 70 s ahead of the actual muscle force generation. The strength and inherent limitations of the eEMG signal to assess muscle force and fatigue were evident from our findings with implications in clinical management of spinal cord injury (SCI) population.

  8. The Effectiveness of FES-Evoked EMG Potentials to Assess Muscle Force and Fatigue in Individuals with Spinal Cord Injury

    Directory of Open Access Journals (Sweden)

    Morufu Olusola Ibitoye

    2014-07-01

    Full Text Available The evoked electromyographic signal (eEMG potential is the standard index used to monitor both electrical changes within the motor unit during muscular activity and the electrical patterns during evoked contraction. However, technical and physiological limitations often preclude the acquisition and analysis of the signal especially during functional electrical stimulation (FES-evoked contractions. Hence, an accurate quantification of the relationship between the eEMG potential and FES-evoked muscle response remains elusive and continues to attract the attention of researchers due to its potential application in the fields of biomechanics, muscle physiology, and rehabilitation science. We conducted a systematic review to examine the effectiveness of eEMG potentials to assess muscle force and fatigue, particularly as a biofeedback descriptor of FES-evoked contractions in individuals with spinal cord injury. At the outset, 2867 citations were identified and, finally, fifty-nine trials met the inclusion criteria. Four hypotheses were proposed and evaluated to inform this review. The results showed that eEMG is effective at quantifying muscle force and fatigue during isometric contraction, but may not be effective during dynamic contractions including cycling and stepping. Positive correlation of up to r = 0.90 (p < 0.05 between the decline in the peak-to-peak amplitude of the eEMG and the decline in the force output during fatiguing isometric contractions has been reported. In the available prediction models, the performance index of the eEMG signal to estimate the generated muscle force ranged from 3.8% to 34% for 18 s to 70 s ahead of the actual muscle force generation. The strength and inherent limitations of the eEMG signal to assess muscle force and fatigue were evident from our findings with implications in clinical management of spinal cord injury (SCI population.

  9. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  10. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...... that call for inquiries into the theoretical foundation of bibliographic classification theory....

  11. Detection of surface electromyography recording time interval without muscle fatigue effect for biceps brachii muscle during maximum voluntary contraction.

    Science.gov (United States)

    Soylu, Abdullah Ruhi; Arpinar-Avsar, Pinar

    2010-08-01

    The effects of fatigue on maximum voluntary contraction (MVC) parameters were examined by using force and surface electromyography (sEMG) signals of the biceps brachii muscles (BBM) of 12 subjects. The purpose of the study was to find the sEMG time interval of the MVC recordings which is not affected by the muscle fatigue. At least 10s of force and sEMG signals of BBM were recorded simultaneously during MVC. The subjects reached the maximum force level within 2s by slightly increasing the force, and then contracted the BBM maximally. The time index of each sEMG and force signal were labeled with respect to the time index of the maximum force (i.e. after the time normalization, each sEMG or force signal's 0s time index corresponds to maximum force point). Then, the first 8s of sEMG and force signals were divided into 0.5s intervals. Mean force, median frequency (MF) and integrated EMG (iEMG) values were calculated for each interval. Amplitude normalization was performed by dividing the force signals to their mean values of 0s time intervals (i.e. -0.25 to 0.25s). A similar amplitude normalization procedure was repeated for the iEMG and MF signals. Statistical analysis (Friedman test with Dunn's post hoc test) was performed on the time and amplitude normalized signals (MF, iEMG). Although the ANOVA results did not give statistically significant information about the onset of the muscle fatigue, linear regression (mean force vs. time) showed a decreasing slope (Pearson-r=0.9462, pfatigue starts after the 0s time interval as the muscles cannot attain their peak force levels. This implies that the most reliable interval for MVC calculation which is not affected by the muscle fatigue is from the onset of the EMG activity to the peak force time. Mean, SD, and range of this interval (excluding 2s gradual increase time) for 12 subjects were 2353, 1258ms and 536-4186ms, respectively. Exceeding this interval introduces estimation errors in the maximum amplitude calculations

  12. Linear methods for reducing EMG contamination in peripheral nerve motor decodes.

    Science.gov (United States)

    Kagan, Zachary B; Wendelken, Suzanne; Page, David M; Davis, Tyler; Hutchinson, Douglas T; Clark, Gregory A; Warren, David J

    2016-08-01

    Signals recorded from the peripheral nervous system (PNS) with high channel count penetrating microelectrode arrays, such as the Utah Slanted Electrode Array (USEA), often have electromyographic (EMG) signals contaminating the neural signal. This common-mode signal source may prevent single neural units from successfully being detected, thus hindering motor decode algorithms. Reducing this EMG contamination may lead to more accurate motor decode performance. A virtual reference (VR), created by a weighted linear combination of signals from a subset of all available channels, can be used to reduce this EMG contamination. Four methods of determining individual channel weights and six different methods of selecting subsets of channels were investigated (24 different VR types in total). The methods of determining individual channel weights were equal weighting, regression-based weighting, and two different proximity-based weightings. The subsets of channels were selected by a radius-based criteria, such that a channel was included if it was within a particular radius of inclusion from the target channel. These six radii of inclusion were 1.5, 2.9, 3.2, 5, 8.4, and 12.8 electrode-distances; the 12.8 electrode radius includes all USEA electrodes. We found that application of a VR improves the detectability of neural events via increasing the SNR, but we found no statistically meaningful difference amongst the VR types we examined. The computational complexity of implementation varies with respect to the method of determining channel weights and the number of channels in a subset, but does not correlate with VR performance. Hence, we examined the computational costs of calculating and applying the VR and based on these criteria, we recommend an equal weighting method of assigning weights with a 3.2 electrode-distance radius of inclusion. Further, we found empirically that application of the recommended VR will require less than 1 ms for 33.3 ms of data from one USEA.

  13. The Assessment of Muscular Effort, Fatigue, and Physiological Adaptation Using EMG and Wavelet Analysis.

    Science.gov (United States)

    Graham, Ryan B; Wachowiak, Mark P; Gurd, Brendon J

    2015-01-01

    Peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α) is a transcription factor co-activator that helps coordinate mitochondrial biogenesis within skeletal muscle following exercise. While evidence gleaned from submaximal exercise suggests that intracellular pathways associated with the activation of PGC-1α, as well as the expression of PGC-1α itself are activated to a greater extent following higher intensities of exercise, we have recently shown that this effect does not extend to supramaximal exercise, despite corresponding increases in muscle activation amplitude measured with electromyography (EMG). Spectral analyses of EMG data may provide a more in-depth assessment of changes in muscle electrophysiology occurring across different exercise intensities, and therefore the goal of the present study was to apply continuous wavelet transforms (CWTs) to our previous data to comprehensively evaluate: 1) differences in muscle electrophysiological properties at different exercise intensities (i.e. 73%, 100%, and 133% of peak aerobic power), and 2) muscular effort and fatigue across a single interval of exercise at each intensity, in an attempt to shed mechanistic insight into our previous observations that the increase in PGC-1α is dissociated from exercise intensity following supramaximal exercise. In general, the CWTs revealed that localized muscle fatigue was only greater than the 73% condition in the 133% exercise intensity condition, which directly matched the work rate results. Specifically, there were greater drop-offs in frequency, larger changes in burst power, as well as greater changes in burst area under this intensity, which were already observable during the first interval. As a whole, the results from the present study suggest that supramaximal exercise causes extreme localized muscular fatigue, and it is possible that the blunted PGC-1α effects observed in our previous study are the result of fatigue-associated increases in

  14. The Assessment of Muscular Effort, Fatigue, and Physiological Adaptation Using EMG and Wavelet Analysis.

    Directory of Open Access Journals (Sweden)

    Ryan B Graham

    Full Text Available Peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α is a transcription factor co-activator that helps coordinate mitochondrial biogenesis within skeletal muscle following exercise. While evidence gleaned from submaximal exercise suggests that intracellular pathways associated with the activation of PGC-1α, as well as the expression of PGC-1α itself are activated to a greater extent following higher intensities of exercise, we have recently shown that this effect does not extend to supramaximal exercise, despite corresponding increases in muscle activation amplitude measured with electromyography (EMG. Spectral analyses of EMG data may provide a more in-depth assessment of changes in muscle electrophysiology occurring across different exercise intensities, and therefore the goal of the present study was to apply continuous wavelet transforms (CWTs to our previous data to comprehensively evaluate: 1 differences in muscle electrophysiological properties at different exercise intensities (i.e. 73%, 100%, and 133% of peak aerobic power, and 2 muscular effort and fatigue across a single interval of exercise at each intensity, in an attempt to shed mechanistic insight into our previous observations that the increase in PGC-1α is dissociated from exercise intensity following supramaximal exercise. In general, the CWTs revealed that localized muscle fatigue was only greater than the 73% condition in the 133% exercise intensity condition, which directly matched the work rate results. Specifically, there were greater drop-offs in frequency, larger changes in burst power, as well as greater changes in burst area under this intensity, which were already observable during the first interval. As a whole, the results from the present study suggest that supramaximal exercise causes extreme localized muscular fatigue, and it is possible that the blunted PGC-1α effects observed in our previous study are the result of fatigue

  15. Two cases of childhood narcolepsy mimicking epileptic seizures in video-EEG/EMG.

    Science.gov (United States)

    Yanagishita, Tomoe; Ito, Susumu; Ohtani, Yui; Eto, Kaoru; Kanbayashi, Takashi; Oguni, Hirokazu; Nagata, Satoru

    2018-06-06

    Narcolepsy is characterized by excessive sleepiness, hypnagogic hallucinations, and sleep paralysis, and can occur with or without cataplexy. Here, we report two children with narcolepsy presenting with cataplexy mimicking epileptic seizures as determined by long-term video-electroencephalography (EEG) and electromyography (EMG) monitoring. Case 1 was a 15-year-old girl presenting with recurrent episodes of "convulsions" and loss of consciousness, who was referred to our hospital with a diagnosis of epilepsy showing "convulsions" and "complex partial seizures". The long-term video-polygraph showed a clonic attack lasting for 15 s, which corresponded to 1-2 Hz with interruption of mentalis EMG discharges lasting for 70-300 ms without any EEG changes. Narcolepsy was suspected due to the attack induced by hearty laughs and the presence of sleep attacks, and confirmed by low orexin levels in cerebrospinal fluid (CSF). Case 2 was an 11-year-old girl presenting with recurrent episodes of myoclonic attacks simultaneously with dropping objects immediately after hearty laughs, in addition to sleep attacks, hypnagogic hallucinations, and sleep paralysis. The long-term video-polygraph showed a subtle attack, characterized by dropping chopsticks from her hand, which corresponded to an interruption of ongoing deltoid EMG discharges lasting 140 ms without any EEG changes. A diagnosis of narcolepsy was confirmed by the low orexin levels in CSF. These cases demonstrate that children with narcolepsy may have attacks of cataplexy that resemble clonic or myoclonic seizures. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

  16. Human-machine interfaces based on EMG and EEG applied to robotic systems

    Directory of Open Access Journals (Sweden)

    Sarcinelli-Filho Mario

    2008-03-01

    Full Text Available Abstract Background Two different Human-Machine Interfaces (HMIs were developed, both based on electro-biological signals. One is based on the EMG signal and the other is based on the EEG signal. Two major features of such interfaces are their relatively simple data acquisition and processing systems, which need just a few hardware and software resources, so that they are, computationally and financially speaking, low cost solutions. Both interfaces were applied to robotic systems, and their performances are analyzed here. The EMG-based HMI was tested in a mobile robot, while the EEG-based HMI was tested in a mobile robot and a robotic manipulator as well. Results Experiments using the EMG-based HMI were carried out by eight individuals, who were asked to accomplish ten eye blinks with each eye, in order to test the eye blink detection algorithm. An average rightness rate of about 95% reached by individuals with the ability to blink both eyes allowed to conclude that the system could be used to command devices. Experiments with EEG consisted of inviting 25 people (some of them had suffered cases of meningitis and epilepsy to test the system. All of them managed to deal with the HMI in only one training session. Most of them learnt how to use such HMI in less than 15 minutes. The minimum and maximum training times observed were 3 and 50 minutes, respectively. Conclusion Such works are the initial parts of a system to help people with neuromotor diseases, including those with severe dysfunctions. The next steps are to convert a commercial wheelchair in an autonomous mobile vehicle; to implement the HMI onboard the autonomous wheelchair thus obtained to assist people with motor diseases, and to explore the potentiality of EEG signals, making the EEG-based HMI more robust and faster, aiming at using it to help individuals with severe motor dysfunctions.

