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Sample records for surface emg classification

  1. Comparison of surface and intramuscular EMG pattern recognition for simultaneous wrist/hand motion classification.

    Science.gov (United States)

    Smith, Lauren H; Hargrove, Levi J

    2013-01-01

    The simultaneous control of multiple degrees of freedom (DOFs) is important for the intuitive, life-like control of artificial limbs. The objective of this study was to determine whether the use of intramuscular electromyogram (EMG) improved pattern classification of simultaneous wrist/hand movements compared to surface EMG. Two pattern classification methods were used in this analysis, and were trained to predict 1-DOF and 2-DOF movements involving wrist rotation, wrist flexion/extension, and hand open/close. The classification methods used were (1) a single pattern classifier discriminating between 1-DOF and 2-DOF motion classes, and (2) a parallel set of three classifiers to predict the activity of each of the 3 DOFs. We demonstrate that in this combined wrist/hand classification task, the use of intramuscular EMG significantly decreases classification error compared to surface EMG for the parallel configuration (p<0.01), but not for the single classifier. We also show that the use of intramuscular EMG mitigates the increase in errors produced when the parallel classifier method is trained without 2-DOF motion class data.

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

    Science.gov (United States)

    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).

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

    Science.gov (United States)

    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.

  4. Predicting 3D lip shapes using facial surface EMG

    NARCIS (Netherlands)

    Eskes, Merijn; van Alphen, Maarten J. A.; Balm, Alfons J. M.; Smeele, Ludi E.; Brandsma, Dieta; van der Heijden, Ferdinand

    2017-01-01

    Aim The aim of this study is to prove that facial surface electromyography (sEMG) conveys sufficient information to predict 3D lip shapes. High sEMG predictive accuracy implies we could train a neural control model for activation of biomechanical models by simultaneously recording sEMG signals and

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

    Science.gov (United States)

    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.

  6. A motion-classification strategy based on sEMG-EEG signal combination for upper-limb amputees.

    Science.gov (United States)

    Li, Xiangxin; Samuel, Oluwarotimi Williams; Zhang, Xu; Wang, Hui; Fang, Peng; Li, Guanglin

    2017-01-07

    Most of the modern motorized prostheses are controlled with the surface electromyography (sEMG) recorded on the residual muscles of amputated limbs. However, the residual muscles are usually limited, especially after above-elbow amputations, which would not provide enough sEMG for the control of prostheses with multiple degrees of freedom. Signal fusion is a possible approach to solve the problem of insufficient control commands, where some non-EMG signals are combined with sEMG signals to provide sufficient information for motion intension decoding. In this study, a motion-classification method that combines sEMG and electroencephalography (EEG) signals were proposed and investigated, in order to improve the control performance of upper-limb prostheses. Four transhumeral amputees without any form of neurological disease were recruited in the experiments. Five motion classes including hand-open, hand-close, wrist-pronation, wrist-supination, and no-movement were specified. During the motion performances, sEMG and EEG signals were simultaneously acquired from the skin surface and scalp of the amputees, respectively. The two types of signals were independently preprocessed and then combined as a parallel control input. Four time-domain features were extracted and fed into a classifier trained by the Linear Discriminant Analysis (LDA) algorithm for motion recognition. In addition, channel selections were performed by using the Sequential Forward Selection (SFS) algorithm to optimize the performance of the proposed method. The classification performance achieved by the fusion of sEMG and EEG signals was significantly better than that obtained by single signal source of either sEMG or EEG. An increment of more than 14% in classification accuracy was achieved when using a combination of 32-channel sEMG and 64-channel EEG. Furthermore, based on the SFS algorithm, two optimized electrode arrangements (10-channel sEMG + 10-channel EEG, 10-channel sEMG + 20-channel

  7. Surface EMG measurements during fMRI at 3T : Accurate EMG recordings after artifact correction

    NARCIS (Netherlands)

    van Duinen, Hiske; Zijdewind, Inge; Hoogduin, H; Maurits, N

    2005-01-01

    In this experiment, we have measured surface EMG of the first dorsal interosseus during predefined submaximal isometric contractions (5, 15, 30, 50, and 70% of maximal force) of the index finger simultaneously with fMRI measurements. Since we have used sparse sampling fMRI (3-s scanning; 2-s

  8. Predicting 3D lip shapes using facial surface EMG.

    Directory of Open Access Journals (Sweden)

    Merijn Eskes

    Full Text Available The aim of this study is to prove that facial surface electromyography (sEMG conveys sufficient information to predict 3D lip shapes. High sEMG predictive accuracy implies we could train a neural control model for activation of biomechanical models by simultaneously recording sEMG signals and their associated motions.With a stereo camera set-up, we recorded 3D lip shapes and simultaneously performed sEMG measurements of the facial muscles, applying principal component analysis (PCA and a modified general regression neural network (GRNN to link the sEMG measurements to 3D lip shapes. To test reproducibility, we conducted our experiment on five volunteers, evaluating several sEMG features and window lengths in unipolar and bipolar configurations in search of the optimal settings for facial sEMG.The errors of the two methods were comparable. We managed to predict 3D lip shapes with a mean accuracy of 2.76 mm when using the PCA method and 2.78 mm when using modified GRNN. Whereas performance improved with shorter window lengths, feature type and configuration had little influence.

  9. Features extraction and multi-classification of sEMG using a GPU-Accelerated GA/MLP hybrid algorithm.

    Science.gov (United States)

    Luo, Weizhen; Zhang, Zhongnan; Wen, Tingxi; Li, Chunfeng; Luo, Ziheng

    2017-01-01

    Surface electromyography (sEMG) signal is the combined effect of superficial muscle EMG and neural electrical activity. In recent years, researchers did large amount of human-machine system studies by using the physiological signals as control signals. To develop and test a new multi-classification method to improve performance of analyzing sEMG signals based on public sEMG dataset. First, ten features were selected as candidate features. Second, a genetic algorithm (GA) was applied to select representative features from the initial ten candidates. Third, a multi-layer perceptron (MLP) classifier was trained by the selected optimal features. Last, the trained classifier was used to predict the classes of sEMG signals. A special graphics processing unit (GPU) was used to speed up the learning process. Experimental results show that the classification accuracy of the new method reached higher than 90%. Comparing to other previously reported results, using the new method yielded higher performance. The proposed features selection method is effective and the classification result is accurate. In addition, our method could have practical application value in medical prosthetics and the potential to improve robustness of myoelectric pattern recognition.

  10. Transradial Amputee Gesture Classification Using an Optimal Number of sEMG Sensors: An Approach Using ICA Clustering.

    Science.gov (United States)

    Naik, Ganesh R; Al-Timemy, Ali H; Nguyen, Hung T

    2016-08-01

    Surface electromyography (sEMG)-based pattern recognition studies have been widely used to improve the classification accuracy of upper limb gestures. Information extracted from multiple sensors of the sEMG recording sites can be used as inputs to control powered upper limb prostheses. However, usage of multiple EMG sensors on the prosthetic hand is not practical and makes it difficult for amputees due to electrode shift/movement, and often amputees feel discomfort in wearing sEMG sensor array. Instead, using fewer numbers of sensors would greatly improve the controllability of prosthetic devices and it would add dexterity and flexibility in their operation. In this paper, we propose a novel myoelectric control technique for identification of various gestures using the minimum number of sensors based on independent component analysis (ICA) and Icasso clustering. The proposed method is a model-based approach where a combination of source separation and Icasso clustering was utilized to improve the classification performance of independent finger movements for transradial amputee subjects. Two sEMG sensor combinations were investigated based on the muscle morphology and Icasso clustering and compared to Sequential Forward Selection (SFS) and greedy search algorithm. The performance of the proposed method has been validated with five transradial amputees, which reports a higher classification accuracy ( > 95%). The outcome of this study encourages possible extension of the proposed approach to real time prosthetic applications.

  11. 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...... between sessions. Single pulse (at 120% and 140% of the resting motor threshold (rMT)) and paired pulse (2 ms and 15 ms paired pulse) transcranial magnetic stimulation (TMS) were used to elicit MEPs in the SMC which were recorded using sEMG. Results: ≈50% of participants (range: 42%-58%; depending...... 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...

  12. Recording and conditioning of surface EMG signal for decomposition

    Czech Academy of Sciences Publication Activity Database

    Pošusta, A.; Otáhal, Jakub

    2012-01-01

    Roč. 8, č. 30 (2012), s. 28-31 ISSN 1801-1217 R&D Projects: GA AV ČR(CZ) 1QS501210509; GA ČR(CZ) GBP304/12/G069 Grant - others:GA MŠk(CZ) LH12070 Institutional support: RVO:67985823 Keywords : surface electromyography * decomposition * EMG Lab * prosthetics Subject RIV: FH - Neurology

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

    Science.gov (United States)

    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.

  14. 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

  15. A two-dimensional matrix image based feature extraction method for classification of sEMG: A comparative analysis based on SVM, KNN and RBF-NN.

    Science.gov (United States)

    Wen, Tingxi; Zhang, Zhongnan; Qiu, Ming; Zeng, Ming; Luo, Weizhen

    2017-01-01

    The computer mouse is an important human-computer interaction device. But patients with physical finger disability are unable to operate this device. Surface EMG (sEMG) can be monitored by electrodes on the skin surface and is a reflection of the neuromuscular activities. Therefore, we can control limbs auxiliary equipment by utilizing sEMG classification in order to help the physically disabled patients to operate the mouse. To develop a new a method to extract sEMG generated by finger motion and apply novel features to classify sEMG. A window-based data acquisition method was presented to extract signal samples from sEMG electordes. Afterwards, a two-dimensional matrix image based feature extraction method, which differs from the classical methods based on time domain or frequency domain, was employed to transform signal samples to feature maps used for classification. In the experiments, sEMG data samples produced by the index and middle fingers at the click of a mouse button were separately acquired. Then, characteristics of the samples were analyzed to generate a feature map for each sample. Finally, the machine learning classification algorithms (SVM, KNN, RBF-NN) were employed to classify these feature maps on a GPU. The study demonstrated that all classifiers can identify and classify sEMG samples effectively. In particular, the accuracy of the SVM classifier reached up to 100%. The signal separation method is a convenient, efficient and quick method, which can effectively extract the sEMG samples produced by fingers. In addition, unlike the classical methods, the new method enables to extract features by enlarging sample signals' energy appropriately. The classical machine learning classifiers all performed well by using these features.