  17. Real-time muscle state estimation from EMG signals during isometric contractions using Kalman filters.

    Science.gov (United States)

    Menegaldo, Luciano L

    2017-12-01

    State-space control of myoelectric devices and real-time visualization of muscle forces in virtual rehabilitation require measuring or estimating muscle dynamic states: neuromuscular activation, tendon force and muscle length. This paper investigates whether regular (KF) and extended Kalman filters (eKF), derived directly from Hill-type muscle mechanics equations, can be used as real-time muscle state estimators for isometric contractions using raw electromyography signals (EMG) as the only available measurement. The estimators' amplitude error, computational cost, filtering lags and smoothness are compared with usual EMG-driven analysis, performed offline, by integrating the nonlinear Hill-type muscle model differential equations (offline simulations-OS). EMG activity of the three triceps surae components (soleus, gastrocnemius medialis and gastrocnemius lateralis), in three torque levels, was collected for ten subjects. The actualization interval (AI) between two updates of the KF and eKF was also varied. The results show that computational costs are significantly reduced (70x for KF and 17[Formula: see text] for eKF). The filtering lags presented sharp linear relationships with the AI (0-300 ms), depending on the state and activation level. Under maximum excitation, amplitude errors varied in the range 10-24% for activation, 5-8% for tendon force and 1.4-1.8% for muscle length, reducing linearly with the excitation level. Smoothness, measured by the ratio between the average standard variations of KF/eKF and OS estimations, was greatly reduced for activation but converged exponentially to 1 for the other states by increasing AI. Compared to regular KF, extended KF does not seem to improve estimation accuracy significantly. Depending on the particular application requirements, the most appropriate KF actualization interval can be selected.

  18. Hazard classification methodology

    International Nuclear Information System (INIS)

    Brereton, S.J.

    1996-01-01

    This document outlines the hazard classification methodology used to determine the hazard classification of the NIF LTAB, OAB, and the support facilities on the basis of radionuclides and chemicals. The hazard classification determines the safety analysis requirements for a facility

  19. The effects of athletics training on isometric strength and EMG activity in adolescent athletes

    OpenAIRE

    NIKOLAOS AGGELOUSIS; NIKOLAOS MANTZOURANIS; THEOPHILOS PILIANIDIS; GEORGIOS DASTERIDIS

    2012-01-01

    The aim of this study was to evaluate the effect of two different training programs on electromyographic activity (EMG), isometric strength and quadriceps hypertrophy in track and field athletes. 27 male adolescents athletes were divided in three (3) groups of nine (9), the Neuromuscular Group (NeuroGr), the Hypertrophy Group (HyperGr) and the Control Group (ControlG). The participants in both NeuroGr and HyperGr trained 3 times per week for 8 weeks while the athletes’of ControlGr did not tak...

  20. Removal of EMG and ECG artifacts from EEG based on wavelet transform and ICA.

    Science.gov (United States)

    Zhou, Weidong; Gotman, Jean

    2004-01-01

    In this study, the methods of wavelet threshold de-noising and independent component analysis (ICA) are introduced. ICA is a novel signal processing technique based on high order statistics, and is used to separate independent components from measurements. The extended ICA algorithm does not need to calculate the higher order statistics, converges fast, and can be used to separate subGaussian and superGaussian sources. A pre-whitening procedure is performed to de-correlate the mixed signals before extracting sources. The experimental results indicate the electromyogram (EMG) and electrocardiograph (ECG) artifacts in electroencephalograph (EEG) can be removed by a combination of wavelet threshold de-noising and ICA.

  1. Development of Hand Grip Assistive Device Control System for Old People through Electromyography (EMG) Signal Acquisitions

    OpenAIRE

    Khamis Herman; Mohamaddan Shahrol; Komeda Takashi; Alias Aidil Azli; Tanjong Shirley Jonathan; Julai Norhuzaimin; Hashim Nurul ‘Izzati

    2017-01-01

    The hand grip assistive device is a glove to assist old people who suffer from hand weakness in their daily life activities. The device earlier control system only use simple on and off switch. This required old people to use both hand to activate the device. The new control system of the hand grip assistive device was developed to allow single hand operation for old people. New control system take advantages of electromyography (EMG) and flex sensor which was implemented to the device. It wa...

  2. A COMPARATIVE STUDY OF EFFICACY OF EMG BIO-FEEDBACK AND PROGRESSIVE MUSCULAR RELAXATION IN TENSION HEADACHE1

    Science.gov (United States)

    Gada, M.T.

    1984-01-01

    SUMMARY The aim of the present study was to find out efficacy of frontalis EMG Biofeedback therapy, deep muscular relaxation therapy and compare the efficacy of both in cases of tension headache. During two week basal-data recording period all patients were taught deep muscular relaxation by Jacobson′s technique. Simultaneously patients were instructed to keep headache diary. Headache diary yielded three different parameters a) number of headache-free days per week, b) peak headache intensity (or each week and c) average daily headache activity score per week. These parameters were used to find out therapeutic efficacy of each treatment. Patients were randomly divided in two groups. EMG Biofeedback group was given frontalis EMG feedback through EMG J 33 muscle trainer of Cyborg Corporation (U.S.A.). Patients in each group were given 20 sessions (two sessions per week); each session lasting 30 minutes. Patients were instructed to practice at least one 30 minute session of relaxation at home. The data were subjected to statistical calculation. The results indicate that frontalis EMG Biofeedback therapy and deep muscle relaxation therapy are significantly effective in cases of tension headache. Both treatments are equally effective. The findings are discussed in relation to Indian situation. PMID:21965970

  3. A comparative study of efficacy of emg bio-feedback and progressive muscular relaxation in tension headache.

    Science.gov (United States)

    Gada, M T

    1984-04-01

    The aim of the present study was to find out efficacy of frontalis EMG Biofeedback therapy, deep muscular relaxation therapy and compare the efficacy of both in cases of tension headache. During two week basal-data recording period all patients were taught deep muscular relaxation by Jacobson's technique. Simultaneously patients were instructed to keep headache diary. Headache diary yielded three different parameters a) number of headache-free days per week, b) peak headache intensity (or each week and c) average daily headache activity score per week. These parameters were used to find out therapeutic efficacy of each treatment. Patients were randomly divided in two groups. EMG Biofeedback group was given frontalis EMG feedback through EMG J 33 muscle trainer of Cyborg Corporation (U.S.A.). Patients in each group were given 20 sessions (two sessions per week); each session lasting 30 minutes. Patients were instructed to practice at least one 30 minute session of relaxation at home. The data were subjected to statistical calculation. The results indicate that frontalis EMG Biofeedback therapy and deep muscle relaxation therapy are significantly effective in cases of tension headache. Both treatments are equally effective. The findings are discussed in relation to Indian situation.

  4. Electromyography (EMG) signal recognition using combined discrete wavelet transform based adaptive neuro-fuzzy inference systems (ANFIS)

    Science.gov (United States)

    Arozi, Moh; Putri, Farika T.; Ariyanto, Mochammad; Khusnul Ari, M.; Munadi, Setiawan, Joga D.

    2017-01-01

    People with disabilities are increasing from year to year either due to congenital factors, sickness, accident factors and war. One form of disability is the case of interruptions of hand function. The condition requires and encourages the search for solutions in the form of creating an artificial hand with the ability as a human hand. The development of science in the field of neuroscience currently allows the use of electromyography (EMG) to control the motion of artificial prosthetic hand into the necessary use of EMG as an input signal to control artificial prosthetic hand. This study is the beginning of a significant research planned in the development of artificial prosthetic hand with EMG signal input. This initial research focused on the study of EMG signal recognition. Preliminary results show that the EMG signal recognition using combined discrete wavelet transform and Adaptive Neuro-Fuzzy Inference System (ANFIS) produces accuracy 98.3 % for training and 98.51% for testing. Thus the results can be used as an input signal for Simulink block diagram of a prosthetic hand that will be developed on next study. The research will proceed with the construction of artificial prosthetic hand along with Simulink program controlling and integrating everything into one system.

  5. Synergy of EMG patterns in gait as an objective measure of muscle selectivity in children with spastic cerebral palsy.

    Science.gov (United States)

    Zwaan, Esther; Becher, Jules G; Harlaar, Jaap

    2012-01-01

    Selective motor control (SMC) is an important determinant of functioning in cerebral palsy (CP). Currently its assessment is based on subjective clinical tests with a low sensitivity. Electromyography (EMG) profiles during gait represent muscle coordination and might be used to assess SMC. EMG measurements during gait were processed into a measure of extensor synergy and thigh synergy. This was obtained in two groups of children with CP, and 30 typically developing children. Extensor synergy in CP was higher (0.95) than in healthy children (0.77), thigh synergy was almost equal in both groups. GMFM scores in the first group of 39 children with CP did not correlate to EMG based synergy measures. In a second group of 38 children with CP, a clear relation of clinical SMC score with extensor synergy was found, but only a weak relation with thigh synergy. Although an extensor synergy was validated at group level, our results present no convincing evidence for the use of EMG during gait to assess SMC in individual subjects with CP. Since gait involves both synergistic and selective contractions, the inherent motor control properties of this task will not allow for an assessment of selectivity comparable to the ability to perform isolated movements. Nevertheless, our results support the sensitive nature of EMG to represent an aberrant motor control in CP. Copyright © 2011 Elsevier B.V. All rights reserved.

  6. Experimental Study of Real-Time Classification of 17 Voluntary Movements for Multi-Degree Myoelectric Prosthetic Hand

    Directory of Open Access Journals (Sweden)

    Trongmun Jiralerspong

    2017-11-01

    Full Text Available The myoelectric prosthetic hand is a powerful tool developed to help people with upper limb loss restore the functions of a biological hand. Recognizing multiple hand motions from only a few electromyography (EMG sensors is one of the requirements for the development of prosthetic hands with high level of usability. This task is highly challenging because both classification rate and misclassification rate worsen with additional hand motions. This paper presents a signal processing technique that uses spectral features and an artificial neural network to classify 17 voluntary movements from EMG signals. The main highlight will be on the use of a small set of low-cost EMG sensor for classification of a reasonably large number of hand movements. The aim of this work is to extend the capabilities to recognize and produce multiple movements beyond what is currently feasible. This work will also show and discuss about how tailoring the number of hand motions for a specific task can help develop a more reliable prosthetic hand system. Online classification experiments have been conducted on seven male and five female participants to evaluate the validity of the proposed method. The proposed algorithm achieves an overall correct classification rate of up to 83%, thus, demonstrating the potential to classify 17 movements from 6 EMG sensors. Furthermore, classifying 9 motions using this method could achieve an accuracy of up to 92%. These results show that if the prosthetic hand is intended for a specific task, limiting the number of motions can significantly increase the performance and usability.

  7. Analysis of EMG temporal parameters from the tibialis anterior during hemiparetic gait

    International Nuclear Information System (INIS)

    Bonell, Claudia E; Cherniz, AnalIa S; Tabernig, Carolina B

    2007-01-01

    Functional electrical stimulation is a rehabilitation technique used to restore the motor muscular function by means of electrical stimulus commanded by a trigger signal under volitional control. In order to enhance the motor rehabilitation, a more convenient control signal may be provided by the same muscle that is being stimulated. For example, the tibialis anterior (TA) in the applications of foot drop correction could be used. This work presents the statistical analysis of the root mean square (RMS) and the absolute mean value (VMA) of the TA electromyogram (EMG) signal computed from different phases of the gait cycle related with increases/decreases stages of muscle activity. The EMG records of 40 strides of 2 subjects with hemiparesia were processed. The RMS and VMA parameters allow distinguishing the oscillation phase from the other analyzed intervals, but they present significant spreading of mean values. This led to conclude that it is possible to use these parameters to identify the start of TA muscle activity, but altogether with other parameter or sensor that would reduce the number of false positives

  8. A battery-free multichannel digital neural/EMG telemetry system for flying insects.

    Science.gov (United States)

    Thomas, Stewart J; Harrison, Reid R; Leonardo, Anthony; Reynolds, Matthew S

    2012-10-01

    This paper presents a digital neural/EMG telemetry system small enough and lightweight enough to permit recording from insects in flight. It has a measured flight package mass of only 38 mg. This system includes a single-chip telemetry integrated circuit (IC) employing RF power harvesting for battery-free operation, with communication via modulated backscatter in the UHF (902-928 MHz) band. An on-chip 11-bit ADC digitizes 10 neural channels with a sampling rate of 26.1 kSps and 4 EMG channels at 1.63 kSps, and telemeters this data wirelessly to a base station. The companion base station transceiver includes an RF transmitter of +36 dBm (4 W) output power to wirelessly power the telemetry IC, and a digital receiver with a sensitivity of -70 dBm for 10⁻⁵ BER at 5.0 Mbps to receive the data stream from the telemetry IC. The telemetry chip was fabricated in a commercial 0.35 μ m 4M1P (4 metal, 1 poly) CMOS process. The die measures 2.36 × 1.88 mm, is 250 μm thick, and is wire bonded into a flex circuit assembly measuring 4.6 × 6.8 mm.

  9. Analysis of EMG temporal parameters from the tibialis anterior during hemiparetic gait

    Energy Technology Data Exchange (ETDEWEB)

    Bonell, Claudia E; Cherniz, AnalIa S; Tabernig, Carolina B [Laboratorio de Ingenieria de Rehabilitacion e Investigaciones Neuromusculares y Sensoriales, Facultad de Ingenieria, UNER, Oro Verde (Argentina)

    2007-11-15

    Functional electrical stimulation is a rehabilitation technique used to restore the motor muscular function by means of electrical stimulus commanded by a trigger signal under volitional control. In order to enhance the motor rehabilitation, a more convenient control signal may be provided by the same muscle that is being stimulated. For example, the tibialis anterior (TA) in the applications of foot drop correction could be used. This work presents the statistical analysis of the root mean square (RMS) and the absolute mean value (VMA) of the TA electromyogram (EMG) signal computed from different phases of the gait cycle related with increases/decreases stages of muscle activity. The EMG records of 40 strides of 2 subjects with hemiparesia were processed. The RMS and VMA parameters allow distinguishing the oscillation phase from the other analyzed intervals, but they present significant spreading of mean values. This led to conclude that it is possible to use these parameters to identify the start of TA muscle activity, but altogether with other parameter or sensor that would reduce the number of false positives.