  16. High energy spectrogram with integrated prior knowledge for EMG-based locomotion classification.

    Science.gov (United States)

    Joshi, Deepak; Nakamura, Bryson H; Hahn, Michael E

    2015-05-01

    Electromyogram (EMG) signal representation is crucial in classification applications specific to locomotion and transitions. For a given signal, classification can be performed using discriminant functions or if-else rule sets, using learning algorithms derived from training examples. In the present work, a spectrogram based approach was developed to classify (EMG) signals for locomotion mode. Spectrograms for each muscle were calculated and summed to develop a histogram. If-else rules were used to classify test data based on a matching score. Prior knowledge of locomotion type reduced class space to exclusive locomotion modes. The EMG data were collected from seven leg muscles in a sample of able-bodied subjects while walking over ground (W), ascending stairs (SA) and the transition between (W-SA). Three muscles with least discriminating power were removed from the original data set to examine the effect on classification accuracy. Initial classification error was <20% across all modes, using leave one out cross validation. Use of prior knowledge reduced the average classification error to <11%. Removing three EMG channels decreased the classification accuracy by 10.8%, 24.3%, and 8.1% for W, W-SA, and SA respectively, and reduced computation time by 42.8%. This approach may be useful in the control of multi-mode assistive devices. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

  17. Surface EMG in advanced hand prosthetics.

    Science.gov (United States)

    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.

  18. 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

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

    Science.gov (United States)

    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.

  20. Surface electromyogram signals classification based on bispectrum.

    Science.gov (United States)

    Orosco, Eugenio; Lopez, Natalia; Soria, Carlos; di Sciascio, Fernando

    2010-01-01

    This paper bispectrum is used to classify human arm movements and control a robotic arm based on upper limb's surface electromyogram signals (sEMG). We use bispectrum based on third-order cumulant to parameterize sEMG signals and classify elbow flexion and extension, forearm pronation and supination, and rest states by an artificial neural network (ANN). Finally, a robotic manipulator is controlled based on classification and parameters extracted from the signals. All this process is made in real-time using QNX ® operative system.

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

    Directory of Open Access Journals (Sweden)

    Xiaolong Zhai

    2017-07-01

    Full Text Available 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.

  2. 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

    ... to estimate muscle fatigue. In this paper, theoretical relationships between surface EMG amplitude measures and mean motor unit firing rates and muscle fiber conduction velocity (MFCV) are established...

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  5. Effect of Vibration Training on Anaerobic Power and Quardroceps Surface EMG in Long Jumpers

    Science.gov (United States)

    Liu, Bin; Luo, Jiong

    2015-01-01

    Objective: To explore the anaerobic power and surface EMG (sEMG) of quardrocep muscle in lower extremities after single vibration training intervention. Methods: 8 excellent male long jumpers voluntarily participated in this study. Four intervention modes were devised, including high frequency high amplitude (HFHA,30Hz,6mm), low frequency low…

  6. Estimation of Upper Limb Joint Angle Using Surface EMG Signal

    Directory of Open Access Journals (Sweden)

    Yee Mon Aung

    2013-10-01

    Full Text Available In the development of robot-assisted rehabilitation systems for upper limb rehabilitation therapy, human electromyogram (EMG is widely used due to its ability to detect the user intended motion. EMG is one kind of biological signal that can be recorded to evaluate the performance of skeletal muscles by means of a sensor electrode. Based on recorded EMG signals, user intended motion could be extracted via estimation of joint torque, force or angle. Therefore, this estimation becomes one of the most important factors to achieve accurate user intended motion. In this paper, an upper limb joint angle estimation methodology is proposed. A back propagation neural network (BPNN is developed to estimate the shoulder and elbow joint angles from the recorded EMG signals. A Virtual Human Model (VHM is also developed and integrated with BPNN to perform the simulation of the estimated angle. The relationships between sEMG signals and upper limb movements are observed in this paper. The effectiveness of our developments is evaluated with four healthy subjects and a VHM simulation. The results show that the methodology can be used in the estimation of joint angles based on EMG.

  7. Application of higher order statistics to surface electromyogram signal classification.

    Science.gov (United States)

    Nazarpour, Kianoush; Sharafat, Ahmad R; Firoozabadi, S Mohammad P

    2007-10-01

    We propose a novel approach for surface electromyogram (sEMG) signal classification. This approach utilizes higher order statistics of sEMG signal to classify four primitive motions, i.e., elbow flexion, elbow extension, forearm supination, and forearm pronation. In documented research, the sEMG signal generated during isometric contraction is modeled by a stationary process whose probability density function (pdf) is assumed to be either Gaussian or Laplacian. In this paper, using Negentropy, we demonstrate that the level of non-Gaussianity of sEMG signal recorded in muscular forces below 25% of maximum voluntary contraction (MVC) is significant. Therefore, application of higher order statistics in sEMG signal processing is justified, due to the fact that more useful information can be extracted from the corresponding higher order statistics. An accurate classification is achieved by using the sequential forward selection (SFS) method for reducing of the dimensionality of feature space and the K-nearest neighbor (KNN) classifier. The results indicate that the proposed approach provides higher sEMG correct classification rates as compared to the existing methods.

  8. EMG pattern classification to control a hand orthosis for functional grasp assistance after stroke.

    Science.gov (United States)

    Meeker, Cassie; Park, Sangwoo; Bishop, Lauri; Stein, Joel; Ciocarlie, Matei

    2017-07-01

    Wearable orthoses can function both as assistive devices, which allow the user to live independently, and as rehabilitation devices, which allow the user to regain use of an impaired limb. To be fully wearable, such devices must have intuitive controls, and to improve quality of life, the device should enable the user to perform Activities of Daily Living. In this context, we explore the feasibility of using electromyography (EMG) signals to control a wearable exotendon device to enable pick and place tasks. We use an easy to don, commodity forearm EMG band with 8 sensors to create an EMG pattern classification control for an exotendon device. With this control, we are able to detect a user's intent to open, and can thus enable extension and pick and place tasks. In experiments with stroke survivors, we explore the accuracy of this control in both non-functional and functional tasks. Our results support the feasibility of developing wearable devices with intuitive controls which provide a functional context for rehabilitation.

  9. Neuromuscular functions in sportsmen and fibromyalgia patients : a surface EMG study in static and dynamic conditions

    NARCIS (Netherlands)

    Klaver-Krol, E.G.

    2012-01-01

    This thesis presents two studies, one involving sportsmen (sprinters versus endurance athletes) and one fibromyalgia patients (patients versus healthy controls). The studies have investigated muscular functions using a non-invasive method: surface electromyography (sEMG). In the sportsmen,

  10. Three-Dimensional Model of a Muscle and Simulation of its Surface EMG

    National Research Council Canada - National Science Library

    Schnetzer, M

    2001-01-01

    ...) and a simulation of its surface EMG. The simulations are part of a larger model including in addition the input system to the motoneuronal pool, the motoneuronal pool itself and the force generating mechanism...

  11. A Wearable System for Recognizing American Sign Language in Real-Time Using IMU and Surface EMG Sensors.

    Science.gov (United States)

    Wu, Jian; Sun, Lu; Jafari, Roozbeh

    2016-09-01

    A sign language recognition system translates signs performed by deaf individuals into text/speech in real time. Inertial measurement unit and surface electromyography (sEMG) are both useful modalities to detect hand/arm gestures. They are able to capture signs and the fusion of these two complementary sensor modalities will enhance system performance. In this paper, a wearable system for recognizing American Sign Language (ASL) in real time is proposed, fusing information from an inertial sensor and sEMG sensors. An information gain-based feature selection scheme is used to select the best subset of features from a broad range of well-established features. Four popular classification algorithms are evaluated for 80 commonly used ASL signs on four subjects. The experimental results show 96.16% and 85.24% average accuracies for intra-subject and intra-subject cross session evaluation, respectively, with the selected feature subset and a support vector machine classifier. The significance of adding sEMG for ASL recognition is explored and the best channel of sEMG is highlighted.

  12. Force control is related to low-frequency oscillations in force and surface EMG.

    Directory of Open Access Journals (Sweden)

    Hwasil Moon

    Full Text Available Force variability during constant force tasks is directly related to oscillations below 0.5 Hz in force. However, it is unknown whether such oscillations exist in muscle activity. The purpose of this paper, therefore, was to determine whether oscillations below 0.5 Hz in force are evident in the activation of muscle. Fourteen young adults (21.07 ± 2.76 years, 7 women performed constant isometric force tasks at 5% and 30% MVC by abducting the left index finger. We recorded the force output from the index finger and surface EMG from the first dorsal interosseous (FDI muscle and quantified the following outcomes: 1 variability of force using the SD of force; 2 power spectrum of force below 2 Hz; 3 EMG bursts; 4 power spectrum of EMG bursts below 2 Hz; and 5 power spectrum of the interference EMG from 10-300 Hz. The SD of force increased significantly from 5 to 30% MVC and this increase was significantly related to the increase in force oscillations below 0.5 Hz (R(2 = 0.82. For both force levels, the power spectrum for force and EMG burst was similar and contained most of the power from 0-0.5 Hz. Force and EMG burst oscillations below 0.5 Hz were highly coherent (coherence = 0.68. The increase in force oscillations below 0.5 Hz from 5 to 30% MVC was related to an increase in EMG burst oscillations below 0.5 Hz (R(2 = 0.51. Finally, there was a strong association between the increase in EMG burst oscillations below 0.5 Hz and the interference EMG from 35-60 Hz (R(2 = 0.95. In conclusion, this finding demonstrates that bursting of the EMG signal contains low-frequency oscillations below 0.5 Hz, which are associated with oscillations in force below 0.5 Hz.

  13. Surface Electromyography Signal Processing and Classification Techniques

    Science.gov (United States)

    Chowdhury, Rubana H.; Reaz, Mamun B. I.; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A. A.; Chellappan, Kalaivani; Chang, Tae. G.

    2013-01-01

    Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, 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. PMID:24048337

  14. Recognition and prediction of individual and combined muscular activation modes via surface EMG analysis

    Directory of Open Access Journals (Sweden)

    Daniel Graupe

    2010-09-01

    Full Text Available The paper discusses how recognition of individual and combined muscular activation modes (functions and the prediction of intended such modes can be accomplished by identifying parameters of noninvasive surface EMG signals. It outlines the mathematical analysis of surface EMG signal to facilitate such recognition and related prediction, including recognition of intention (in terms of attempts to activate motor functions from the EMG, without accessing the CNS itself, in cases where a patient, say, a high-level amputee does not have the final-activation muscles and joints. The EMG activity thus allows to interpret and recognize CNS commands from minute variations in the parameters of surface EMG signals that record changes in the firing of motor neurons triggering contractions in related muscle fibers. We note that although in popular media this is sometimes referred to as detection of “thoughts”, no thoughts are detected, but only motor-outcomes of thoughts as found in the EMG signal. Examples of concrete cases where such recognition or prediction were accomplished in the author’s lab and in devices that came out of that lab, are given as are references to these in the literature over the last 35 years.

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

    Science.gov (United States)

    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.