  10. Kinematic, kinetic and EMG analysis of four front crawl flip turn techniques.

    Science.gov (United States)

    Pereira, Suzana Matheus; Ruschel, Caroline; Hubert, Marcel; Machado, Leandro; Roesler, Helio; Fernandes, Ricardo Jorge; Vilas-Boas, João Paulo

    2015-01-01

    This study aimed to analyse the kinematic, kinetic and electromyographic characteristics of four front crawl flip turn technique variants. The variants distinguished from each other by differences in body position (i.e., dorsal, lateral, ventral) during rolling, wall support, pushing and gliding phases. Seventeen highly trained swimmers (17.9 ± 3.2 years old) participated in interventional sessions and performed three trials of each variant, being monitored with a 3-D video system, a force platform and an electromyography (EMG) system. Studied variables: rolling time and distance, wall support time, push-off time, peak force and horizontal impulse at wall support and push-off, centre of mass horizontal velocity at the end of the push-off, gliding time, centre of mass depth, distance, average and final velocity during gliding, total turn time and electrical activity of Gastrocnemius Medialis, Tibialis Anterior, Biceps Femoris and Vastus Lateralis muscles. Depending on the variant, total turn time ranged from 2.37 ± 0.32 to 2.43 ± 0.33 s, push-off force from 1.86 ± 0.33 to 1.92 ± 0.26 BW and centre of mass velocity during gliding from 1.78 ± 0.21 to 1.94 ± 0.22 m · s(-1). The variants were not distinguishable in terms of kinematical, kinetic and EMG parameters during the rolling, wall support, pushing and gliding phases.

  11. Cortico-muscular coherence on artifact corrected EEG-EMG data recorded with a MRI scanner.

    Science.gov (United States)

    Muthuraman, M; Galka, A; Hong, V N; Heute, U; Deuschl, G; Raethjen, J

    2013-01-01

    Simultaneous recording of electroencephalogram (EEG) and electromyogram (EMG) with magnetic resonance imaging (MRI) provides great potential for studying human brain activity with high temporal and spatial resolution. But, due to the MRI, the recorded signals are contaminated with artifacts. The correction of these artifacts is important to use these signals for further spectral analysis. The coherence can reveal the cortical representation of peripheral muscle signal in particular motor tasks, e.g. finger movements. The artifact correction of these signals was done by two different algorithms the Brain vision analyzer (BVA) and the Matlab FMRIB plug-in for EEGLAB. The Welch periodogram method was used for estimating the cortico-muscular coherence. Our analysis revealed coherence with a frequency of 5Hz in the contralateral side of the brain. The entropy is estimated for the calculated coherence to get the distribution of coherence in the scalp. The significance of the paper is to identify the optimal algorithm to rectify the MR artifacts and as a first step to use both these signals EEG and EMG in conjunction with MRI for further studies.

  12. Real Time Hand Motion Reconstruction System for Trans-Humeral Amputees Using EEG and EMG

    Directory of Open Access Journals (Sweden)

    Jacobo Fernandez-Vargas

    2016-08-01

    Full Text Available Predicting a hand’s position using only biosignals is a complex problem that has not been completely solved. The only reliable solutions currently available require invasive surgery. The attempts using non-invasive technologies are rare, and usually have led to lower correlation values between the real and the reconstructed position than those required for real-world applications. In this study, we propose a solution for reconstructing the hand’s position in three dimensions using EEG and EMG to detect from the shoulder area. This approach would be valid for most trans-humeral amputees. In order to find the best solution, we tested four different architectures for the system based on artificial neural networks. Our results show that it is possible to reconstruct the hand’s motion trajectory with a correlation value up to 0.809 compared to a typical value in the literature of 0.6. We also demonstrated that both EEG and EMG contribute jointly to the motion reconstruction. Furthermore, we discovered that the system architectures do not change the results radically. In addition, our results suggest that different motions may have different brain activity patterns that could be detected through EEG. Finally, we suggest a method to study non-linear relations in the brain through the EEG signals, which may lead to a more accurate system.

  13. Schedule-induced masseter EMG in facial pain subjects vs. no-pain controls.

    Science.gov (United States)

    Gramling, S E; Grayson, R L; Sullivan, T N; Schwartz, S

    1997-02-01

    Empirical reports suggest that oral habits (e.g., teeth clenching) may be behavioral mediators linking stress to muscle hyperreactivity and the development of facial pain. Another report suggests that excessive behavioral adjuncts develop in conjunction with fixed-time stimulus presentation. The present study assessed the extent to which the oral habits exhibited by facial pain patients are schedule-induced. Subjects with Temporomandibular Disorder (TMD) symptomatology (n = 15) and pain-free controls (n = 15) participated in a 4-phase experiment (adaptation, baseline, task, recovery) designed to elicit schedule-induced behaviors. Self-report of oral habits and negative affect were recorded after each phase. Objective measures of oral habits were obtained via behavioral observation and masseter EMG recordings. Results revealed that negative arousal significantly increased during the fixed-time (FT) task and was also associated with increased oral habits among the TMD subjects. Moreover, 40% of the TMD subjects and none of the controls exhibited a pattern of EMG elevations in the early part of the inter-stimulus interval that met a strict criteria for scheduled-induced behavior per se. Taken together, these results suggest that the TMD subjects were engaging in schedule-induced oral habits. The adjunctive behavior literature seems to provide a plausible explanation as to how oral habits develop and are maintained in TMD patients, despite their painful consequences.

  14. Continuous Estimation of Human Multi-Joint Angles From sEMG Using a State-Space Model.

    Science.gov (United States)

    Ding, Qichuan; Han, Jianda; Zhao, Xingang

    2017-09-01

    Due to the couplings among joint-relative muscles, it is a challenge to accurately estimate continuous multi-joint movements from multi-channel sEMG signals. Traditional approaches always build a nonlinear regression model, such as artificial neural network, to predict the multi-joint movement variables using sEMG as inputs. However, the redundant sEMG-data are always not distinguished; the prediction errors cannot be evaluated and corrected online as well. In this work, a correlation-based redundancy-segmentation method is proposed to segment the sEMG-vector including redundancy into irredundant and redundant subvectors. Then, a general state-space framework is developed to build the motion model by regarding the irredundant subvector as input and the redundant one as measurement output. With the built state-space motion model, a closed-loop prediction-correction algorithm, i.e., the unscented Kalman filter (UKF), can be employed to estimate the multi-joint angles from sEMG, where the redundant sEMG-data are used to reject model uncertainties. After having fully employed the redundancy, the proposed method can provide accurate and smooth estimation results. Comprehensive experiments are conducted on the multi-joint movements of the upper limb. The maximum RMSE of the estimations obtained by the proposed method is 0.16±0.03, which is significantly less than 0.25±0.06 and 0.27±0.07 (p < 0.05) obtained by common neural networks.

  15. Selective depletion of spinal monoamines changes the rat soleus EMG from a tonic to a more phasic pattern

    DEFF Research Database (Denmark)

    Kiehn, Ole; Erdal, Jesper; Eken, Torsten

    1996-01-01

    subarachnoid space and gross-EMG recording electrodes in the soleus muscle. EMG recordings were performed in control conditions and at different times after intrathecal administration of either 40-55 μg 5,6-dihydroxytryptamine (5,6-DHT) and 40-55 μg 6-hydroxydopamine (6-OHDA) or 80 μg 5,7-dihydroxytryptamine...... (5,7-DHT) alone. The depletions were evaluated biochemically in brains and spinal cords after recordings. 3. In agreement with previous studies the intrathecal administration of neurotoxins caused a reduction of the noradrenaline (NA) and serotonin (5-HT) content of the lumbar spinal cord to about 2...

  16. A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series.

    Science.gov (United States)

    Chambon, Stanislas; Galtier, Mathieu N; Arnal, Pierrick J; Wainrib, Gilles; Gramfort, Alexandre

    2018-04-01

    Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of the signal of a sleep stage, based on the visual inspection of signals such as electroencephalograms (EEGs), electrooculograms (EOGs), electrocardiograms, and electromyograms (EMGs). We introduce here the first deep learning approach for sleep stage classification that learns end-to-end without computing spectrograms or extracting handcrafted features, that exploits all multivariate and multimodal polysomnography (PSG) signals (EEG, EMG, and EOG), and that can exploit the temporal context of each 30-s window of data. For each modality, the first layer learns linear spatial filters that exploit the array of sensors to increase the signal-to-noise ratio, and the last layer feeds the learnt representation to a softmax classifier. Our model is compared to alternative automatic approaches based on convolutional networks or decisions trees. Results obtained on 61 publicly available PSG records with up to 20 EEG channels demonstrate that our network architecture yields the state-of-the-art performance. Our study reveals a number of insights on the spatiotemporal distribution of the signal of interest: a good tradeoff for optimal classification performance measured with balanced accuracy is to use 6 EEG with 2 EOG (left and right) and 3 EMG chin channels. Also exploiting 1 min of data before and after each data segment offers the strongest improvement when a limited number of channels are available. As sleep experts, our system exploits the multivariate and multimodal nature of PSG signals in order to deliver the state-of-the-art classification performance with a small computational cost.

  17. Estimation of muscle fatigue using surface electromyography and near-infrared spectroscopy.

    Science.gov (United States)

    Taelman, Joachim; Vanderhaegen, Joke; Robijns, Mieke; Naulaers, Gunnar; Spaepen, Arthur; Van Huffel, Sabine

    2011-01-01

    This study looks at various parameters, derived from surface electromyography (sEMG) and Near Infrared Spectroscopy (NIRS) and their relationship in muscle fatigue during a static elbow flexion until exhaustion as well as during a semidynamic exercise.We found a linear increasing trend for a corrected amplitude parameter and a linear decreasing slope for the frequency content of the sEMG signal. The tissue oxygenation index (TOI) extracted from NIRS recordings showed a four-phase response for all the subjects. A strong correlation between frequency content of the sEMG signal and TOI was established. We can conclude that both sEMG and NIRS give complementary information concerning muscle fatigue.

  18. SURFACE ELECTROMYOGRAPHY IN BIOMECHANICS: APPLICATIONS AND SIGNAL ANALYSIS ASPECTS

    Directory of Open Access Journals (Sweden)

    DEAK GRAłIELA-FLAVIA

    2009-12-01

    Full Text Available Surface electromyography (SEMG is a technique for detecting and recording the electrical activity of the muscles using surface electrodes. The EMG signal is used in biomechanics mainly as an indicator of the initiation of muscle activation, as an indicator of the force produced by a contracting muscle, and as an index ofthe fatigue occurring within a muscle. EMG, used as a method of investigation, can tell us if the muscle is active or not, if the muscle is more or less active, when it is on or off, how much active is it, and finally, if it fatigues.The purpose of this article is to discuss some specific EMG signal analysis aspects with emphasis on comparison type analysis and frequency fatigue analysis.

  19. Sleep stage classification with low complexity and low bit rate.

    Science.gov (United States)

    Virkkala, Jussi; Värri, Alpo; Hasan, Joel; Himanen, Sari-Leena; Müller, Kiti

    2009-01-01

    Standard sleep stage classification is based on visual analysis of central (usually also frontal and occipital) EEG, two-channel EOG, and submental EMG signals. The process is complex, using multiple electrodes, and is usually based on relatively high (200-500 Hz) sampling rates. Also at least 12 bit analog to digital conversion is recommended (with 16 bit storage) resulting in total bit rate of at least 12.8 kbit/s. This is not a problem for in-house laboratory sleep studies, but in the case of online wireless self-applicable ambulatory sleep studies, lower complexity and lower bit rates are preferred. In this study we further developed earlier single channel facial EMG/EOG/EEG-based automatic sleep stage classification. An algorithm with a simple decision tree separated 30 s epochs into wakefulness, SREM, S1/S2 and SWS using 18-45 Hz beta power and 0.5-6 Hz amplitude. Improvements included low complexity recursive digital filtering. We also evaluated the effects of a reduced sampling rate, reduced number of quantization steps and reduced dynamic range on the sleep data of 132 training and 131 testing subjects. With the studied algorithm, it was possible to reduce the sampling rate to 50 Hz (having a low pass filter at 90 Hz), and the dynamic range to 244 microV, with an 8 bit resolution resulting in a bit rate of 0.4 kbit/s. Facial electrodes and a low bit rate enables the use of smaller devices for sleep stage classification in home environments.

  20. Redundancy or heterogeneity in the electric activity of the biceps brachii muscle? Added value of PCA-processed multi-channel EMG muscle activation estimates in a parallel-fibered muscle

    NARCIS (Netherlands)

    Staudenmann, D.; Stegeman, D.F.; van Dieen, J.H.