  16. Functional mapping of the pelvic floor and sphincter muscles from high-density surface EMG recordings.

    Science.gov (United States)

    Peng, Yun; He, Jinbao; Khavari, Rose; Boone, Timothy B; Zhang, Yingchun

    2016-11-01

    Knowledge of the innervation of pelvic floor and sphincter muscles is of great importance to understanding the pathophysiology of female pelvic floor dysfunctions. This report presents our high-density intravaginal and intrarectal electromyography (EMG) probes and a comprehensive innervation zone (IZ) imaging technique based on high-density EMG readings to characterize the IZ distribution. Both intravaginal and intrarectal probes are covered with a high-density surface electromyography electrode grid (8 × 8). Surface EMG signals were acquired in ten healthy women performing maximum voluntary contractions of their pelvic floor. EMG decomposition was performed to separate motor-unit action potentials (MUAPs) and then localize their IZs. High-density surface EMG signals were successfully acquired over the vaginal and rectal surfaces. The propagation patterns of muscle activity were clearly visualized for multiple muscle groups of the pelvic floor and anal sphincter. During each contraction, up to 218 and 456 repetitions of motor units were detected by the vaginal and rectal probes, respectively. MUAPs were separated with their IZs identified at various orientations and depths. The proposed probes are capable of providing a comprehensive mapping of IZs of the pelvic floor and sphincter muscles. They can be employed as diagnostic and preventative tools in clinical practices.

  17. DCT domain feature extraction scheme based on motor unit action potential of EMG signal for neuromuscular disease classification.

    Science.gov (United States)

    Doulah, Abul Barkat Mollah Sayeed Ud; Fattah, Shaikh Anowarul; Zhu, Wei-Ping; Ahmad, M Omair

    2014-01-01

    A feature extraction scheme based on discrete cosine transform (DCT) of electromyography (EMG) signals is proposed for the classification of normal event and a neuromuscular disease, namely the amyotrophic lateral sclerosis. Instead of employing DCT directly on EMG data, it is employed on the motor unit action potentials (MUAPs) extracted from the EMG signal via a template matching-based decomposition technique. Unlike conventional MUAP-based methods, only one MUAP with maximum dynamic range is selected for DCT-based feature extraction. Magnitude and frequency values of a few high-energy DCT coefficients corresponding to the selected MUAP are used as the desired feature which not only reduces computational burden, but also offers better feature quality with high within-class compactness and between-class separation. For the purpose of classification, the K-nearest neighbourhood classifier is employed. Extensive analysis is performed on clinical EMG database and it is found that the proposed method provides a very satisfactory performance in terms of specificity, sensitivity and overall classification accuracy.

  18. 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.

  19. 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.

  20. Convolutive blind source separation of surface EMG measurements of the respiratory muscles.

    Science.gov (United States)

    Petersen, Eike; Buchner, Herbert; Eger, Marcus; Rostalski, Philipp

    2017-04-01

    Electromyography (EMG) has long been used for the assessment of muscle function and activity and has recently been applied to the control of medical ventilation. For this application, the EMG signal is usually recorded invasively by means of electrodes on a nasogastric tube which is placed inside the esophagus in order to minimize noise and crosstalk from other muscles. Replacing these invasive measurements with an EMG signal obtained non-invasively on the body surface is difficult and requires techniques for signal separation in order to reconstruct the contributions of the individual respiratory muscles. In the case of muscles with small cross-sectional areas, or with muscles at large distances from the recording site, solutions to this problem have been proposed previously. The respiratory muscles, however, are large and distributed widely over the upper body volume. In this article, we describe an algorithm for convolutive blind source separation (BSS) that performs well even for large, distributed muscles such as the respiratory muscles, while using only a small number of electrodes. The algorithm is derived as a special case of the TRINICON general framework for BSS. To provide evidence that it shows potential for separating inspiratory, expiratory, and cardiac activities in practical applications, a joint numerical simulation of EMG and ECG activities was performed, and separation success was evaluated in a variety of noise settings. The results are promising.

  1. Comparison of EMG signals recorded by surface electrodes on endotracheal tube and thyroid cartilage during monitored thyroidectomy

    Directory of Open Access Journals (Sweden)

    Feng-Yu Chiang

    2017-10-01

    Full Text Available A variety of electromyography (EMG recording methods were reported during intraoperative neural monitoring (IONM of recurrent laryngeal nerve (RLN in thyroid surgery. This study compared two surface recording methods that were obtained by electrodes on endotracheal tube (ET and thyroid cartilage (TC. This study analyzed 205 RLNs at risk in 110 patients undergoing monitored thyroidectomy. Each patient was intubated with an EMG ET during general anesthesia. A pair of single needle electrode was inserted obliquely into the TC lamina on each side. Standard IONM procedure was routinely followed, and EMG signals recorded by the ET and TC electrodes at each step were compared. In all nerves, evoked laryngeal EMG signals were reliably recorded by the ET and TC electrodes, and showed the same typical waveform and latency. The EMG signals recorded by the TC electrodes showed significantly higher amplitudes and stability compared to those by the ET electrodes. Both recording methods accurately detected 7 partial loss of signal (LOS and 2 complete LOS events caused by traction stress, but only the ET electrodes falsely detected 3 LOS events caused by ET displacement during surgical manipulation. Two patients with true complete LOS experienced temporary RLN palsy postoperatively. Neither permanent RLN palsy, nor complications from ET or TC electrodes were encountered in this study. Both electrodes are effective and reliable for recording laryngeal EMG signals during monitored thyroidectomy. Compared to ET electrodes, TC electrodes obtain higher and more stable EMG signals as well as fewer false EMG results during IONM.

  2. 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.

  3. 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.

  4. Does Heel Height Cause Imbalance during Sit-to-Stand Task: Surface EMG Perspective

    Directory of Open Access Journals (Sweden)

    Ganesh R. Naik

    2017-08-01

    Full Text Available The purpose of this study was to determine whether electromyography (EMG muscle activities around the knee differ during sit-to-stand (STS and returning task for females wearing shoes with different heel heights. Sixteen healthy young women (age = 25.2 ± 3.9 years, body mass index = 20.8 ± 2.7 kg/m2 participated in this study. Electromyography signals were recorded from the two muscles, vastus medialis (VM and vastus lateralis (VL that involve in the extension of knee. The participants wore shoes with five different heights, including 4, 6, 8, 10, and 12 cm. Surface electromyography (sEMG data were acquired during STS and stand-to-sit-returning (STSR tasks. The data was filtered using a fourth order Butterworth (band pass filter of 20–450 Hz frequency range. For each heel height, we extracted median frequency (MDF and root mean square (RMS features to measure sEMG activities between VM and VL muscles. The experimental results (based on MDF and RMS-values indicated that there is imbalance between vasti muscles for more elevated heels. The results are also quantified with statistical measures. The study findings suggest that there would be an increased likelihood of knee imbalance and fatigue with regular usage of high heel shoes (HHS in women.

  5. Surface EMG of the masticatory muscles (part 2): fatigue testing, mastication analysis and influence of different factors.

    Science.gov (United States)

    Hugger, S; Schindler, H J; Kordass, B; Hugger, A

    2013-01-01

    The second part of this review of the literature on the clinical significance of surface electromyography (EMG) of the masticatory muscles systematically examines the results of clinical studies in patients with temporomandibular disorders (TMD), preferably randomized controlled trials, investigating relevant aspects of EMG activity during prolonged chewing activity (fatigue effects), during the mastication process, and under the influence of different factors. Studies on the influence of factors such as gender, age, tooth status, orofacial morphology and (acute) pain, the significance of different occlusal relationships during static and dynamic occlusion, and the impact of changes in static occlusion on EMG activity of the masticatory muscles were included in the review.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. EMG Pattern Classification to Control a Hand Orthosis for Functional Grasp Assistance after Stroke

    OpenAIRE

    Meeker, Cassie; Park, Sangwoo; Bishop, Lauri; Stein, Joel; Ciocarlie, Matei

    2018-01-01

    Wearable orthoses can function both as assistive devices, which allow the user to live independently, and as rehabilitation devices, which allow the user to regain use of an impaired limb. To be fully wearable, such devices must have intuitive controls, and to improve quality of life, the device should enable the user to perform Activities of Daily Living. In this context, we explore the feasibility of using electromyography (EMG) signals to control a wearable exotendon device to enable pick ...

  8. Amplitude and frequency changes in surface EMG of biceps femoris during five days Bruce Protocol treadmill test.

    Science.gov (United States)

    Jamaluddin, Fauzani N; Ahmad, Siti A; Noor, Samsul Bahari Mohd; Hassan, Wan Zuha Wan; Yaakob, Azhar; Adam, Yunus; Ali, Sawal H M

    2015-01-01

    Electromyography (EMG) is one of the indirect tools in indexing fatigue. Fatigue can be detected when there are changes on amplitude and frequency. However, various outcomes from literature make researchers conclude that EMG is not a reliable tool to measure fatigue. This paper investigates EMG behavior of biceps femoris in median frequency and mean absolute value during five days of Bruce Protocol treadmill test. Before that, surface EMG signals are filtered using band pass filter cut-off at 20-500Hz and are de-noised using db45 1-decimated wavelet transform. Five participants achieved more than 85% of their maximal heart rate during the running activity. The authors also consider other markers of fatigue such as performance, muscle soreness and lethargy as indicators to adaptation and maladaptation conditions. Result shows that turning points of median frequency and mean absolute value are very significant in indexing fatigue and indicators to adaptation of resistive training.

  9. A Real-Time Pinch-to-Zoom Motion Detection by Means of a Surface EMG-Based Human-Computer Interface

    Directory of Open Access Journals (Sweden)

    Jongin Kim

    2014-12-01

    Full Text Available In this paper, we propose a system for inferring the pinch-to-zoom gesture using surface EMG (Electromyography signals in real time. Pinch-to-zoom, which is a common gesture in smart devices such as an iPhone or an Android phone, is used to control the size of images or web pages according to the distance between the thumb and index finger. To infer the finger motion, we recorded EMG signals obtained from the first dorsal interosseous muscle, which is highly related to the pinch-to-zoom gesture, and used a support vector machine for classification between four finger motion distances. The powers which are estimated by Welch’s method were used as feature vectors. In order to solve the multiclass classification problem, we applied a one-versus-one strategy, since a support vector machine is basically a binary classifier. As a result, our system yields 93.38% classification accuracy averaged over six subjects. The classification accuracy was estimated using 10-fold cross validation. Through our system, we expect to not only develop practical prosthetic devices but to also construct a novel user experience (UX for smart devices.

  10. A real-time pinch-to-zoom motion detection by means of a surface EMG-based human-computer interface.

    Science.gov (United States)

    Kim, Jongin; Cho, Dongrae; Lee, Kwang Jin; Lee, Boreom

    2014-12-29

    In this paper, we propose a system for inferring the pinch-to-zoom gesture using surface EMG (Electromyography) signals in real time. Pinch-to-zoom, which is a common gesture in smart devices such as an iPhone or an Android phone, is used to control the size of images or web pages according to the distance between the thumb and index finger. To infer the finger motion, we recorded EMG signals obtained from the first dorsal interosseous muscle, which is highly related to the pinch-to-zoom gesture, and used a support vector machine for classification between four finger motion distances. The powers which are estimated by Welch's method were used as feature vectors. In order to solve the multiclass classification problem, we applied a one-versus-one strategy, since a support vector machine is basically a binary classifier. As a result, our system yields 93.38% classification accuracy averaged over six subjects. The classification accuracy was estimated using 10-fold cross validation. Through our system, we expect to not only develop practical prosthetic devices but to also construct a novel user experience (UX) for smart devices.