    2013-01-01

    Conventional bipolar EMG provides imprecise muscle activation estimates due to possibly heterogeneous activity within muscles and due to improper alignment of the electrodes with the muscle fibers. Principal component analysis (PCA), applied on multi-channel monopolar EMG yielded substantial

  1. Correlation analysis between surface electromyography and continuous-wave near-infrared spectroscopy parameters during isometric exercise to volitional fatigue

    OpenAIRE

    ŞAYLİ, Ömer; AKIN, Ata; ÇOTUK, Hasan Birol

    2014-01-01

    In this study, the process of muscular fatigue was examined using surface electromyography (sEMG) and continuous-wave near-infrared spectroscopy (cw-NIRS) simultaneously during an isometric hand grip exercise at 50% and 75% of the maximal voluntary contraction (MVC), sustained until volitional fatigue. The mean frequency of the sEMG decreased during the whole exercise, whereas the root mean square had a tendency to increase. Oxyhemoglobin/deoxyhemoglobin concentration changes computed ...

  2. SAW Classification Algorithm for Chinese Text Classification

    OpenAIRE

    Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

    2015-01-01

    Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

  3. Augmented effects of EMG biofeedback interfaced with virtual reality on neuromuscular control and movement coordination during reaching in children with cerebral palsy.

    Science.gov (United States)

    Yoo, Ji Won; Lee, Dong Ryul; Cha, Young Joo; You, Sung Hyun

    2017-01-01

    The purpose of the present study was to compare therapeutic effects of an electromyography (EMG) biofeedback augmented by virtual reality (VR) and EMG biofeedback alone on the triceps and biceps (T:B) muscle activity imbalance and elbow joint movement coordination during a reaching motor taskOBJECTIVE: To compare therapeutic effects of an electromyography (EMG) biofeedback augmented by virtual reality (VR) and EMG biofeedback alone on the triceps and biceps muscle activity imbalance and elbow joint movement coordination during a reaching motor task in normal children and children with spastic cerebral palsy (CP). 18 children with spastic CP (2 females; mean±standard deviation = 9.5 ± 1.96 years) and 8 normal children (3 females; mean ± standard deviation = 9.75 ± 2.55 years) were recruited from a local community center. All children with CP first underwent one intensive session of EMG feedback (30 minutes), followed by one session of the EMG-VR feedback (30 minutes) after a 1-week washout period. Clinical tests included elbow extension range of motion (ROM), biceps muscle strength, and box and block test. EMG triceps and biceps (T:B) muscle activity imbalance and reaching movement acceleration coordination were concurrently determined by EMG and 3-axis accelerometer measurements respectively. Independent t-test and one-way repeated analysis of variance (ANOVA) were performed at p augmented by virtual reality exercise games in children with spastic CP. The augmented EMG and VR feedback produced better neuromuscular balance control in the elbow joint than the EMG biofeedback alone.

  4. Waste classification sampling plan

    International Nuclear Information System (INIS)

    Landsman, S.D.

    1998-01-01

    The purpose of this sampling is to explain the method used to collect and analyze data necessary to verify and/or determine the radionuclide content of the B-Cell decontamination and decommissioning waste stream so that the correct waste classification for the waste stream can be made, and to collect samples for studies of decontamination methods that could be used to remove fixed contamination present on the waste. The scope of this plan is to establish the technical basis for collecting samples and compiling quantitative data on the radioactive constituents present in waste generated during deactivation activities in B-Cell. Sampling and radioisotopic analysis will be performed on the fixed layers of contamination present on structural material and internal surfaces of process piping and tanks. In addition, dose rate measurements on existing waste material will be performed to determine the fraction of dose rate attributable to both removable and fixed contamination. Samples will also be collected to support studies of decontamination methods that are effective in removing the fixed contamination present on the waste. Sampling performed under this plan will meet criteria established in BNF-2596, Data Quality Objectives for the B-Cell Waste Stream Classification Sampling, J. M. Barnett, May 1998

  5. Automated Algorithm for Generalized Tonic–Clonic Epileptic Seizure Onset Detection Based on sEMG Zero-Crossing Rate

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sándor; Hoppe, Karsten

    2012-01-01

    were analyzed from 11 consecutive patients. Our method is based on a high-pass filtering with a cutoff at 150 Hz, and monitoring a count of zero crossings with a hysteresis of $\\pm 50\\,\\mu \\hbox{V}$ . Based on data from one sEMG electrode (on the deltoid muscle), we achieved a sensitivity of 100...

  6. Specific Diurnal EMG Activity Pattern Observed in Occlusal Collapse Patients: Relationship between Diurnal Bruxism and Tooth Loss Progression

    Science.gov (United States)

    Kawakami, Shigehisa; Kumazaki, Yohei; Manda, Yosuke; Oki, Kazuhiro; Minagi, Shogo

    2014-01-01

    Aim The role of parafunctional masticatory muscle activity in tooth loss has not been fully clarified. This study aimed to reveal the characteristic activity of masseter muscles in bite collapse patients while awake and asleep. Materials and Methods Six progressive bite collapse patients (PBC group), six age- and gender-matched control subjects (MC group), and six young control subjects (YC group) were enrolled. Electromyograms (EMG) of the masseter muscles were continuously recorded with an ambulatory EMG recorder while patients were awake and asleep. Diurnal and nocturnal parafunctional EMG activity was classified as phasic, tonic, or mixed using an EMG threshold of 20% maximal voluntary clenching. Results Highly extended diurnal phasic activity was observed only in the PBC group. The three groups had significantly different mean diurnal phasic episodes per hour, with 13.29±7.18 per hour in the PBC group, 0.95±0.97 per hour in the MC group, and 0.87±0.98 per hour in the YC group (pbruxism as a strong destructive force. We found that diurnal phasic masticatory muscle activity was most characteristic in patients with progressive bite collapse. Practical implications The incidence of diurnal phasic contractions could be used for the prognostic evaluation of stomatognathic system stability. PMID:25010348

  7. A New Method to Detect Driver Fatigue Based on EMG and ECG Collected by Portable Non-Contact Sensors

    Directory of Open Access Journals (Sweden)

    Lin Wang

    2017-11-01

    Full Text Available Recently, detection and prediction on driver fatigue have become interest of research worldwide. In the present work, a new method is built to effectively evaluate driver fatigue based on electromyography (EMG and electrocardiogram (ECG collected by portable real-time and non-contact sensors. First, under the non-disturbance condition for driver’s attention, mixed physiological signals (EMG, ECG and artefacts are collected by non-contact sensors located in a cushion on the driver’s seat. EMG and ECG are effectively separated by FastICA, and de-noised by empirical mode decomposition (EMD. Then, three physiological features, complexity of EMG, complexity of ECG, and sample entropy (SampEn of ECG, are extracted and analysed. Principal components are obtained by principal components analysis (PCA and are used as independent variables. Finally, a mathematical model of driver fatigue is built, and the accuracy of the model is up to 91%. Moreover, based on the questionnaire, the calculation results of model are consistent with real fatigue felt by the participants. Therefore, this model can effectively detect driver fatigue.

  8. An internet-based wearable watch-over system for elderly and disabled utilizing EMG and accelerometer.

    Science.gov (United States)

    Kishimoto, M; Yoshida, T; Hayasaka, T; Mori, D; Imai, Y; Matsuki, N; Ishikawa, T; Yamaguchi, T

    2009-01-01

    An effective way for preventing injuries and diseases among the elderly is to monitor their daily lives. In this regard, we propose the use of a "Hyper Hospital Network", which is an information support system for elderly people and patients. In the current study, we developed a wearable system for monitoring electromyography (EMG) and acceleration using the Hyper Hospital Network plan. The current system is an upgraded version of our previous system for gait analysis (Yoshida et al. [13], Telemedicine and e-Health 13 703-714), and lets us monitor decreases in exercise and the presence of a hemiplegic gait more accurately. To clarify the capabilities and reliability of the system, we performed three experimental evaluations: one to verify the performance of the wearable system, a second to detect a hemiplegic gait, and a third to monitor EMG and accelerations simultaneously. Our system successfully detected a lack of exercise by monitoring the iEMG in healthy volunteers. Moreover, by using EMG and acceleration signals simultaneously, the reliability of the Hampering Index (HI) for detecting hemiplegia walking was improved significantly. The present study provides useful knowledge for the development of a wearable computer designed to monitor the physical conditions of older persons and patients.

  9. Specific diurnal EMG activity pattern observed in occlusal collapse patients: relationship between diurnal bruxism and tooth loss progression.

    Science.gov (United States)

    Kawakami, Shigehisa; Kumazaki, Yohei; Manda, Yosuke; Oki, Kazuhiro; Minagi, Shogo

    2014-01-01

    The role of parafunctional masticatory muscle activity in tooth loss has not been fully clarified. This study aimed to reveal the characteristic activity of masseter muscles in bite collapse patients while awake and asleep. Six progressive bite collapse patients (PBC group), six age- and gender-matched control subjects (MC group), and six young control subjects (YC group) were enrolled. Electromyograms (EMG) of the masseter muscles were continuously recorded with an ambulatory EMG recorder while patients were awake and asleep. Diurnal and nocturnal parafunctional EMG activity was classified as phasic, tonic, or mixed using an EMG threshold of 20% maximal voluntary clenching. Highly extended diurnal phasic activity was observed only in the PBC group. The three groups had significantly different mean diurnal phasic episodes per hour, with 13.29±7.18 per hour in the PBC group, 0.95±0.97 per hour in the MC group, and 0.87±0.98 per hour in the YC group (pstability.

  10. A hybrid brain-machine interface based on EEG and EMG activity for the motor rehabilitation of stroke patients.

    Science.gov (United States)

    Sarasola-Sanz, Andrea; Irastorza-Landa, Nerea; Lopez-Larraz, Eduardo; Bibian, Carlos; Helmhold, Florian; Broetz, Doris; Birbaumer, Niels; Ramos-Murguialday, Ander

    2017-07-01

    Including supplementary information from the brain or other body parts in the control of brain-machine interfaces (BMIs) has been recently proposed and investigated. Such enriched interfaces are referred to as hybrid BMIs (hBMIs) and have been proven to be more robust and accurate than regular BMIs for assistive and rehabilitative applications. Electromyographic (EMG) activity is one of the most widely utilized biosignals in hBMIs, as it provides a quite direct measurement of the motion intention of the user. Whereas most of the existing non-invasive EEG-EMG-hBMIs have only been subjected to offline testings or are limited to one degree of freedom (DoF), we present an EEG-EMG-hBMI that allows the simultaneous control of 7-DoFs of the upper limb with a robotic exoskeleton. Moreover, it establishes a biologically-inspired hierarchical control flow, requiring the active participation of central and peripheral structures of the nervous system. Contingent visual and proprioceptive feedback about the user's EEG and EMG activity is provided in the form of velocity modulation during functional task training. We believe that training with this closed-loop system may facilitate functional neuroplastic processes and eventually elicit a joint brain and muscle motor rehabilitation. Its usability is validated during a real-time operation session in a healthy participant and a chronic stroke patient, showing encouraging results for its application to a clinical rehabilitation scenario.

  11. What do facial expressions of emotion express in young children? The relationship between facial display and EMG measures

    Directory of Open Access Journals (Sweden)

    Michela Balconi

    2014-04-01

    Full Text Available The present paper explored the relationship between emotional facial response and electromyographic modulation in children when they observe facial expression of emotions. Facial responsiveness (evaluated by arousal and valence ratings and psychophysiological correlates (facial electromyography, EMG were analyzed when children looked at six facial expressions of emotions (happiness, anger, fear, sadness, surprise and disgust. About EMG measure, corrugator and zygomatic muscle activity was monitored in response to different emotional types. ANOVAs showed differences for both EMG and facial response across the subjects, as a function of different emotions. Specifically, some emotions were well expressed by all the subjects (such as happiness, anger and fear in terms of high arousal, whereas some others were less level arousal (such as sadness. Zygomatic activity was increased mainly for happiness, from one hand, corrugator activity was increased mainly for anger, fear and surprise, from the other hand. More generally, EMG and facial behavior were highly correlated each other, showing a “mirror” effect with respect of the observed faces.

  12. [Women boxing athletes' EMG of upper limbs and lumbar muscles in the training of air striking of straight punch].

    Science.gov (United States)

    Zhang, Ri-Hui; Kang, Zhi-Xin

    2011-05-01

    To study training effect of upper limbs and lumbar muscles in the proceed of air striking of straight punch by analyzing boxing athletes' changes of electromyogram (EMG). We measured EMG of ten women boxing athletes' upper arm biceps (contractor muscle), upper arm triceps (antagonistic muscle), forearm flexor muscle (contractor muscle), forearm extensor muscle (antagonistic muscle), and lumbar muscles by ME6000 (Mega Electronics Ltd.). The stipulated exercise was to do air striking of straight punch with loads of 2.5 kg of dumbbell in the hand until exhausted. In the proceed of exercise-induce exhausted, the descend magnitude and speed of median frequency (MF) in upper limb antagonistic muscle exceeded to contracting muscle, moreover, the work percentage showed that contractor have done a larger percentage of work than antagonistic muscle. Compared with world champion's EMG, the majority of ordinary athletes' lumbar muscles MF revealed non-drop tendency, and the work percentage showed that lumbar muscles had a very little percentage of work. After comparing the EMG test index in upper limb and lumbar muscle of average boxing athletes with that of the world champion, we find the testees lack of the training of upper limb antagonistic muscle and lumbar muscle, and more trainings aimed at these muscles need to be taken.

  13. The Design of EMG Measurement System for Arm Strength Training Machine

    Directory of Open Access Journals (Sweden)

    Tze-Yee Ho

    2015-01-01

    Full Text Available The setup of interactive communication between arm strength training machine and the people will make exercise and rehabilitation therapy become more friendly. The employment of electromyographic not only can help physical therapy but also can achieve more effective rehabilitation. Both of the system hardware and software of the arm strength training machine with EMG system are well designed and described. The fundamental design of electromyographic measurement system based on a microcontroller is analyzed and discussed. The software programming is developed in MPLAB integrated development environment from the Microchip Technology Inc. and the friendly user interface is created as well. Finally, an arm strength training machine with electromyographic control system is realized and demonstrated. The experimental results show the feasibility and fidelity of the complete designed system.

  14. [Automatic analysis of the interference EMG of the brachioradial muscle in neuropathy of the radial nerve].

    Science.gov (United States)

    Popelianskiĭ, Ia Iu; Bogdanov, E I; Khamidullina, V Z

    1988-01-01

    In 8 patients with radial neuropathy the authors studied histograms of distribution of potentials of motor units (PMU) by their duration, as well as of the number of intercrossings (T) and the mean amplitude of interference EMG of the musculus brachioradialis. The findings included a decrease in the T value and T/M ratio in the presence of an insignificant shift of the histograms and of the mean duration of PMU. With regard to the diagnosis of early neuropathies a reduction in the average value of T and T/M in the presence of ungraded voluntary tension of the muscle is diagnostically more important than changes in the duration of individual PMU.

  15. Construction of Lower Limbs Rehabilitation System Based on Bodily Features and EMG

    Science.gov (United States)

    Kushida, Daisuke; Kanazawa, Tomohiro; Kitamura, Akira

    In rehabilitation, there are two roles of reinforcement of the expansion of the motion range and muscular power. The diseased part is requested to be operated by the external force in the former, and the load corresponding to patient's muscular power is requested to be given in the latter. Recently, there are a lot of researches that try such rehabilitation by the machine. The principal object is put on the motion control of the machine in those researches. The most important thing is a mechanism that patient's state is quantitatively evaluated. This paper proposes the mechanism that presumes the patient recovery by relating bodily features to EMG of the diseased part in rehabilitation. In addition, a new rehabilitation system, that contained the self adjustment of the load using those mechanisms and the consideration of fatigue, is proposed. Effectiveness of the proposed rehabilitation system is verified by the simulation work.

  16. Motor unit recruitment and bursts of activity in the surface electromyogram during a sustained contraction.

    Science.gov (United States)

    Riley, Zachary A; Terry, Mary E; Mendez-Villanueva, Alberto; Litsey, Jane C; Enoka, Roger M

    2008-06-01

    Bursts of activity in the surface electromyogram (EMG) during a sustained contraction have been interpreted as corresponding to the transient recruitment of motor units, but this association has never been confirmed. The current study compared the timing of trains of action potentials discharged by single motor units during a sustained contraction with the bursts of activity detected in the surface EMG signal. The 20 motor units from 6 subjects [recruitment threshold, 35.3 +/- 11.3% maximal voluntary contraction (MVC) force] that were detected with fine wire electrodes discharged 2-9 trains of action potentials (7.2 +/- 5.6 s in duration) when recruited during a contraction that was sustained at a force below its recruitment threshold (target force, 25.4 +/- 10.6% MVC force). High-pass filtering the bipolar surface EMG signal improved its correlation with the single motor unit signal. An algorithm applied to the surface EMG was able to detect 75% of the trains of motor unit action potentials. The results indicate that bursts of activity in the surface EMG during a constant-force contraction correspond to the transient recruitment of higher-threshold motor units in healthy individuals, and these results could assist in the diagnosis and design of treatment in individuals who demonstrate deficits in motor unit activation.

  17. Observation and imitation of actions performed by humans, androids, and robots: an EMG study

    Science.gov (United States)

    Hofree, Galit; Urgen, Burcu A.; Winkielman, Piotr; Saygin, Ayse P.

    2015-01-01

    Understanding others’ actions is essential for functioning in the physical and social world. In the past two decades research has shown that action perception involves the motor system, supporting theories that we understand others’ behavior via embodied motor simulation. Recently, empirical approach to action perception has been facilitated by using well-controlled artificial stimuli, such as robots. One broad question this approach can address is what aspects of similarity between the observer and the observed agent facilitate motor simulation. Since humans have evolved among other humans and animals, using artificial stimuli such as robots allows us to probe whether our social perceptual systems are specifically tuned to process other biological entities. In this study, we used humanoid robots with different degrees of human-likeness in appearance and motion along with electromyography (EMG) to measure muscle activity in participants’ arms while they either observed or imitated videos of three agents produce actions with their right arm. The agents were a Human (biological appearance and motion), a Robot (mechanical appearance and motion), and an Android (biological appearance and mechanical motion). Right arm muscle activity increased when participants imitated all agents. Increased muscle activation was found also in the stationary arm both during imitation and observation. Furthermore, muscle activity was sensitive to motion dynamics: activity was significantly stronger for imitation of the human than both mechanical agents. There was also a relationship between the dynamics of the muscle activity and motion dynamics in stimuli. Overall our data indicate that motor simulation is not limited to observation and imitation of agents with a biological appearance, but is also found for robots. However we also found sensitivity to human motion in the EMG responses. Combining data from multiple methods allows us to obtain a more complete picture of action

  18. Thinking Outside the Button Box: EMG as a Computer Input Device for Psychological Research

    Directory of Open Access Journals (Sweden)

    L. Elizabeth Crawford

    2017-07-01

    Full Text Available Experimental psychology research commonly has participants respond to stimuli by pressing buttons or keys. Standard computer input devices constrain the range of motoric responses participants can make, even as the field advances theory about the importance of the motor system in cognitive and social information processing. Here we describe an inexpensive way to use an electromyographic (EMG signal as a computer input device, enabling participants to control a computer by contracting muscles that are not usually used for that purpose, but which may be theoretically relevant. We tested this approach in a study of facial mimicry, a well-documented phenomenon in which viewing emotional faces elicits automatic activation of corresponding muscles in the face of the viewer. Participants viewed happy and angry faces and were instructed to indicate the emotion on each face as quickly as possible by either furrowing their brow or contracting their cheek. The mapping of motor response to judgment was counterbalanced, so that one block of trials required a congruent mapping (contract brow to respond “angry,” cheek to respond “happy” and the other block required an incongruent mapping (brow for “happy,” cheek for “angry”. EMG sensors placed over the left corrugator supercilii muscle and left zygomaticus major muscle fed readings of muscle activation to a microcontroller, which sent a response to a computer when activation reached a pre-determined threshold. Response times were faster when the motor-response mapping was congruent than when it was incongruent, extending prior studies on facial mimicry. We discuss further applications of the method for research that seeks to expand the range of human-computer interaction beyond the button box.

  19. Development of Chewing in Children From 12 to 48 Months: Longitudinal Study of EMG Patterns

    Science.gov (United States)

    GREEN, JORDAN R.; MOORE, CHRISTOPHER A.; RUARK, JACKI L.; RODDA, PAULA R.; MORVÉE, WENDY T.; VanWITZENBURG, MARCUS J.

    2014-01-01

    Developmental changes in the coordinative organization of masticatory muscles were examined longitudinally in four children over 49 experimental sessions spanning the age range of 12–48 mo. Electromyographic (EMG) records were obtained for right and left masseter muscles, right and left temporalis muscles, and the anterior belly of the digastric. Two independent analytic processes were employed, one that relied on identification of onset and offset of muscle activation and a second that used pairwise cross-correlational techniques. The results of these two analyses, which were found to be consistent with each other, demonstrated that the basic chewing pattern of reciprocally activated antagonistic muscle groups is established by 12 mo of age. Nevertheless, chewing efficiency appears to be improved through a variety of changes in the chewing pattern throughout early development. Coupling of activity among the jaw elevator muscles was shown to strengthen with maturation, and the synchrony of onset and offset of these muscles also increased. Coactivation of antagonistic muscles decreased significantly with development. This decrease in antagonistic coactivation and increase in synchrony among jaw elevators, and a parallel decrease in EMG burst duration, were taken as evidence of increased chewing efficiency. No significant differences in the frequency of chewing were found across the ages studied. Additional considerations include the appropriateness of this coordinative infrastructure for other developing oromotor skills, such as speech production. It is suggested that the relatively fixed coordinative framework for chewing exhibited by these children would not be suitable for adaptation to speech movements, which have been shown to rely on a much more variable and adjustable coordinative organization. PMID:9163386

  20. Discrimination of Parkinsonian Tremor From Essential Tremor by Voting Between Different EMG Signal Processing Techniques

    Directory of Open Access Journals (Sweden)

    A Hossen

    2014-06-01

    Full Text Available Parkinson's disease (PD and essential tremor (ET are the two most common disorders that cause involuntary muscle shaking movements, or what is called "tremor”. PD is a neurodegenerative disease caused by the loss of dopamine receptors which control and adjust the movement of the body. On the other hand, ET is a neurological movement disorder which also causes tremors and shaking, but it is not related to dopamine receptor loss; it is simply a tremor. The differential diagnosis between these two disorders is sometimes difficult to make clinically because of the similarities of their symptoms; additionally, the available tests are complex and expensive. Thus, the objective of this paper is to discriminate between these two disorders with simpler, cheaper and easier ways by using electromyography (EMG signal processing techniques. EMG and accelerometer records of 39 patients with PD and 41 with ET were acquired from the Hospital of Kiel University in Germany and divided into a trial group and a test group. Three main techniques were applied: the wavelet-based soft-decision technique, statistical signal characterization (SSC of the spectrum of the signal, and SSC of the amplitude variation of the Hilbert transform. The first technique resulted in a discrimination efficiency of 80% on the trial set and 85% on the test set. The second technique resulted in an efficiency of 90% on the trial set and 82.5% on the test set. The third technique resulted in an 87.5% efficiency on the trial set and 65.5% efficiency on the test set. Lastly, a final vote was done to finalize the discrimination using these three techniques, and as a result of the vote, accuracies of 92.5%, 85.0% and 88.75% were obtained on the trial data, test data and total data, respectively.

  1. Effect of instructions on EMG during the bench press in trained and untrained males.

    Science.gov (United States)

    Daniels, Rebecca J; Cook, Summer B

    2017-10-01

    Strength and rehabilitation professionals strive to emphasize certain muscles used during an exercise and it may be possible to alter muscle recruitment strategies with varying instructions. This study aimed to determine whether resistance trained and untrained males could selectively activate the pectoralis major or triceps brachii during the bench press according to various instructions. This study included 13 trained males (21.5±2.9years old, 178.7±7.0cm, 85.7±10.7kg) and 12 untrained males (20.3±1.6years old, 178.8±9.4cm, 74.6±17.3kg). Participants performed a bench press one-repetition maximum (1-RM) test, 3 uninstructed repetitions at 80% 1-RM and two more sets of three repetitions with instructions to isolate the chest or arm muscles. Electromyography (EMG) was obtained from the pectoralis major, anterior deltoid, and the long head and short head of the triceps brachii. Maximum EMG activity normalized to 1-RM for each muscle was averaged over the three repetitions for each set and compared between the uninstructed, chest-instructed and arm-instructed conditions among the groups. The trained participants had a greater 1-RM (126.2±30.6kg) than the untrained participants (61.6±14.8kg) (P0.05). When the group data was combined, short head of the triceps activity was significantly lower in the chest instruction (80.1±19.3%) when compared to the uninstructed (85.6±23.3%; P=0.01) and arm-instructed (86.0±23.2; P=0.01) conditions. It can be concluded that instructions can affect muscle activation during the bench press, and this is not dependent on training status. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Ambient temperature and neck EMG with +Gz loading on a trampoline.

    Science.gov (United States)

    Sovelius, Roope; Oksa, Juha; Rintala, Harri; Huhtala, Heini; Siitonen, Simo

    2007-06-01

    Fighter pilots who are frequently exposed to severe cold ambient temperatures experience neck pain disabilities and occupational disorders more often than those who are not so exposed. We hypothesized that a cold-induced increase in muscle strain might lead to in-flight neck injuries. The aims of this study were to measure the level of cooling before takeoff and to determine muscle strain under Gz loading (0 to +4 Gz) at different temperatures. Test subjects' (n = 14) skin temperature (T(skin)) over the trapezoids was measured before the walk to the aircraft and again in the cockpit (air temperature -14 degrees C). The subjects then performed trampoline exercises in two different ambient temperatures (-2 degrees C and +21 degrees C) after a 30-min period at the respective temperatures. EMG activity of the sternocleidomastoid (SCM), cervical erector spinae (CES), trapezoid (TRA), thoracic erector spinae (TES) muscles, and Tskin of the SCM and TRA were measured. Tskin over the trapezoids decreased from 30.1 +/- 1.7 degrees C to 27.8 +/- 2.6 degrees C (p < 0.001) before takeoff. The change of muscle strain in cold was +11.0% in SCM, +14.9% in CES, +3.7% in TRA, and -1.7% in TES. Change was statistically significant in the cervical, uncovered area (SCM, CES). The linear regression model indicated a 2.6% increase in muscle strain per every decreased degree centigrade in skin temperature over the SCM. Superficial cooling over the neck muscles was significant prior to takeoff. Muscle loading in the cold caused higher EMG activity. A major increase in muscle strain was seen in the cervical muscles. These findings suggest a cold-induced increase in muscle strain during in-flight Gz loading.