  11. Surface EMG-based Sketching Recognition Using Two Analysis Windows and Gene Expression Programming

    Science.gov (United States)

    Yang, Zhongliang; Chen, Yumiao

    2016-01-01

    Sketching is one of the most important processes in the conceptual stage of design. Previous studies have relied largely on the analyses of sketching process and outcomes; whereas surface electromyographic (sEMG) signals associated with sketching have received little attention. In this study, we propose a method in which 11 basic one-stroke sketching shapes are identified from the sEMG signals generated by the forearm and upper arm muscles from 4 subjects. Time domain features such as integrated electromyography, root mean square and mean absolute value were extracted with analysis windows of two length conditions for pattern recognition. After reducing data dimensionality using principal component analysis, the shapes were classified using Gene Expression Programming (GEP). The performance of the GEP classifier was compared to the Back Propagation neural network (BPNN) and the Elman neural network (ENN). Feature extraction with the short analysis window (250 ms with a 250 ms increment) improved the recognition rate by around 6.4% averagely compared with the long analysis window (2500 ms with a 2500 ms increment). The average recognition rate for the eleven basic one-stroke sketching patterns achieved by the GEP classifier was 96.26% in the training set and 95.62% in the test set, which was superior to the performance of the BPNN and ENN classifiers. The results show that the GEP classifier is able to perform well with either length of the analysis window. Thus, the proposed GEP model show promise for recognizing sketching based on sEMG signals. PMID:27790083

  12. 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.

  13. Surface EMG to assess arm function in boys with DMD: a pilot study.

    Science.gov (United States)

    Janssen, Mariska M H P; Harlaar, Jaap; de Groot, Imelda J M

    2015-04-01

    Preserving functional abilities of the upper extremities is a major concern in boys with Duchenne Muscular Dystrophy (DMD). To assess disease progression and treatments, good knowledge on arm function in boys with DMD is essential. Therefore, feasibility and validity of the use of surface electromyography (sEMG) to assess arm function in boys with DMD was examined. Five boys with DMD and 6 age-matched controls participated in this study. Single joint movements and ADL activities were examined while recording sEMG of main shoulder and elbow muscles. All boys with DMD and controls were able to perform the non standardized movements of the measurement protocol, however one boy with DMD was not able to perform all the standardized movements. Boys with DMD used significantly more of their maximal muscle capacity for all muscles to conduct movements compared to controls. The measurement protocol was feasible to assess arm function in boys with DMD. This tool was able to discriminate between DMD patients and controls. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. 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

  15. 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

    2018-01-01

    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

  16. 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.

  17. 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.

  18. Modeling dynamic high-DOF finger postures from surface EMG using nonlinear synergies in latent space representation.

    Science.gov (United States)

    Ngeo, Jimson; Tamei, Tomoya; Ikeda, Kazushi; Shibata, Tomohiro

    2015-01-01

    Accurate proportional myoelectric control of the hand is important in replicating dexterous manipulation in robot prostheses and orthoses. However, this is still difficult to achieve due to the complex and high degree-of-freedom (DOF) nature present in the governing musculoskeletal system. To address this problem, we suggest using a low dimensional encoding based on nonlinear synergies to represent both the high-DOF finger joint kinematics and the coordination of muscle activities taken from surface electromyographic (EMG) signals. Generating smooth multi-finger movements using EMG inputs is then done by using a shared Gaussian Process latent variable model that learns a dynamical model between both the kinematic and EMG data represented in a shared latent space. The experimental results show that the method is able to synthesize continuous movements of a full five-finger hand model, with total dimensions as large as 69 (although highly redundant and correlated). Finally, by comparing the estimation performances when the number of EMG latent dimensions are varied, we show that these synergistic features can capture the variance, shared and specific to the observed kinematics.

  19. Muscle-tendon units localization and activation level analysis based on high-density surface EMG array and NMF algorithm

    Science.gov (United States)

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

    2016-12-01

    Objective. Some skeletal muscles can be subdivided into smaller segments called muscle-tendon units (MTUs). The purpose of this paper is to propose a framework to locate the active region of the corresponding MTUs within a single skeletal muscle and to analyze the activation level varieties of different MTUs during a dynamic motion task. Approach. Biceps brachii and gastrocnemius were selected as targeted muscles and three dynamic motion tasks were designed and studied. Eight healthy male subjects participated in the data collection experiments, and 128-channel surface electromyographic (sEMG) signals were collected with a high-density sEMG electrode grid (a grid consists of 8 rows and 16 columns). Then the sEMG envelopes matrix was factorized into a matrix of weighting vectors and a matrix of time-varying coefficients by nonnegative matrix factorization algorithm. Main results. The experimental results demonstrated that the weightings vectors, which represent invariant pattern of muscle activity across all channels, could be used to estimate the location of MTUs and the time-varying coefficients could be used to depict the variation of MTUs activation level during dynamic motion task. Significance. The proposed method provides one way to analyze in-depth the functional state of MTUs during dynamic tasks and thus can be employed on multiple noteworthy sEMG-based applications such as muscle force estimation, muscle fatigue research and the control of myoelectric prostheses. This work was supported by the National Nature Science Foundation of China under Grant 61431017 and 61271138.

  20. Identification of Onset Of Fatigue in Biceps Brachii Muscles Using Surface EMG and Multifractal DMA Alogrithm.

    Science.gov (United States)

    Marri, Kiran; Swaminathan, Ramakrishnan

    2015-01-01

    Prolonged and repeated fatigue conditions can cause muscle damage and adversely impact coordination in dynamic contractions. Hence it is important to determine the onset of muscle fatigue (OMF) in clinical rehabilitation and sports medicine. The aim of this study is to propose a method for analyzing surface electromyography (sEMG) signals and identify OMF using multifractal detrending moving average algorithm (MFDMA). Signals are recorded from biceps brachii muscles of twenty two healthy volunteers while performing standard curl exercise. The first instance of muscle discomfort during curl exercise is considered as experimental OMF. Signals are pre-processed and divided into 1-second epoch for MFDMA analysis. Degree of multifractality (DOM) feature is calculated from multifractal spectrum. Further, the variance of DOM is computed and OMF is calculated from instances of high peaks. The analysis is carried out by dividing the entire duration into six equal zones for time axis normalization. High peaks are observed in zones where subjects reported muscle discomfort. First muscle discomfort occurred in third and forth zones for majority of subjects. The calculated and experimental muscle discomfort zone closely matched in 72% of subjects indicating that multifractal technique may be a good method for detecting onset of fatigue. The experimental data may have an element of subjectivity in identifying muscle discomfort. This work can also be useful to analyze progressive changes in muscle dynamics in neuromuscular condition and co-contraction activity.

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  3. 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...... minutes in the rest periods. EMGs were recorded from the trapezius, infraspinatus, deltoid, and erector spinae muscles. The amplitude of EMG (AEMG) and mean power frequency (MPF) of EMG were calculated. Each TC was divided equally into three parts. Ratings of perceived exertion (RPE) in the neck, shoulder...... during the TCs. AEMG and MPF fluctuated before W1 although the changes of RPE were small. Averaging several TCs was recommended to get stable results from TCs. EMG changes and appropriate TC conditions were discussed in relation to the adaptation in fatiguing contractions....

  4. Support vectors machine classification of surface electromyography for non-invasive naturally controlled hand prostheses.

    Science.gov (United States)

    Moura, Karina O A; Favieiro, Gabriela W; Balbinot, Alexandre

    2016-08-01

    The scientific researches in human rehabilitation techniques have continually evolved to offer again the mobility and freedom lost to disability. Many systems managed by myoelectric signals intended to mimic the movement of the human arm still have results considered partial, which makes it subject of many researches. The use of Natural Interfaces Signal Processing methods makes possible to design systems capable of offering prosthesis in a more natural and intuitive way. This paper presents a study investigating the use of forearm surface electromyography (sEMG) signals for classification of specific movements of hand using 12 sEMG channels and support vector machine (SVM). The system acquired the sEMG signal using a virtual model as a visual stimulus in order to demonstrate to the volunteer the hand movements which must be replicated by them. The Root Mean Square (RMS) value feature is extracted of the signal and it serves as input data for the classification with SVM. The classification stage used three types of kernel functions (linear, polynomial, radial basis) for comparison of the results. The average accuracy reached for the classification of seventeen distinct movements of 83.7% was achieved using the SVM linear classifier, 80.8% was achieved using the SVM polynomial classifier and 85.1% was achieved using the SVM radial basis classifier.

  5. Arm Orthosis/Prosthesis Movement Control Based on Surface EMG Signal Extraction.

    Science.gov (United States)

    Suberbiola, Aaron; Zulueta, Ekaitz; Lopez-Guede, Jose Manuel; Etxeberria-Agiriano, Ismael; Graña, Manuel

    2015-05-01

    This paper shows experimental results on electromyography (EMG)-based system control applied to motorized orthoses. Biceps and triceps EMG signals are captured through two biometrical sensors, which are then filtered and processed by an acquisition system. Finally an output/control signal is produced and sent to the actuators, which will then perform the actual movement, using algorithms based on autoregressive (AR) models and neural networks, among others. The research goal is to predict the desired movement of the lower arm through the analysis of EMG signals, so that the movement can be reproduced by an arm orthosis, powered by two linear actuators. In this experiment, best accuracy has achieved values up to 91%, using a fourth-order AR-model and 100ms block length.

  6. 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.

  7. Reliability of surface EMG as an assessment tool for trunk activity and potential to determine neurorecovery in SCI.

    Science.gov (United States)

    Mitchell, M D; Yarossi, M B; Pierce, D N; Garbarini, E L; Forrest, G F

    2015-05-01

    Reliability and validity study. This study investigates the responsiveness and reliability of the brain motor control assessment (BMCA) as a standardized neurophysiological assessment tool to: (i) characterize trunk neural activity in neurologically-intact controls; (ii) measure and quantify neurorecovery of trunk after spinal cord injury (SCI). Kessler Foundation Research Center, West Orange, NJ. A standardized BMCA protocol was performed to measure surface electromyography (sEMG) recordings for seven bilateral trunk muscles on 15 able-bodied controls during six maneuvers (inhalation, exhalation, neck flexion, jendrassik, unilateral grip). Additionally, sEMG recordings were analyzed for one chronic SCI individual before electrical stimulation (ES), after ES of the lower extremities while supine, and after active stand training using body-weight support with bilateral ES. sEMG recordings were collected on bilateral erector spinae, internal and external obliques, upper and middle trapezius, biceps and triceps. For each maneuver a voluntary response index was calculated: incorporating the magnitude of sEMG signal and a similarity index (SI), which quantifies the distribution of activity across all muscles. Among all maneuvers, the SI presented reproducible assessment of trunk-motor function within (ICC: 0.860-0.997) and among (P⩾0.22) able-bodied individuals. In addition, potential changes were measured in a chronic SCI individual after undergoing two intensive ES protocols. The BMCA provides reproducible characterization of trunk activity in able-bodied individuals, lending credence for its use in neurophysiological assessment of motor control. Additionally, the BMCA as an assessment tool to measure neurorecovery in an individual with chronic SCI after intense ES interventions was demonstrated.