  3. Comparative performance analysis of M-IMU/EMG and voice user interfaces for assistive robots.

    Science.gov (United States)

    Laureiti, Clemente; Cordella, Francesca; di Luzio, Francesco Scotto; Saccucci, Stefano; Davalli, Angelo; Sacchetti, Rinaldo; Zollo, Loredana

    2017-07-01

    People with a high level of disability experience great difficulties to perform activities of daily living and resort to their residual motor functions in order to operate assistive devices. The commercially available interfaces used to control assistive manipulators are typically based on joysticks and can be used only by subjects with upper-limb residual mobilities. Many other solutions can be found in the literature, based on the use of multiple sensory systems for detecting the human motion intention and state. Some of them require a high cognitive workload for the user. Some others are more intuitive and easy to use but have not been widely investigated in terms of usability and user acceptance. The objective of this work is to propose an intuitive and robust user interface for assistive robots, not obtrusive for the user and easily adaptable for subjects with different levels of disability. The proposed user interface is based on the combination of M-IMU and EMG for the continuous control of an arm-hand robotic system by means of M-IMUs. The system has been experimentally validated and compared to a standard voice interface. Sixteen healthy subjects volunteered to participate in the study: 8 subjects used the combined M-IMU/EMG robot control, and 8 subjects used the voice control. The arm-hand robotic system made of the KUKA LWR 4+ and the IH2 Azzurra hand was controlled to accomplish the daily living task of drinking. Performance indices and evaluation scales were adopted to assess performance of the two interfaces.

  4. Observation and Imitation of Actions Performed by Humans, Androids and Robots: An EMG study

    Directory of Open Access Journals (Sweden)

    Galit eHofree

    2015-06-01

    Full Text Available Understanding others’ actions is essential for functioning in the physical and social world. In the past two decades research has shown that action perception involves the motor system, supporting theories that we understand others’ behavior via embodied motor simulation. Recently, action perception has been facilitated by using well-controlled artificial stimuli, such as robots. One key question this approach enables is what aspects of similarity between the observer and the observed agent facilitate motor simulation? Since humans have evolved among other humans and animals, using artificial stimuli such as robots allows us to probe whether our social perceptual systems are tuned to process other biological entities. In this study, we used humanoid robots with different degrees of humanlikeness in appearance and motion along with electromyography (EMG to measure muscle activity in participants’ arms while they either observed or imitated videos of three agents produce actions with their right arm. The agents were a Human (biological appearance and motion, a Robot (mechanical appearance and motion and an Android (biological appearance, mechanical motion. Right arm muscle activity increased when participants imitated all agents. Increased muscle activation was found also in the stationary arm both during imitation and observation. Furthermore, muscle activity was sensitive to motion dynamics: activity was significantly stronger for imitation of the human than both mechanical agents. There was also a relationship between the dynamics of the muscle activity and motion dynamics in stimuli. Overall our data indicate that motor simulation is not limited to observation and imitation of agents with a biological appearance, but is also found for robots. However we also found sensitivity to human motion in the EMG responses. Combining data from multiple methods allows us to obtain a more complete picture of action understanding and the underlying

  5. Specific diurnal EMG activity pattern observed in occlusal collapse patients: relationship between diurnal bruxism and tooth loss progression.

    Directory of Open Access Journals (Sweden)

    Shigehisa Kawakami

    Full Text Available AIM: The role of parafunctional masticatory muscle activity in tooth loss has not been fully clarified. This study aimed to reveal the characteristic activity of masseter muscles in bite collapse patients while awake and asleep. MATERIALS AND METHODS: Six progressive bite collapse patients (PBC group, six age- and gender-matched control subjects (MC group, and six young control subjects (YC group were enrolled. Electromyograms (EMG of the masseter muscles were continuously recorded with an ambulatory EMG recorder while patients were awake and asleep. Diurnal and nocturnal parafunctional EMG activity was classified as phasic, tonic, or mixed using an EMG threshold of 20% maximal voluntary clenching. RESULTS: Highly extended diurnal phasic activity was observed only in the PBC group. The three groups had significantly different mean diurnal phasic episodes per hour, with 13.29±7.18 per hour in the PBC group, 0.95±0.97 per hour in the MC group, and 0.87±0.98 per hour in the YC group (p<0.01. ROC curve analysis suggested that the number of diurnal phasic episodes might be used to predict bite collapsing tooth loss. CONCLUSION: Extensive bite loss might be related to diurnal masticatory muscle parafunction but not to parafunction during sleep. CLINICAL RELEVANCE SCIENTIFIC RATIONALE FOR STUDY: Although mandibular parafunction has been implicated in stomatognathic system breakdown, a causal relationship has not been established because scientific modalities to evaluate parafunctional activity have been lacking. PRINCIPAL FINDINGS: This study used a newly developed EMG recording system that evaluates masseter muscle activity throughout the day. Our results challenge the stereotypical idea of nocturnal bruxism as a strong destructive force. We found that diurnal phasic masticatory muscle activity was most characteristic in patients with progressive bite collapse. PRACTICAL IMPLICATIONS: The incidence of diurnal phasic contractions could be used for

  6. Electromyography (EMG) analysis on impact of classroom chair and table usage among primary school students in Perlis

    Science.gov (United States)

    Jing, Ewe Hui; Shan, Lim Shaiu; Effendi, M. S. M.; Rosli, Muhamad Farizuan

    2017-09-01

    The existing design of primary school classroom chair and table had brought low back pain, neck pain and shoulder pain problems respectively among students in primary school. The purpose of this study is to relate the electromyography (EMG) analysis with the most critical area of the body during sitting and writing. Six male and six female primary school students from SK Seri Perlis with no back pain, neck pain and shoulder pain problems involved were invited as respondents in this study. EMG experiment was carried out by first determined the critical point at T9 and L3 from thoracic and lumbar segment respectively for ECG electrode placement and performed with a series of sitting trials for analysis. The sitting trials performed were slouch to lumbopelvic sitting and slouch to thoracic sitting follow by instruction. Next, the electrode placement was identified at C2-C3 on cervical spine for neck and at midpoint between C7 to the lateral edge of acromion spanning for shoulder respectively. These points were identified for a series of writing task performing for the EMG analysis. There were two type of writing task which included writing by looking at the whiteboard and paper placed on the table. The subjects were instructed to rest during the experiment when necessary. During lumbopelvic sitting posture, the average muscle activation on lumbar area was at the highest peak. The peak indicated that there was critical effect from the experimental finding. The performance of writing task from whiteboard gave rise a higher impact on neck muscle while writing task from paper had a greater impact on shoulder muscle. The critical affected muscle on these areas was proven on these written tasks. The EMG experiment showed that the existing design of primary school classroom chair and table had brought impact on lumbar, neck and shoulder towards the students who were using. A future recommendation suggests that to redesign primary school classroom chair and table which

  7. Multichannel analysis of surface-waves and integration of downhole acoustic televiewer imaging, ultrasonic Vs and Vp, and vertical seismic profiling in an NEHRP-standard classification, South of Concordia, Kansas, USA

    Science.gov (United States)

    Raef, Abdelmoneam; Gad, Sabreen; Tucker-Kulesza, Stacey

    2015-10-01

    Seismic site characteristics, as pertaining to earthquake hazard reduction, are a function of the subsurface elastic moduli and the geologic structures. This study explores how multiscale (surface, downhole, and laboratory) datasets can be utilized to improve "constrained" average Vs30 (shear-wave velocity to a 30-meter depth). We integrate borehole, surface and laboratory measurements for a seismic site classification based on the standards of the National Earthquake Hazard Reduction Program (NEHRP). The seismic shear-wave velocity (Vs30) was derived from a geophysical inversion workflow that utilized multichannel analysis of surface-waves (MASW) and downhole acoustic televiewer imaging (DATI). P-wave and S-wave velocities, based on laboratory measurements of arrival times of ultrasonic-frequency signals, supported the workflow by enabling us to calculate Poisson's ratio, which was incorporated in building an initial model for the geophysical inversion of MASW. Extraction of core samples from two boreholes provided lithology and thickness calibration of the amplitudes of the acoustic televiewer imaging for each layer. The MASW inversion, for calculating Vs sections, was constrained with both ultrasonic laboratory measurements (from first arrivals of Vs and Vp waveforms at simulated in situ overburden stress conditions) and the downhole acoustic televiewer (DATV) amplitude logs. The Vs30 calculations enabled categorizing the studied site as NEHRP-class "C" - very dense soil and soft rock. Unlike shallow fractured carbonates in the studied area, S-wave and P-wave velocities at ultrasonic frequency for the deeper intact shale core-samples from two boreholes were in better agreement with the corresponding velocities from both a zero-offset vertical seismic profiling (VSP) and inversion of Rayleigh-wave velocity dispersion curves.

  8. Asteroid taxonomic classifications

    International Nuclear Information System (INIS)

    Tholen, D.J.

    1989-01-01

    This paper reports on three taxonomic classification schemes developed and applied to the body of available color and albedo data. Asteroid taxonomic classifications according to two of these schemes are reproduced

  9. Hand eczema classification

    DEFF Research Database (Denmark)

    Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M

    2008-01-01

    of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

  10. Classification with support hyperplanes

    NARCIS (Netherlands)

    G.I. Nalbantov (Georgi); J.C. Bioch (Cor); P.J.F. Groenen (Patrick)

    2006-01-01

    textabstractA new classification method is proposed, called Support Hy- perplanes (SHs). To solve the binary classification task, SHs consider the set of all hyperplanes that do not make classification mistakes, referred to as semi-consistent hyperplanes. A test object is classified using

  11. Standard classification: Physics

    International Nuclear Information System (INIS)

    1977-01-01

    This is a draft standard classification of physics. The conception is based on the physics part of the systematic catalogue of the Bayerische Staatsbibliothek and on the classification given in standard textbooks. The ICSU-AB classification now used worldwide by physics information services was not taken into account. (BJ) [de

  12. Automated Decision Tree Classification of Corneal Shape

    Science.gov (United States)

    Twa, Michael D.; Parthasarathy, Srinivasan; Roberts, Cynthia; Mahmoud, Ashraf M.; Raasch, Thomas W.; Bullimore, Mark A.

    2011-01-01

    Purpose The volume and complexity of data produced during videokeratography examinations present a challenge of interpretation. As a consequence, results are often analyzed qualitatively by subjective pattern recognition or reduced to comparisons of summary indices. We describe the application of decision tree induction, an automated machine learning classification method, to discriminate between normal and keratoconic corneal shapes in an objective and quantitative way. We then compared this method with other known classification methods. Methods The corneal surface was modeled with a seventh-order Zernike polynomial for 132 normal eyes of 92 subjects and 112 eyes of 71 subjects diagnosed with keratoconus. A decision tree classifier was induced using the C4.5 algorithm, and its classification performance was compared with the modified Rabinowitz–McDonnell index, Schwiegerling’s Z3 index (Z3), Keratoconus Prediction Index (KPI), KISA%, and Cone Location and Magnitude Index using recommended classification thresholds for each method. We also evaluated the area under the receiver operator characteristic (ROC) curve for each classification method. Results Our decision tree classifier performed equal to or better than the other classifiers tested: accuracy was 92% and the area under the ROC curve was 0.97. Our decision tree classifier reduced the information needed to distinguish between normal and keratoconus eyes using four of 36 Zernike polynomial coefficients. The four surface features selected as classification attributes by the decision tree method were inferior elevation, greater sagittal depth, oblique toricity, and trefoil. Conclusions Automated decision tree classification of corneal shape through Zernike polynomials is an accurate quantitative method of classification that is interpretable and can be generated from any instrument platform capable of raw elevation data output. This method of pattern classification is extendable to other classification

  13. Automatic sleep stage classification using two facial electrodes.

    Science.gov (United States)

    Virkkala, Jussi; Velin, Riitta; Himanen, Sari-Leena; Värri, Alpo; Müller, Kiti; Hasan, Joel

    2008-01-01

    Standard sleep stage classification is based on visual analysis of central EEG, EOG and EMG signals. Automatic analysis with a reduced number of sensors has been studied as an easy alternative to the standard. In this study, a single-channel electro-oculography (EOG) algorithm was developed for separation of wakefulness, SREM, light sleep (S1, S2) and slow wave sleep (S3, S4). The algorithm was developed and tested with 296 subjects. Additional validation was performed on 16 subjects using a low weight single-channel Alive Monitor. In the validation study, subjects attached the disposable EOG electrodes themselves at home. In separating the four stages total agreement (and Cohen's Kappa) in the training data set was 74% (0.59), in the testing data set 73% (0.59) and in the validation data set 74% (0.59). Self-applicable electro-oculography with only two facial electrodes was found to provide reasonable sleep stage information.

  14. Attack surfaces

    DEFF Research Database (Denmark)

    Gruschka, Nils; Jensen, Meiko

    2010-01-01

    The new paradigm of cloud computing poses severe security risks to its adopters. In order to cope with these risks, appropriate taxonomies and classification criteria for attacks on cloud computing are required. In this work-in-progress paper we present one such taxonomy based on the notion...... of attack surfaces of the cloud computing scenario participants....

  15. Classification of refrigerants; Classification des fluides frigorigenes

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-07-01

    This document was made from the US standard ANSI/ASHRAE 34 published in 2001 and entitled 'designation and safety classification of refrigerants'. This classification allows to clearly organize in an international way the overall refrigerants used in the world thanks to a codification of the refrigerants in correspondence with their chemical composition. This note explains this codification: prefix, suffixes (hydrocarbons and derived fluids, azeotropic and non-azeotropic mixtures, various organic compounds, non-organic compounds), safety classification (toxicity, flammability, case of mixtures). (J.S.)

  16. EMG and force production of the flexor hallucis longus muscle in isometric plantarflexion and the push-off phase of walking.

    Science.gov (United States)

    Péter, Annamária; Hegyi, András; Stenroth, Lauri; Finni, Taija; Cronin, Neil J

    2015-09-18

    Large forces are generated under the big toe in the push-off phase of walking. The largest flexor muscle of the big toe is the flexor hallucis longus (FHL), which likely contributes substantially to these forces. This study examined FHL function at different levels of isometric plantarflexion torque and in the push-off phase at different speeds of walking. FHL and calf muscle activity were measured with surface EMG and plantar pressure was recorded with pressure insoles. FHL activity was compared to the activity of the calf muscles. Force and impulse values were calculated under the big toe, and were compared to the entire pressed area of the insole to determine the relative contribution of big toe flexion forces to the ground reaction force. FHL activity increased with increasing plantarflexion torque level (F=2.8, P=0.024) and with increasing walking speed (F=11.608, Ppush-off phase of walking, peak force under the big toe increased at a higher rate than force under the other areas of the plantar surface (F=3.801, P=0.018), implying a greater relative contribution to total force at faster speeds. Moreover, substantial differences were found between isometric plantarflexion and walking concerning FHL activity relative to that of the calf muscles, highlighting the task-dependant behaviour of FHL. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Classification, disease, and diagnosis.

    Science.gov (United States)

    Jutel, Annemarie

    2011-01-01

    Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

  18. An equilibrium-point model for fast, single-joint movement: I. Emergence of strategy-dependent EMG patterns.

    Science.gov (United States)

    Latash, M L; Gottlieb, G L

    1991-09-01

    We describe a model for the regulation of fast, single-joint movements, based on the equilibrium-point hypothesis. Limb movement follows constant rate shifts of independently regulated neuromuscular variables. The independently regulated variables are tentatively identified as thresholds of a length sensitive reflex for each of the participating muscles. We use the model to predict EMG patterns associated with changes in the conditions of movement execution, specifically, changes in movement times, velocities, amplitudes, and moments of limb inertia. The approach provides a theoretical neural framework for the dual-strategy hypothesis, which considers certain movements to be results of one of two basic, speed-sensitive or speed-insensitive strategies. This model is advanced as an alternative to pattern-imposing models based on explicit regulation of timing and amplitudes of signals that are explicitly manifest in the EMG patterns.

  19. Upper-Limb Recovery After Stroke: A Randomized Controlled Trial Comparing EMG-Triggered, Cyclic, and Sensory Electrical Stimulation.

    Science.gov (United States)

    Wilson, Richard D; Page, Stephen J; Delahanty, Michael; Knutson, Jayme S; Gunzler, Douglas D; Sheffler, Lynne R; Chae, John

    2016-11-01

    This study compared the effect of cyclic neuromuscular electrical stimulation (NMES), electromyographically (EMG)-triggered NMES, and sensory stimulation on motor impairment and activity limitations in patients with upper-limb hemiplegia. This was a multicenter, single-blind, multiarm parallel-group study of nonhospitalized hemiplegic stroke survivors within 6 months of stroke. A total of 122 individuals were randomized to receive either cyclic NMES, EMG-triggered NMES, or sensory stimulation twice every weekday in 40-minute sessions, over an 8 week-period. Patients were followed for 6 months after treatment concluded. There were significant increases in the Fugl-Meyer Assessment [F(1, 111) = 92.6, P stimulation therapy applied within 6 months of stroke. Improvements were likely a result of spontaneous recovery. There was no difference based on the type of electrical stimulation that was administered. © The Author(s) 2016.

  20. Motor unit number index (MUNIX) derivation from the relationship between the area and power of surface electromyogram: a computer simulation and clinical study

    Science.gov (United States)

    Miralles, Francesc

    2018-06-01

    Objective. The motor unit number index (MUNIX) is a technique based on the surface electromyogram (sEMG) that is gaining acceptance as a method for monitoring motor neuron loss, because it is reliable and produces less discomfort than other electrodiagnostic techniques having the same intended purpose. MUNIX assumes that the relationship between the area of sEMG obtained at increasing levels of muscle activation and the values of a variable called ‘ideal case motor unit count’ (ICMUC), defined as the product of the ratio between area and power of the compound muscle action potential (CMAP) by that of the sEMG, is described by a decreasing power function. Nevertheless, the reason for this comportment is unknown. The objective of this work is to investigate if the definition of MUNIX could derive from more basic properties of the sEMG. Approach. The CMAP and sEMG epochs obtained at different levels of muscle activation from (1) the abductor pollicis brevis (APB) muscle of persons with and without a carpal tunnel syndrome (CTS) and (2) from a computer model of sEMG generation previously published were analysed. Main results. MUNIX reflects the power relationship existing between the area and power of a sEMG. The exponent of this function was smaller in patients with motor CTS than in the rest of the subjects. The analysis of the relationship between the area and power of a sEMG could aid in distinguishing a MUNIX reduction due to a motoneuron loss from that due to a loss of muscle fibre. Significance. MUNIX is derived from the relationship between the area and power of a sEMG. This relationship changes when there is a loss of motor units (MUs), which partially explains the diagnostic sensibility of MUNIX. Although the reasons for this change are unknown, it could reflect an increase in the proportion of MUs of great amplitude.

  1. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1993-04-01

    This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

  2. Are fatigue-related EMG-parameters correlated to trunk extensor muscles fatigue induced by the Sörensen test?

    OpenAIRE

    Demoulin Christophe; George, Florian; Matheve, Thomas; Jidovtseff, Boris; Vanderthommen, Marc

    2016-01-01

    The Sorensen test has been extensively studied and is a rapid, simple, and reproducible evaluation of the trunk extensor muscles [1]. It is often considered as a fatigue test because fatigue-related electromyographic (EMG) parameters change throughout the test [2]; however, only recently it has been confirmed that this test induces a decrease of trunk extensor force during a maximal voluntary contraction (MVC) [3], which best characterises muscle fatigue. The main aim of this stud...

  3. Prediction of Above-elbow Motions in Amputees, based on Electromyographic(EMG Signals, Using Nonlinear Autoregressive Exogenous (NARX Model

    Directory of Open Access Journals (Sweden)

    Ali Akbar Akbari

    2014-08-01

    Full Text Available Introduction In order to improve the quality of life of amputees, biomechatronic researchers and biomedical engineers have been trying to use a combination of various techniques to provide suitable rehabilitation systems. Diverse biomedical signals, acquired from a specialized organ or cell system, e.g., the nervous system, are the driving force for the whole system. Electromyography(EMG, as an experimental technique,is concerned with the development, recording, and analysis of myoelectric signals. EMG-based research is making progress in the development of simple, robust, user-friendly, and efficient interface devices for the amputees. Materials and Methods Prediction of muscular activity and motion patterns is a common, practical problem in prosthetic organs. Recurrent neural network (RNN models are not only applicable for the prediction of time series, but are also commonly used for the control of dynamical systems. The prediction can be assimilated to identification of a dynamic process. An architectural approach of RNN with embedded memory is Nonlinear Autoregressive Exogenous (NARX model, which seems to be suitable for dynamic system applications. Results Performance of NARX model is verified for several chaotic time series, which are applied as input for the neural network. The results showed that NARX has the potential to capture the model of nonlinear dynamic systems. The R-value and MSE are  and  , respectively. Conclusion  EMG signals of deltoid and pectoralis major muscles are the inputs of the NARX  network. It is possible to obtain EMG signals of muscles in other arm motions to predict the lost functions of the absent arm in above-elbow amputees, using NARX model.

  4. Exoskeleton Technology in Rehabilitation: Towards an EMG-Based Orthosis System for Upper Limb Neuromotor Rehabilitation

    Directory of Open Access Journals (Sweden)

    Luis Manuel Vaca Benitez

    2013-01-01

    Full Text Available The rehabilitation of patients should not only be limited to the first phases during intense hospital care but also support and therapy should be guaranteed in later stages, especially during daily life activities if the patient’s state requires this. However, aid should only be given to the patient if needed and as much as it is required. To allow this, automatic self-initiated movement support and patient-cooperative control strategies have to be developed and integrated into assistive systems. In this work, we first give an overview of different kinds of neuromuscular diseases, review different forms of therapy, and explain possible fields of rehabilitation and benefits of robotic aided rehabilitation. Next, the mechanical design and control scheme of an upper limb orthosis for rehabilitation are presented. Two control models for the orthosis are explained which compute the triggering function and the level of assistance provided by the device. As input to the model fused sensor data from the orthosis and physiology data in terms of electromyography (EMG signals are used.

  5. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation

    Science.gov (United States)

    Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

    2016-01-01

    In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion. PMID:26881743

  6. Imaging seizure activity: a combined EEG/EMG-fMRI study in reading epilepsy.

    Science.gov (United States)

    Salek-Haddadi, Afraim; Mayer, Thomas; Hamandi, Khalid; Symms, Mark; Josephs, Oliver; Fluegel, Dominique; Woermann, Friedrich; Richardson, Mark P; Noppeney, Uta; Wolf, Peter; Koepp, Matthias J

    2009-02-01

    To characterize the spatial relationship between activations related to language-induced seizure activity, language processing, and motor control in patients with reading epilepsy. We recorded and simultaneously monitored several physiological parameters [voice-recording, electromyography (EMG), electrocardiography (ECG), electroencephalography (EEG)] during blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in nine patients with reading epilepsy. Individually tailored language paradigms were used to induce and record habitual seizures inside the MRI scanner. Voxel-based morphometry (VBM) was used for structural brain analysis. Reading-induced seizures occurred in six out of nine patients. One patient experienced abundant orofacial reflex myocloni during silent reading in association with bilateral frontal or generalized epileptiform discharges. In a further five patients, symptoms were only elicited while reading aloud with self-indicated events. Consistent activation patterns in response to reading-induced myoclonic seizures were observed within left motor and premotor areas in five of these six patients, in the left striatum (n = 4), in mesiotemporal/limbic areas (n = 4), in Brodmann area 47 (n = 3), and thalamus (n = 2). These BOLD activations were overlapping or adjacent to areas physiologically activated during language and facial motor tasks. No subtle structural abnormalities common to all patients were identified using VBM, but one patient had a left temporal ischemic lesion. Based on the findings, we hypothesize that reflex seizures occur in reading epilepsy when a critical mass of neurons are activated through a provoking stimulus within corticoreticular and corticocortical circuitry subserving normal functions.

  7. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation.

    Science.gov (United States)

    Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

    2016-01-01

    In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion.

  8. Shoe midsole longitudinal bending stiffness and running economy, joint energy, and EMG.

    Science.gov (United States)

    Roy, Jean-Pierre R; Stefanyshyn, Darren J

    2006-03-01

    It has been shown that mechanical energy is dissipated at the metatarsophalangeal (MTP) joint during running and jumping. Furthermore, increasing the longitudinal bending stiffness of the midsole significantly reduced the energy dissipated at the MTP joint and increased jump performance. It was hypothesized that increasing midsole longitudinal bending stiffness would also lead to improvements in running economy. This study investigated the influence of midsole longitudinal bending stiffness on running economy (performance variable) and evaluated the local effects on joint energetics and muscular activity. Carbon fiber plates were inserted into running shoe midsoles and running economy, joint energy, and electromyographic (EMG) data were collected on 13 subjects. Approximately a 1% metabolic energy savings was observed when subjects ran in a stiff midsole relative to the control midsole. Subjects with a greater body mass had a greater decrease in oxygen consumption rates in the stiff midsole relative to the control midsole condition. The stiffer midsoles showed no significant differences in energy absorption at the MTP joint compared with the control shoe. Finally, no significant changes were observed in muscular activation. Increasing midsole longitudinal bending stiffness led to improvements in running economy, yet the underlying mechanisms that can be attributed to this improvement are still not fully understood.