  8. 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

  9. 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.

  10. Multiscale feature based analysis of surface EMG signals under fatigue and non-fatigue conditions.

    Science.gov (United States)

    Navaneethakrishna, M; Ramakrishnan, S

    2014-01-01

    In this work, an attempt has been made to differentiate sEMG signals under muscle fatigue and non-fatigue conditions using multiscale features. Signals are recorded from biceps brachii muscle of 50 normal adults during repetitive dynamic contractions. After prescribed preprocessing, each signal is divided into six segments out of which first and last segments are considered in this analysis. Multiscale RMS (MSRMS) and Multiscale Permutation Entropy (MSPE) are computed for each subject in the time scales ranging from 1 to 50. The median values of the MSRMS and MSPE are calculated for further analysis. The results show an increase in amplitude for sEMG signals under fatigue condition. MSRMS values are found to be significantly higher in fatigue. An approximately constant difference in MSRMS value between fatigue and non-fatigue condition is observed over the entire time scale with a negative slope. Further, the median of MSRMS values for each subject is able to distinguish fatigue and non-fatigue conditions. Similar analysis on MSPE showed significant difference between fatigue and non-fatigue cases and lower values of MSPE is observed in fatigue. It is also observed that the median value of MSRMS and MSPE are able to distinguish these conditions. t-test for MSRMS, MSPE and their median value show high statistical significance. It appears that this method of analysis can be used for clinical evaluation of muscles.

  11. Effects of sampling rate on automated fatigue recognition in surface EMG signals

    Directory of Open Access Journals (Sweden)

    Kahl Lorenz

    2015-09-01

    Full Text Available This study investigated the effects different sampling rates may produce on the quality of muscle fatigue detection algorithms. sEMG signals were obtained from isometric contractions of the arm. Subsampled signals resulting in technically relevant sampling rates were computationally deduced from the original recordings. The spectral based fatigue recognition methods mean and median frequency as well as spectral moment ratio were included in this investigation, as well as the sample and the fuzzy approximate entropy. The resulting fatigue indices were evaluated with respect to noise and separability of different load levels. We concluded that the spectral moment ratio provides the best results in fatigue detection over a wide range of sampling rates.

  12. 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

  13. 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.

  14. 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 post...... during the TCs. AEMG and MPF fluctuated before W1 although the changes of RPE were small. Averaging several TCs was recommended to get stable results from TCs. EMG changes and appropriate TC conditions were discussed in relation to the adaptation in fatiguing contractions....

  15. 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...

  16. 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.

  17. EMG feature assessment for myoelectric pattern recognition and channel selection: a study with incomplete spinal cord injury.

    Science.gov (United States)

    Liu, Jie; Li, Xiaoyan; Li, Guanglin; Zhou, Ping

    2014-07-01

    Myoelectric pattern recognition with a large number of electromyogram (EMG) channels provides an approach to assessing motor control information available from the recorded muscles. In order to develop a practical myoelectric control system, a feature dependent channel reduction method was developed in this study to determine a small number of EMG channels for myoelectric pattern recognition analysis. The method selects appropriate raw EMG features for classification of different movements, using the minimum Redundancy Maximum Relevance (mRMR) and the Markov random field (MRF) methods to rank a large number of EMG features, respectively. A k-nearest neighbor (KNN) classifier was used to evaluate the performance of the selected features in terms of classification accuracy. The method was tested using 57 channels' surface EMG signals recorded from forearm and hand muscles of individuals with incomplete spinal cord injury (SCI). Our results demonstrate that appropriate selection of a small number of raw EMG features from different recording channels resulted in similar high classification accuracies as achieved by using all the EMG channels or features. Compared with the conventional sequential forward selection (SFS) method, the feature dependent method does not require repeated classifier implementation. It can effectively reduce redundant information not only cross different channels, but also cross different features in the same channel. Such hybrid feature-channel selection from a large number of EMG recording channels can reduce computational cost for implementation of a myoelectric pattern recognition based control system. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

  18. 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

  19. Stationary Wavelet-based Two-directional Two-dimensional Principal Component Analysis for EMG Signal Classification

    Directory of Open Access Journals (Sweden)

    Ji Yi

    2017-06-01

    Full Text Available Discrete wavelet transform (WT followed by principal component analysis (PCA has been a powerful approach for the analysis of biomedical signals. Wavelet coefficients at various scales and channels were usually transformed into a one-dimensional array, causing issues such as the curse of dimensionality dilemma and small sample size problem. In addition, lack of time-shift invariance of WT coefficients can be modeled as noise and degrades the classifier performance. In this study, we present a stationary wavelet-based two-directional two-dimensional principal component analysis (SW2D2PCA method for the efficient and effective extraction of essential feature information from signals. Time-invariant multi-scale matrices are constructed in the first step. The two-directional two-dimensional principal component analysis then operates on the multi-scale matrices to reduce the dimension, rather than vectors in conventional PCA. Results are presented from an experiment to classify eight hand motions using 4-channel electromyographic (EMG signals recorded in healthy subjects and amputees, which illustrates the efficiency and effectiveness of the proposed method for biomedical signal analysis.

  20. 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.

  1. 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

  2. Abdominal muscle EMG-activity during bridge exercises on stable and unstable surfaces.

    Science.gov (United States)

    Czaprowski, Dariusz; Afeltowicz, Anna; Gębicka, Anna; Pawłowska, Paulina; Kędra, Agnieszka; Barrios, Carlos; Hadała, Michał

    2014-08-01

    To assess abdominal muscles (AM) activity during prone, side, and supine bridge on stable and unstable surfaces (BOSU, Swiss Ball). Prospective comparison study. Research laboratory. Thirty-three healthy volunteers from a university population. Surface electromyography of the rectus abdominis (RA), the external oblique (EO) and the internal oblique with the transversus abdominis (IO-TA). The AM exhibited the highest activity during prone bridge on a Swiss Ball (RA, EO, IO-TA 44.7 ± 19.2, 54.7 ± 22.9, 36.8 ± 18.6 in % of MVC, respectively). The lowest activity was observed during supine bridge on a stable surface and a BOSU (under 5.0). The lowest ratio analyzed on the basis of the relation of EO and IO-TA activity to RA was obtained during prone bridge on the Swiss Ball (1.4 ± 0.7 for EO, 0.9 ± 0.5 for IO-TA). The highest ratio was obtained during prone bridge on stable surface and supine bridges. The highest level of activity in the abdominal muscles is achieved during prone bridge on a Swiss Ball. However, this exercise provided the lowest activity of the EO and IO-TA in relation to RA. It is essential to conduct further studies verifying the usefulness of using Swiss Ball during core stability training. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Computed myography: three-dimensional reconstruction of motor functions from surface EMG data

    International Nuclear Information System (INIS)

    Doel, Kees van den; Ascher, Uri M; Pai, Dinesh K

    2008-01-01

    We describe a methodology called computed myography to qualitatively and quantitatively determine the activation level of individual muscles by voltage measurements from an array of voltage sensors on the skin surface. A finite element model for electrostatics simulation is constructed from morphometric data. For the inverse problem, we utilize a generalized Tikhonov regularization. This imposes smoothness on the reconstructed sources inside the muscles and suppresses sources outside the muscles using a penalty term. Results from experiments with simulated and human data are presented for activation reconstructions of three muscles in the upper arm (biceps brachii, bracialis and triceps). This approach potentially offers a new clinical tool to sensitively assess muscle function in patients suffering from neurological disorders (e.g., spinal cord injury), and could more accurately guide advances in the evaluation of specific rehabilitation training regimens

  4. Computed myography: three-dimensional reconstruction of motor functions from surface EMG data

    Science.gov (United States)

    van den Doel, Kees; Ascher, Uri M.; Pai, Dinesh K.

    2008-12-01

    We describe a methodology called computed myography to qualitatively and quantitatively determine the activation level of individual muscles by voltage measurements from an array of voltage sensors on the skin surface. A finite element model for electrostatics simulation is constructed from morphometric data. For the inverse problem, we utilize a generalized Tikhonov regularization. This imposes smoothness on the reconstructed sources inside the muscles and suppresses sources outside the muscles using a penalty term. Results from experiments with simulated and human data are presented for activation reconstructions of three muscles in the upper arm (biceps brachii, bracialis and triceps). This approach potentially offers a new clinical tool to sensitively assess muscle function in patients suffering from neurological disorders (e.g., spinal cord injury), and could more accurately guide advances in the evaluation of specific rehabilitation training regimens.

  5. Surface-EMG analysis for the quantification of thigh muscle dynamic co-contractions during normal gait.

    Science.gov (United States)

    Strazza, Annachiara; Mengarelli, Alessandro; Fioretti, Sandro; Burattini, Laura; Agostini, Valentina; Knaflitz, Marco; Di Nardo, Francesco

    2017-01-01

    The research purpose was to quantify the co-contraction patterns of quadriceps femoris (QF) vs. hamstring muscles during free walking, in terms of onset-offset muscular activation, excitation intensity, and occurrence frequency. Statistical gait analysis was performed on surface-EMG signals from vastus lateralis (VL), rectus femoris (RF), and medial hamstrings (MH), in 16315 strides walked by 30 healthy young adults. Results showed full superimpositions of MH with both VL and RF activity from terminal swing, 80 to 100% of gait cycle (GC), to the successive loading response (≈0-15% of GC), in around 90% of the considered strides. A further superimposition was detected during the push-off phase both between VL and MH activation intervals (38.6±12.8% to 44.1±9.6% of GC) in 21.9±13.6% of strides, and between RF and MH activation intervals (45.9±5.3% to 50.7±9.7 of GC) in 32.7±15.1% of strides. These findings led to identify three different co-contractions among QF and hamstring muscles during able-bodied walking: in early stance (in ≈90% of strides), in push-off (in 25-30% of strides) and in terminal swing (in ≈90% of strides). The co-contraction in terminal swing is the one with the highest levels of muscle excitation intensity. To our knowledge, this analysis represents the first attempt for quantification of QF/hamstring muscles co-contraction in young healthy subjects during normal gait, able to include the physiological variability of the phenomenon. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. A comparison of surface and fine wire EMG recordings of gluteus medius during selected maximum isometric voluntary contractions of the hip.

    Science.gov (United States)

    Semciw, Adam I; Neate, Rachel; Pizzari, Tania

    2014-12-01

    Electromyographic (EMG) studies into gluteus medius (GMed) typically involve surface EMG electrodes. Previous comparisons of surface and fine wire electrode recordings in other muscles during high load isometric tasks suggest that recordings between electrodes are comparable when the muscle is contracting at a high intensity, however, surface electrodes record additional activity when the muscle is contracting at a low intensity. The purpose of this study was to compare surface and fine wire recordings of GMed at high and low intensities of muscle contractions, under high load conditions (maximum voluntary isometric contractions, MVICs). Mann-Whitney U tests compared median electrode recordings during three MVIC hip actions; abduction, internal rotation and external rotation, in nine healthy adults. There were no significant differences between electrode recordings in positions that evoked a high intensity contraction (internal rotation and abduction, fine wire activity >77% MVIC; effect size, ES0.277). During external rotation, the intensity of muscle activity was low (4.2% MVIC), and surface electrodes recorded additional myoelectric activity (ES=0.67, p=0.002). At low levels of muscle activity during high load isometric tasks, the use of surface electrodes may result in additional myoelectric recordings of GMed, potentially reflective of cross-talk from surrounding muscles. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

  7. 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%.

  8. Activity of the equine rectus abdominis and oblique external abdominal muscles measured by surface EMG during walk and trot on the treadmill.

    Science.gov (United States)

    Zsoldos, R R; Kotschwar, A; Kotschwar, A B; Rodriguez, C P; Peham, C; Licka, T

    2010-11-01

    The rectus abdominis (RA) and oblique external abdominal (OEA) muscles are both part of the construction of the equine trunk and thought to be essential for the function of the spine during locomotion. Although RA activity at trot has previously been investigated, the relationship between OEA and RA at walk and trot has not yet been described. To document abdominal muscle activities during walk and trot, and test the hypothesis that muscle activity at walk would be smaller than at trot. Six horses (8-20 years old, 450-700 kg) were used for surface electromyography (EMG) measurements, with EMG electrodes placed caudal to the sternum (RA) and at the level of the 16th rib (OEA). On all hooves, the withers and the sacrum reflective markers were placed to determine motion cycles. Normal distribution of data was tested using a Kolmogorov-Smirnov test and Student's t test was used to compare left-right and walk-trot differences (P activity ranged from 8-44 mV (RA) and 7-54 mV (OEA). At trot, EMG activity ranged from 18-150 mV (RA) and 27-239 mV (OEA). There were statistically significant differences between maximum activities of left and right OEA and RA muscles at walk in all horses, and in 4/6 horses at trot. Muscle activities of OEA and RA are smaller at walk than at trot. At walk, the OEA/RA ratio is lower than at trot. There are more significant correlations between muscle activities of both RA and OEA and limb movements at walk than at the trot. © 2010 EVJ Ltd.

  9. 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.

  10. Transvaginal electrical stimulation with surface-EMG biofeedback in managing stress urinary incontinence in women of premenopausal age: a double-blind, placebo-controlled, randomized clinical trial.

    Science.gov (United States)

    Terlikowski, Robert; Dobrzycka, Bozena; Kinalski, Maciej; Kuryliszyn-Moskal, Anna; Terlikowski, Slawomir J

    2013-10-01

    The aim of this study was to evaluate the results of conservative treatment of urodynamic stress urinary incontinence (SUI) using transvaginal electrical stimulation with surface-electromyography-assisted biofeedback (TVES + sEMG) in women of premenopausal age. One hundred and two patients with SUI were divided into two groups: active (n = 68) and placebo (n = 34) TVES + sEMG. The treatment lasted for 8 weeks and consisted of two sessions per day. Women were evaluated before and after the intervention by pad test, voiding diary, urodynamic test, and the Incontinence Quality of Life Questionnaire (I-QOL). Mean urinary leakage on a standard pad test at the end of 8th week was significantly lower in the active than the placebo group (19.5 ± 13.6 vs. 39.8 ± 28.5). Mean urinary leakage on a 24-h pad test was significantly reduced in the active group at the end of 8th and 16th weeks compared with the placebo group (8.2 ± 14.8 vs. 14.6 ± 18.9 and 6.1 ± 11.4 vs. 18.2 ± 20.8, respectively). There was also a significant improvement in muscle strength as measured by the Oxford scale in the active vs the placebo group after 8 and 16 weeks (4.2 vs 2.6 and 4.1 vs 2.7, respectively). No significant difference was found between groups in urodynamic data before and after treatment. At the end of 8th week, the mean I-QOL score in the active vs the placebo group was 78.2 ± 17.9 vs 55.9 ± 14.2, respectively, and at the end of 16th week 80.8 ± 24.1 vs. 50.6 ± 14.9, respectively. Our study showed that TVES + sEMG is a trustworthy method of treatment in premenopausal women with SUI; however, its reliability needs to be established.

  11. 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

  12. 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.

  13. Effect of Selective Muscle Training Using Visual EMG Biofeedback on Infraspinatus and Posterior Deltoid

    OpenAIRE

    Lim, One-bin; Kim, Jeong-ah; Song, Si-jeong; Cynn, Heon-seock; Yi, Chung-hwi

    2014-01-01

    We investigated the effects of visual electromyography (EMG) biofeedback during side-lying shoulder external rotation exercise on the EMG amplitude for the posterior deltoid, infraspinatus, and infraspinatus/posterior deltoid EMG activity ratio. Thirty-one asymptomatic subjects were included. Subjects performed side-lying shoulder external rotation exercise with and without visual EMG biofeedback. Surface EMG was used to collect data from the posterior deltoid and infraspinatus muscles. The v...

  14. 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.

  15. A Spiking Neural Network in sEMG Feature Extraction.

    Science.gov (United States)

    Lobov, Sergey; Mironov, Vasiliy; Kastalskiy, Innokentiy; Kazantsev, Victor

    2015-11-03

    We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control.

  16. 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.

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

    Indian Academy of Sciences (India)

    Prakash

    Surf's Up – Protein Classification by Surface Comparisons. 97. J. Biosci. 32(1), January 2007. 1. Introduction. With an increasing number of experimentally uncharacterized protein sequences and structures produced by genome sequencing or structural genomic initiatives, we often encounter large protein families with only ...

  18. EMG evaluation of hip adduction exercises for soccer players

    DEFF Research Database (Denmark)

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

    2014-01-01

    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...... for the adductor longus during eight hip adduction strengthening exercises and peak EMG was normalised (nEMG) using an isometric maximal voluntary contraction (MVC) as reference. Furthermore, muscle activation of the gluteus medius, rectus abdominis and the external abdominal obliques was analysed during...... the exercises. RESULTS: There were large differences in peak nEMG of the adductor longus between the exercises, with values ranging from 14% to 108% nEMG (pEMG results for the gluteals...

  19. 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

  20. EMG-based facial gesture recognition through versatile elliptic basis function neural network.

    Science.gov (United States)

    Hamedi, Mahyar; Salleh, Sh-Hussain; Astaraki, Mehdi; Noor, Alias Mohd

    2013-07-17

    Recently, the recognition of different facial gestures using facial neuromuscular activities has been proposed for human machine interfacing applications. Facial electromyograms (EMGs) analysis is a complicated field in biomedical signal processing where accuracy and low computational cost are significant concerns. In this paper, a very fast versatile elliptic basis function neural network (VEBFNN) was proposed to classify different facial gestures. The effectiveness of different facial EMG time-domain features was also explored to introduce the most discriminating. In this study, EMGs of ten facial gestures were recorded from ten subjects using three pairs of surface electrodes in a bi-polar configuration. The signals were filtered and segmented into distinct portions prior to feature extraction. Ten different time-domain features, namely, Integrated EMG, Mean Absolute Value, Mean Absolute Value Slope, Maximum Peak Value, Root Mean Square, Simple Square Integral, Variance, Mean Value, Wave Length, and Sign Slope Changes were extracted from the EMGs. The statistical relationships between these features were investigated by Mutual Information measure. Then, the feature combinations including two to ten single features were formed based on the feature rankings appointed by Minimum-Redundancy-Maximum-Relevance (MRMR) and Recognition Accuracy (RA) criteria. In the last step, VEBFNN was employed to classify the facial gestures. The effectiveness of single features as well as the feature sets on the system performance was examined by considering the two major metrics, recognition accuracy and training time. Finally, the proposed classifier was assessed and compared with conventional methods support vector machines and multilayer perceptron neural network. The average classification results showed that the best performance for recognizing facial gestures among all single/multi-features was achieved by Maximum Peak Value with 87.1% accuracy. Moreover, the results proved a

  1. CLASSIFICATION OF THE MGR SURFACE ENVIRONMENTAL MONITORING SYSTEM

    International Nuclear Information System (INIS)

    J.A. Ziegler

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) surface environmental monitoring system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333PY ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  2. 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%.

  3. Averaged EMG profiles in jogging and running at different speeds

    NARCIS (Netherlands)

    Gazendam, Marnix G. J.; Hof, At L.

    EMGs were collected from 14 muscles with surface electrodes in 10 subjects walking 1.25-2.25 m s(-1) and running 1.25-4.5 m s(-1). The EMGs were rectified, interpolated in 100% of the stride, and averaged over all subjects to give an average profile. In running, these profiles could be decomposed

  4. 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.

  5. Surface EMG and muscle fatigue: multi-channel approaches to the study of myoelectric manifestations of muscle fatigue.

    Science.gov (United States)

    Marco, Gazzoni; Alberto, Botter; Taian, Vieira

    2017-05-01

    In a broad view, fatigue is used to indicate a degree of weariness. On a muscular level, fatigue posits the reduced capacity of muscle fibres to produce force, even in the presence of motor neuron excitation via either spinal mechanisms or electric pulses applied externally. Prior to decreased force, when sustaining physically demanding tasks, alterations in the muscle electrical properties take place. These alterations, termed myoelectric manifestation of fatigue, can be assessed non-invasively with a pair of surface electrodes positioned appropriately on the target muscle; traditional approach. A relatively more recent approach consists of the use of multiple electrodes. This multi-channel approach provides access to a set of physiologically relevant variables on the global muscle level or on the level of single motor units, opening new fronts for the study of muscle fatigue; it allows for: (i) a more precise quantification of the propagation velocity, a physiological variable of marked interest to the study of fatigue; (ii) the assessment of regional, myoelectric manifestations of fatigue; (iii) the analysis of single motor units, with the possibility to obtain information about motor unit control and fibre membrane changes. This review provides a methodological account on the multi-channel approach for the study of myoelectric manifestation of fatigue and on the experimental conditions to which it applies, as well as examples of their current applications.

  6. 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.