  9. Finger language recognition based on ensemble artificial neural network learning using armband EMG sensors.

    Science.gov (United States)

    Kim, Seongjung; Kim, Jongman; Ahn, Soonjae; Kim, Youngho

    2018-04-18

    Deaf people use sign or finger languages for communication, but these methods of communication are very specialized. For this reason, the deaf can suffer from social inequalities and financial losses due to their communication restrictions. In this study, we developed a finger language recognition algorithm based on an ensemble artificial neural network (E-ANN) using an armband system with 8-channel electromyography (EMG) sensors. The developed algorithm was composed of signal acquisition, filtering, segmentation, feature extraction and an E-ANN based classifier that was evaluated with the Korean finger language (14 consonants, 17 vowels and 7 numbers) in 17 subjects. E-ANN was categorized according to the number of classifiers (1 to 10) and size of training data (50 to 1500). The accuracy of the E-ANN-based classifier was obtained by 5-fold cross validation and compared with an artificial neural network (ANN)-based classifier. As the number of classifiers (1 to 8) and size of training data (50 to 300) increased, the average accuracy of the E-ANN-based classifier increased and the standard deviation decreased. The optimal E-ANN was composed with eight classifiers and 300 size of training data, and the accuracy of the E-ANN was significantly higher than that of the general ANN.

  10. Is EMG of the lower leg dependent on weekly running mileage?

    Science.gov (United States)

    Baur, H; Hirschmüller, A; Müller, S; Cassel, M; Mayer, F

    2012-01-01

    Neuromuscular activity of the lower leg is dependent on the task performed, speed of movement and gender. Whether training volume influences neuromuscular activity is not known. The EMG of physically active persons differing in running mileage was analysed to investigate this. 55 volunteers were allocated to a low (LM:  30 km &  45 km) group according to their weekly running volume. Neuromuscular activity of the lower leg was measured during running (3.33 m·s - 1). Mean amplitude values for preactivation, weight acceptance and push-off were calculated and normalised to the mean activity of the entire gait cycle.Higher activity in the gastrocnemius group was observed in weight acceptance in LM compared to IM (+30%) and HM (+25%) but lower activity was present in the push-off for LM compared to IM and HM. For the peroneal muscle, differences were present in the push-off where HM showed increased activity compared to IM (+24%) and LM (+60%). The tibial muscle revealed slightly lower activity during preactivation for the high mileage runners. Neuromuscular activity differs during stance between the high and intermediate group compared to low mileage runners. Slight adaptations in neuromuscular activation indicate a more target-oriented activation strategy possibly due to repetitive training in runners with higher weekly mileage. © Georg Thieme Verlag KG Stuttgart · New York.

  11. Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation.

    Directory of Open Access Journals (Sweden)

    Luka Peternel

    Full Text Available In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion.

  12. Adductor magnus: An EMG investigation into proximal and distal portions and direction specific action.

    Science.gov (United States)

    Benn, Matthew L; Pizzari, Tania; Rath, Leanne; Tucker, Kylie; Semciw, Adam I

    2018-05-01

    Cadaveric studies indicate that adductor magnus is structurally partitioned into at least two regions. The aim of this study was to investigate the direction-specific actions of proximal and distal portions of adductor magnus, and in doing so determine if these segments have distinct functional roles. Fine-wire EMG electrodes were inserted into two portions of adductor magnus of 12 healthy young adults. Muscle activity was recorded during maximum voluntary isometric contractions (MVICs) across eight tests (hip flexion/extension, internal/external rotation, abduction, and adduction at 0°, 45°, and 90° hip flexion). Median activity within each action (normalized to peak) was compared between segments using repeated measures nonparametric tests (α = 0.05). An effect size (ES = z-score/√sample size) was calculated to determine the magnitude of difference between muscle segments. The relative contribution of each muscle segment differed significantly during internal rotation (P magnus has at least two functionally unique regions. Differences were most evident during rotation. The different direction-specific actions may imply that each segment performs separate roles in hip stability and movement. These findings may have implications on injury prevention and rehabilitation for adductor-related groin injuries, hamstring strain injury, and hip pathology. Clin. Anat. 31:535-543, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

  13. Simulation of parameters of the stationary facility "ATLAS" by means of disk EMG

    CERN Document Server

    Buyko, A M; Ivanova, G G; Gorbachev, Yu N; Kuzaev, A I; Kulagin, A A; Mokhov, V N; Pak, S V; Petrukhin, A A; Sofronov, V N; Yakubov, V B; Anderson, B G; Atchison, W L; Clark, D A; Faehl, R J; Lindemuth, I R; Reinovsky, R E; Rodríguez, G; Stokes, J L; Tabaka, L J

    2001-01-01

    Summary form only given, as follows. The paper presents the results of the Russian-American experiment (ALT-1) on simulation of the ATLAS capacitor bank energy parameters in the liner load. The capacitor bank ATLAS is being constructed in USA for high energy density physics research (A New Energy Density Physics Research Facility: ATLAS). The experiment was conducted at VNIIEF in November 1999. The experimental device consisted of helical and disk explosive magnetic generators (EMG), of electrically exploded foil opening switch (FOS) and of the liner load connected to FOS with the help of exploded closing switch. The initial parameters of the liner made of technically pure aluminum were: outer radius 40 mm, operating height -~40 mm, thickness -2 mm. In the experiment the liner was driven by the pulse of current with the amplitude 31.5 MA with a total risetime of ~4 ms. 50-gram liner' velocity, measured by the laser interferometer VISAR, was * 10 km/s. The paper gives as well some other characteristics obtaine...

  14. Reliable MRI and MRN signs of nerve and muscle injury following trauma to the shoulder with EMG and

    Directory of Open Access Journals (Sweden)

    Omar Ahmed Hassanien

    2016-09-01

    Full Text Available Purpose: To evaluate the role of MRN in diagnosis of suprascapular nerve injury and its relation with muscle injury after shoulder trauma in comparison with the EMG results. Patient & method: The study was carried on 30 patients following trauma to the shoulder, either direct trauma (80% or indirect trauma in 20% presented clinically with shoulder pain and limited movements and referred for MRI examination. The MRI results were correlated with EMG results for all cases. Results: Those 30 cases were divided into 13 cases with acute onset, 10 cases with subacute onset and 7 cases with chronic onset. In acute injuries, 5 cases (5/30 showed combined nerve and muscle injuries, 4 cases (4/30 showed nerve injury only and 5 cases (5/30 showed muscle injury only. In subacute injuries 5 cases (5/30 showed combined muscle and nerve injuries and 5 cases (5/30 showed muscle injury only, in chronic 7 cases (7/30 showed combined nerve and muscle injuries, where EMG showed sharp waves only in 7 cases which are all chronic. Conclusion: MRN is the best modality in diagnosis of nerve injuries and associated muscle injuries in one sitting with no obvious difficulties in the examination. MRN associating with the routine MRI elevated the sensitivity of diagnosis.

  15. EMG normalization method based on grade 3 of manual muscle testing: Within- and between-day reliability of normalization tasks and application to gait analysis.

    Science.gov (United States)

    Tabard-Fougère, Anne; Rose-Dulcina, Kevin; Pittet, Vincent; Dayer, Romain; Vuillerme, Nicolas; Armand, Stéphane

    2018-02-01

    Electromyography (EMG) is an important parameter in Clinical Gait Analysis (CGA), and is generally interpreted with timing of activation. EMG amplitude comparisons between individuals, muscles or days need normalization. There is no consensus on existing methods. The gold standard, maximum voluntary isometric contraction (MVIC), is not adapted to pathological populations because patients are often unable to perform an MVIC. The normalization method inspired by the isometric grade 3 of manual muscle testing (isoMMT3), which is the ability of a muscle to maintain a position against gravity, could be an interesting alternative. The aim of this study was to evaluate the within- and between-day reliability of the isoMMT3 EMG normalizing method during gait compared with the conventional MVIC method. Lower limb muscles EMG (gluteus medius, rectus femoris, tibialis anterior, semitendinosus) were recorded bilaterally in nine healthy participants (five males, aged 29.7±6.2years, BMI 22.7±3.3kgm -2 ) giving a total of 18 independent legs. Three repeated measurements of the isoMMT3 and MVIC exercises were performed with an EMG recording. EMG amplitude of the muscles during gait was normalized by these two methods. This protocol was repeated one week later. Within- and between-day reliability of normalization tasks were similar for isoMMT3 and MVIC methods. Within- and between-day reliability of gait EMG normalized by isoMMT3 was higher than with MVIC normalization. These results indicate that EMG normalization using isoMMT3 is a reliable method with no special equipment needed and will support CGA interpretation. The next step will be to evaluate this method in pathological populations. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Classification of Flotation Frothers

    Directory of Open Access Journals (Sweden)

    Jan Drzymala

    2018-02-01

    Full Text Available In this paper, a scheme of flotation frothers classification is presented. The scheme first indicates the physical system in which a frother is present and four of them i.e., pure state, aqueous solution, aqueous solution/gas system and aqueous solution/gas/solid system are distinguished. As a result, there are numerous classifications of flotation frothers. The classifications can be organized into a scheme described in detail in this paper. The frother can be present in one of four physical systems, that is pure state, aqueous solution, aqueous solution/gas and aqueous solution/gas/solid system. It results from the paper that a meaningful classification of frothers relies on choosing the physical system and next feature, trend, parameter or parameters according to which the classification is performed. The proposed classification can play a useful role in characterizing and evaluation of flotation frothers.

  17. EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model.

    Science.gov (United States)

    Menegaldo, Luciano Luporini; de Oliveira, Liliam Fernandes; Minato, Kin K

    2014-04-04

    This paper describes the "EMG Driven Force Estimator (EMGD-FE)", a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. An example of the application's functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues.

  18. Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.

    Science.gov (United States)

    Najdi, Shirin; Gharbali, Ali Abdollahi; Fonseca, José Manuel

    2017-08-18

    Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual process of sleep stage classification is time-consuming, subjective and costly. Therefore, in order to improve the accuracy and efficiency of the sleep stage classification, researchers have been trying to develop automatic classification algorithms. Automatic sleep stage classification mainly consists of three steps: pre-processing, feature extraction and classification. Since classification accuracy is deeply affected by the extracted features, a poor feature vector will adversely affect the classifier and eventually lead to low classification accuracy. Therefore, special attention should be given to the feature extraction and selection process. In this paper the performance of seven feature selection methods, as well as two feature rank aggregation methods, were compared. Pz-Oz EEG, horizontal EOG and submental chin EMG recordings of 22 healthy males and females were used. A comprehensive feature set including 49 features was extracted from these recordings. The extracted features are among the most common and effective features used in sleep stage classification from temporal, spectral, entropy-based and nonlinear categories. The feature selection methods were evaluated and compared using three criteria: classification accuracy, stability, and similarity. Simulation results show that MRMR-MID achieves the highest classification performance while Fisher method provides the most stable ranking. In our simulations, the performance of the aggregation methods was in the average level, although they are known to generate more stable results and better accuracy. The Borda and RRA rank aggregation methods could not outperform significantly the conventional feature ranking methods. Among

  19. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  20. Fractal feature of sEMG from Flexor digitorum superficialis muscle correlated with levels of contraction during low-level finger flexions.

    Science.gov (United States)

    Arjunan, Sridhar P; Kumar, Dinesh K; Naik, Ganesh R

    2010-01-01

    This research paper reports an experimental study on identification of the changes in fractal properties of surface Electromyogram (sEMG) with the changes in the force levels during low-level finger flexions. In the previous study, the authors have identified a novel fractal feature, Maximum fractal length (MFL) as a measure of strength of low-level contractions and has used this feature to identify various wrist and finger movements. This study has tested the relationship between the MFL and force of contraction. The results suggest that changes in MFL is correlated with the changes in contraction levels (20%, 50% and 80% maximum voluntary contraction (MVC)) during low-level muscle activation such as finger flexions. From the statistical analysis and by visualisation using box-plot, it is observed that MFL (p ≈ 0.001) is a more correlated to force of contraction compared to RMS (p≈0.05), even when the muscle contraction is less than 50% MVC during low-level finger flexions. This work has established that this fractal feature will be useful in providing information about changes in levels of force during low-level finger movements for prosthetic control or human computer interface.

  1. Test-retest reliability of trunk motor variability measured by large-array surface electromyography.

    Science.gov (United States)

    Abboud, Jacques; Nougarou, François; Loranger, Michel; Descarreaux, Martin

    2015-01-01

    The objective of this study was to evaluate the test-retest reliability of the trunk muscle activity distribution in asymptomatic participants during muscle fatigue using large-array surface electromyography (EMG). Trunk muscle activity distribution was evaluated twice, with 3 to 4 days between them, in 27 asymptomatic volunteers using large-array surface EMG. Motor variability, assessed with 2 different variables (the centroid coordinates of the root mean square map and the dispersion variable), was evaluated during a low back muscle fatigue task. Test-retest reliability of muscle activity distribution was obtained using Pearson correlation coefficients. A shift in the distribution of EMG amplitude toward the lateral-caudal region of the lumbar erector spinae induced by muscle fatigue was observed. Moderate to very strong correlations were found between both sessions in the last 3 phases of the fatigue task for both motor variability variables, whereas weak to moderate correlations were found in the first phases of the fatigue task only for the dispersion variable. These findings show th