  7. Correlated EMG Oscillations between Antagonists during Cocontraction in Men.

    Science.gov (United States)

    Yoshitake, Yasuhide; Kanehisa, Hiroaki; Shinohara, Minoru

    2017-03-01

    The purpose of this study was to determine the modulation of common low-frequency oscillations in pools of motor units across antagonistic muscles because of the difference in the activation level of pools of spinal motor neurons and the presence of neuromuscular fatigue during intended cocontraction. Ten healthy young men (21.8 ± 1.5 yr) performed intended steady cocontractions of elbow flexors and extensors at maximal and a submaximal (10% of maximal EMG) effort. The submaximal cocontraction was repeated after sustained maximal contraction of elbow flexors. Surface EMG was recorded from the biceps brachii and triceps brachii muscles. Correlated EMG oscillations between the antagonistic muscles were quantified by the cross-correlation function (CCF) using rectified EMG for the EMG for the 3- to 15-Hz bands. The positive CCF peak in rectified EMG EMG, a negative CCF peak (i.e., out-of-phase oscillations) during submaximal cocontraction was smaller compared with maximal cocontraction but increased after the sustained contraction. Across subjects, the degree of reduction in maximal EMG amplitude after the sustained contraction was correlated with the amount of change in the CCF peak in EMG oscillations between antagonistic muscles occur during intended cocontraction, and 2) the magnitude of these correlated oscillations increases with the activation level of pools of spinal motor neurons and neuromuscular fatigue.

  8. Classification of simple surface points and a global theorem for simple closed surfaces in three-dimensional digital spaces

    Science.gov (United States)

    Chen, Li; Zhang, Jianping

    1993-12-01

    In this paper, we present two theorems: classification theorem and corner point theorem for closed digital surfaces. The classification theorem deals with the categorization of simple surface points and states that there are exactly six different types of simple surface points. On the basis of the classification theorem and Euler formula on planar graph, we have proved the corner point theorem: Any simple closed surface has at least eight corner points, where a corner point of a closed surface is a point in the surface which has exactly three adjacent points in the closed surface. Another result reported in this paper is that any simple closed surface has at least fourteen points.

  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. 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

  11. SMEX02 Land Surface Information: Land Use Classification

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of land use classification data collected for the Iowa Soil Moisture Experiment 2002 (SMEX02) study region. The land use classification image...

  12. 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...... the motor cortex. The rate of flexion during shortening contractions reduced muscle lengthening caused by muscle relaxation. Surface EMG was recorded from biceps brachii and brachioradialis, and the low-level EMG during silent periods produced by TMS was measured. RESULTS: Low-level EMG activity was reduced...

  13. 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.

  14. 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

  15. 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 s...

  16. 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).

  17. EMG analysis of back muscles during various types of sitting position

    OpenAIRE

    Nitka, Radek

    2009-01-01

    Title: EMG Analysis of Back Muscles during various Types of Sitting Position Purposes: The purpose of the thesis is the assessment of EMG activity of back muscles while sitting on a chair without any back support, and while sitting on a gymball. Methods: Surface electromyography - recording EMG activity of back muscles (20 minutes sitting on a chair and 20 minutes sitting on a gymball). Results: The mean muscle activity of all probands while sitting on a chair is higher than while sitting on ...

  18. The influence of foot position on lower leg muscle activity during a heel raise exercise measured with fine-wire and surface EMG.

    Science.gov (United States)

    Akuzawa, Hiroshi; Imai, Atsushi; Iizuka, Satoshi; Matsunaga, Naoto; Kaneoka, Koji

    2017-11-01

    Exercises for lower leg muscles are important to improve function. To examine the influence of foot position on lower leg muscle activity during heel raises. Cross-sectional laboratory study. Laboratory. Fourteen healthy men participated in this study. The muscle activity levels of the tibialis posterior (TP), peroneus longus (PL), flexor digitorum longus (FDL) and medial gastrocnemius (MG) were measured. The heel raises consisted of three foot positions: 1) neutral, 2) 30° abduction, and 3) 30° adduction. The EMG data for five repetitions of each foot position were normalized to maximum voluntary contraction. One-way repeated measure ANOVA was employed for statistical analysis. The muscle activity level of TP, PL and FDL was significantly different between the three foot positions during the heel raises. TP and FDL showed the highest activity level in 30° foot adduction while PL demonstrated the highest activity level in 30° foot abduction. Heel raises with 30° foot adduction and abduction positions can change lower leg muscle activity; These findings suggest that altering foot posture during the heel raise exercise may benefit patients with impaired TP, PL or FDL function. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. 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…

  20. The topological classification of Fano surfaces of real three-dimensional cubics

    Energy Technology Data Exchange (ETDEWEB)

    Krasnov, Vyacheslav A [Yaroslavl Demidov State University (Russian Federation)

    2007-10-31

    We consider surfaces whose points are the lines on the real three-dimensional varieties of degree 3. These surfaces are called Fano surfaces. This paper deals with finding the topological types, that is, a topological classification, of real Fano surfaces. Moreover, we prove that the equivariant topological type of the corresponding complex Fano surface with the involution of complex conjugation determines the rigid isotopy class of the corresponding real three-dimensional cubic.

  1. 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...

  2. 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

  3. 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.

  4. Effect of Selective Muscle Training Using Visual Emg Biofeedback on Infraspinatus and Posterior Deltoid

    Directory of Open Access Journals (Sweden)

    Lim One-bin

    2014-12-01

    Full Text Available We investigated the effects of visual electromyography (EMG biofeedback during side-lying shoulder external rotation exercise on the EMG amplitude for the posterior deltoid, infraspinatus, and infraspinatus/posterior deltoid EMG activity ratio. Thirty-one asymptomatic subjects were included. Subjects performed side-lying shoulder external rotation exercise with and without visual EMG biofeedback. Surface EMG was used to collect data from the posterior deltoid and infraspinatus muscles. The visual EMG biofeedback applied the pre-established threshold to prevent excessive posterior deltoid muscle contraction. A paired t-test was used to determine the significance of the measurements between without vs. with visual EMG biofeedback. Posterior deltoid activity significantly decreased while infraspinatus activity and the infraspinatus/posterior activity ratio significantly increased during side-lying shoulder external rotation exercise with visual EMG biofeedback. This suggests that using visual EMG biofeedback during shoulder external rotation exercise is a clinically effective training method for reducing posterior deltoid activity and increasing infraspinatus activity.

  5. Effect of Selective Muscle Training Using Visual EMG Biofeedback on Infraspinatus and Posterior Deltoid

    Science.gov (United States)

    Lim, One-bin; Kim, Jeong-ah; Song, Si-jeong; Cynn, Heon-seock; Yi, Chung-hwi

    2014-01-01

    We investigated the effects of visual electromyography (EMG) biofeedback during side-lying shoulder external rotation exercise on the EMG amplitude for the posterior deltoid, infraspinatus, and infraspinatus/posterior deltoid EMG activity ratio. Thirty-one asymptomatic subjects were included. Subjects performed side-lying shoulder external rotation exercise with and without visual EMG biofeedback. Surface EMG was used to collect data from the posterior deltoid and infraspinatus muscles. The visual EMG biofeedback applied the pre-established threshold to prevent excessive posterior deltoid muscle contraction. A paired t-test was used to determine the significance of the measurements between without vs. with visual EMG biofeedback. Posterior deltoid activity significantly decreased while infraspinatus activity and the infraspinatus/posterior activity ratio significantly increased during side-lying shoulder external rotation exercise with visual EMG biofeedback. This suggests that using visual EMG biofeedback during shoulder external rotation exercise is a clinically effective training method for reducing posterior deltoid activity and increasing infraspinatus activity. PMID:25713668

  6. 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 magnus, adductor longus and gracilis. EMG activation for pectineus was highest in Hips 90. Injury history was a significant factor in the EMG output for the adductor longus (p magnus. For force data, clinical test type was a significant factor (p force. All other factors had no significant effect on the force outputs. Hip adduction strength assessment is best measured at hips 0 (which produced most force) or 45° flexion (which generally gave the highest EMG output). 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.

  7. 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.

  8. 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.

  9. Unsupervised Classification of Mercury's Surface Spectral and Chemical Characteristics

    Science.gov (United States)

    D'Amore, M.; Helbert, J.; Ferrari, S.; Maturilli, A.; Nittler, L. R.; Domingue, D. L.; Vilas, F.; Weider, S. Z.; Starr, R. D.; Crapster-Pregont, E. J.; Ebel, D. S.; Solomon, S. C.

    2014-12-01

    The spectral reflectance of Mercury's surface has been mapped in the 400-1145 nm wavelength range by the Mercury Atmospheric and Surface Composition Spectrometer (MASCS) instrument during orbital observations by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft. Under the hypothesis that surface compositional information can be efficiently derived from such spectral measurements with the use of statistical techniques, we have conducted unsupervised hierarchical clustering analyses to identify and characterize spectral units from MASCS observations. The results display a large-scale dichotomy, with two spectrally distinct units: polar and equatorial, possibly linked to differences in surface environment or composition. The spatial extent of the polar unit in the northern hemisphere correlates approximately with that of the northern volcanic plains. To explore possible relations between composition and spectral behavior, we have compared the spectral units with elemental abundance maps derived from MESSENGER's X-Ray Spectrometer (XRS). It is important to note that the mapping coverage for XRS differs from that of MASCS, particularly for the heavy elements. Nonetheless, by comparing the visible and near-infrared MASCS and XRS datasets and investigating the links between them, we seek further clues to the formation and evolution of Mercury's crust. Moreover, the methodology will permit automation of the production of new maps of the spectral and chemical signature of the surface.

  10. Detection of EMG-based muscle fatigue during cyclic dynamic contraction using a monopolar configuration.

    Science.gov (United States)

    Hotta, Yu; Ito, Kenichi

    2013-01-01

    Measurement of surface EMG signals is usually performed using the bipolar (single differential) configuration. However, even if contraction during exercise is performed until near-complete exhaustion, the change in the surface EMG accompanying the fatigue could be undetectable using the bipolar configuration. In order to overcome this disadvantage, this study proposes the measurement of surface EMG using the monopolar configuration. Experimental results show that the monopolar configuration can detect the change in muscle fatigue with greater sensitivity and better stability, as compared to the bipolar configuration.

  11. Choosing of rational parameters of vibrational cleaning of sieving surfaces during materials classification

    OpenAIRE

    Кадильникова, Татьяна Михайловна; Силина, Наталья Александровна

    2012-01-01

    The article considers the issues of creation of energy-efficient technologies of vibrational cleaning of sieving surfaces during the classification of bulk solids of various sizes. The effects of vibration on the bulk solids were studied, its positive impact on the distribution of material on the work surface and the passage of solids through the sieve fractions of the mesh were determined. The article presents the dynamic scheme of vibrational cleaning of sieving surfaces during the classifi...

  12. Surface electromyogram analysis of the direction of isometric torque generation by the first dorsal interosseous muscle

    Science.gov (United States)

    Zhou, Ping; Suresh, Nina L.; Zev Rymer, William

    2011-06-01

    The objective of this study was to determine whether a novel technique using high density surface electromyogram (EMG) recordings can be used to detect the directional dependence of muscle activity in a multifunctional muscle, the first dorsal interosseous (FDI). We used surface EMG recordings with a two-dimensional electrode array to search for inhomogeneous FDI activation patterns with changing torque direction at the metacarpophalangeal joint, the locus of action of the FDI muscle. The interference EMG distribution across the whole FDI muscle was recorded during isometric contraction at the same force magnitude in five different directions in the index finger abduction-flexion plane. The electrode array EMG activity was characterized by contour plots, interpolating the EMG amplitude between electrode sites. Across all subjects the amplitude of the flexion EMG was consistently lower than that of the abduction EMG at the given force. Pattern recognition methods were used to discriminate the isometric muscle contraction tasks with a linear discriminant analysis classifier, based on the extraction of two different feature sets of the surface EMG signal: the time domain (TD) feature set and a combination of autoregressive coefficients and the root mean square amplitude (AR+RMS) as a feature set. We found that high accuracies were obtained in the classification of different directions of the FDI muscle isometric contraction. With a monopolar electrode configuration, the average overall classification accuracy from nine subjects was 94.1 ± 2.3% for the TD feature set and 95.8 ± 1.5% for the AR+RMS feature set. Spatial filtering of the signal with bipolar electrode configuration improved the average overall classification accuracy to 96.7 ± 2.7% for the TD feature set and 98.1 ± 1.6% for the AR+RMS feature set. The distinct EMG contour plots and the high classification accuracies obtained from this study confirm distinct interference EMG pattern distributions as a

  13. 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

  14. Natural fracture systems on planetary surfaces: Genetic classification and pattern randomness

    Science.gov (United States)

    Rossbacher, Lisa A.

    1987-01-01

    One method for classifying natural fracture systems is by fracture genesis. This approach involves the physics of the formation process, and it has been used most frequently in attempts to predict subsurface fractures and petroleum reservoir productivity. This classification system can also be applied to larger fracture systems on any planetary surface. One problem in applying this classification system to planetary surfaces is that it was developed for ralatively small-scale fractures that would influence porosity, particularly as observed in a core sample. Planetary studies also require consideration of large-scale fractures. Nevertheless, this system offers some valuable perspectives on fracture systems of any size.

  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 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.

  17. Measurement of EMG activity with textile electrodes embedded into clothing.

    Science.gov (United States)

    Finni, T; Hu, M; Kettunen, P; Vilavuo, T; Cheng, S

    2007-11-01

    Novel textile electrodes that can be embedded into sports clothing to measure averaged rectified electromyography (EMG) have been developed for easy use in field tests and in clinical settings. The purpose of this study was to evaluate the validity, reliability and feasibility of this new product to measure averaged rectified EMG. The validity was tested by comparing the signals from bipolar textile electrodes (42 cm(2)) and traditional bipolar surface electrodes (1.32 cm(2)) during bilateral isometric knee extension exercise with two electrode locations (A: both electrodes located in the same place, B: traditional electrodes placed on the individual muscles according to SENIAM, n=10 persons for each). Within-session repeatability (the coefficient of variation CV%, n=10) was calculated from five repetitions of 60% maximum voluntary contraction (MVC). The day-to-day repeatability (n=8) was assessed by measuring three different isometric force levels on five consecutive days. The feasibility of the textile electrodes in field conditions was assessed during a maximal treadmill test (n=28). Bland-Altman plots showed a good agreement within 2SD between the textile and traditional electrodes, demonstrating that the textile electrodes provide similar information on the EMG signal amplitude to the traditional electrodes. The within-session CV ranged from 13% to 21% in both the textile and traditional electrodes. The day-to-day CV was smaller, ranging from 4% to 11% for the textile electrodes. A similar relationship (r(2)=0.5) was found between muscle strength and the EMG of traditional and textile electrodes. The feasibility study showed that the textile electrode technique can potentially make EMG measurements very easy in field conditions. This study indicates that textile electrodes embedded into shorts is a valid and feasible method for assessing the average rectified value of EMG.

  18. EMG processing to interpret a neural tension-limiting mechanism with fatigue.

    Science.gov (United States)

    La Delfa, Nicholas J; Sutherland, Chad A; Potvin, Jim R

    2014-09-01

    Surface electromyography (sEMG) amplitude increases with constant muscle tension during fatiguing sub-maximum efforts. The purpose of this study was to determine if extreme highpass filtering and/or autoregressive whitening would result in a more consistent sEMG-to-moment ratio than a standard bandpass filter (20-500 Hz) during repeated, dynamic maximal efforts of the quadriceps. We collected sEMG and knee extensor moment from 16 participants during the concentric and eccentric phases of repeated, maximal knee extensor efforts. The alternative processing methods provided more consistent vastus medialis and lateralis sEMG-to-moment ratios. A neural tension-limiting mechanism appeared to exist and was magnified during the eccentric phase, particularly with fatigue. There appears to be a difference in how the central nervous system controls concentric and eccentric efforts as the quadriceps fatigues, and this is more apparent with the alternative EMG processing methods we used. Copyright © 2013 Wiley Periodicals, Inc.

  19. 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.

  20. Analysis of the sEMG/force relationship using HD-sEMG technique and data fusion: A simulation study.

    Science.gov (United States)

    Al Harrach, Mariam; Carriou, Vincent; Boudaoud, Sofiane; Laforet, Jeremy; Marin, Frederic

    2017-04-01

    The relationship between the surface Electromyogram (sEMG) signal and the force of an individual muscle is still ambiguous due to the complexity of experimental evaluation. However, understanding this relationship should be useful for the assessment of neuromuscular system in healthy and pathological contexts. In this study, we present a global investigation of the factors governing the shape of this relationship. Accordingly, we conducted a focused sensitivity analysis of the sEMG/force relationship form with respect to neural, functional and physiological parameters variation. For this purpose, we used a fast generation cylindrical model for the simulation of an 8×8 High Density-sEMG (HD-sEMG) grid and a twitch based force model for the muscle force generation. The HD-sEMG signals as well as the corresponding force signals were simulated in isometric non-fatiguing conditions and were based on the Biceps Brachii (BB) muscle properties. A total of 10 isometric constant contractions of 5s were simulated for each configuration of parameters. The Root Mean Squared (RMS) value was computed in order to quantify the sEMG amplitude. Then, an image segmentation method was used for data fusion of the 8×8 RMS maps. In addition, a comparative study between recent modeling propositions and the model proposed in this study is presented. The evaluation was made by computing the Normalized Root Mean Squared Error (NRMSE) of their fitting to the simulated relationship functions. Our results indicated that the relationship between the RMS (mV) and muscle force (N) can be modeled using a 3rd degree polynomial equation. Moreover, it appears that the obtained coefficients are patient-specific and dependent on physiological, anatomical and neural parameters. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Classification

    Science.gov (United States)

    Oza, Nikunj C.

    2011-01-01

    A supervised learning task involves constructing a mapping from input data (normally described by several features) to the appropriate outputs. Within supervised learning, one type of task is a classification learning task, in which each output is one or more classes to which the input belongs. In supervised learning, a set of training examples---examples with known output values---is used by a learning algorithm to generate a model. This model is intended to approximate the mapping between the inputs and outputs. This model can be used to generate predicted outputs for inputs that have not been seen before. For example, we may have data consisting of observations of sunspots. In a classification learning task, our goal may be to learn to classify sunspots into one of several types. Each example may correspond to one candidate sunspot with various measurements or just an image. A learning algorithm would use the supplied examples to generate a model that approximates the mapping between each supplied set of measurements and the type of sunspot. This model can then be used to classify previously unseen sunspots based on the candidate's measurements. This chapter discusses methods to perform machine learning, with examples involving astronomy.

  2. EMG-based pattern recognition approach in post stroke robot-aided rehabilitation: a feasibility study

    Science.gov (United States)

    2013-01-01

    Background Several studies investigating the use of electromyographic (EMG) signals in robot-based stroke neuro-rehabilitation to enhance functional recovery. Here we explored whether a classical EMG-based patterns recognition approach could be employed to predict patients’ intentions while attempting to generate goal-directed movements in the horizontal plane. Methods Nine right-handed healthy subjects and seven right-handed stroke survivors performed reaching movements in the horizontal plane. EMG signals were recorded and used to identify the intended motion direction of the subjects. To this aim, a standard pattern recognition algorithm (i.e., Support Vector Machine, SVM) was used. Different tests were carried out to understand the role of the inter- and intra-subjects’ variability in affecting classifier accuracy. Abnormal muscular spatial patterns generating misclassification were evaluated by means of an assessment index calculated from the results achieved with the PCA, i.e., the so-called Coefficient of Expressiveness (CoE). Results Processing the EMG signals of the healthy subjects, in most of the cases we were able to build a static functional map of the EMG activation patterns for point-to-point reaching movements on the horizontal plane. On the contrary, when processing the EMG signals of the pathological subjects a good classification was not possible. In particular, patients’ aimed movement direction was not predictable with sufficient accuracy either when using the general map extracted from data of normal subjects and when tuning the classifier on the EMG signals recorded from each patient. Conclusions The experimental findings herein reported show that the use of EMG patterns recognition approach might not be practical to decode movement intention in subjects with neurological injury such as stroke. Rather than estimate motion from EMGs, future scenarios should encourage the utilization of these signals to detect and interpret the normal and

  3. Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

    Science.gov (United States)

    Lure, Y. M. Fleming; Grody, Norman C.; Chiou, Y. S. Peter; Yeh, H. Y. Michael

    1993-01-01

    A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular

  4. EMG-force relationship during static contraction: Effects on sensor placement locations on biceps brachii muscle.

    Science.gov (United States)

    Ahamed, Nizam Uddin; Sundaraj, Kenneth; Alqahtani, Mahdi; Altwijri, Omar; Ali, Md Asraf; Islam, Md Anamul

    2014-10-15

    The relationship between surface electromyography (EMG) and force have been the subject of ongoing investigations and remain a subject of controversy. Even under static conditions, the relationships at different sensor placement locations in the biceps brachii (BB) muscle are complex. The aim of this study was to compare the activity and relationship between surface EMG and static force from the BB muscle in terms of three sensor placement locations. Twenty-one right hand dominant male subjects (age 25.3 ± 1.2 years) participated in the study. Surface EMG signals were detected from the subject's right BB muscle. The muscle activation during force was determined as the root mean square (RMS) electromyographic signal normalized to the peak RMS EMG signal of isometric contraction for 10 s. The statistical analysis included linear regression to examine the relationship between EMG amplitude and force of contraction [40-100% of maximal voluntary contraction (MVC)], repeated measures ANOVA to assess differences among the sensor placement locations, and coefficient of variation (CoV) for muscle activity variation. The results demonstrated that when the sensor was placed on the muscle belly, the linear slope coefficient was significantly greater for EMG versus force testing (r^{2} = 0.61, P > 0.05) than when placed on the lower part (r^{2}=0.31, Pr^{2}=0.29, P > 0.05). In addition, the EMG signal activity on the muscle belly had less variability than the upper and lower parts (8.55% vs. 15.12% and 12.86%, respectively). These findings indicate the importance of applying the surface EMG sensor at the appropriate locations that follow muscle fiber orientation of the BB muscle during static contraction. As a result, EMG signals of three different placements may help to understand the difference in the amplitude of the signals due to placement.

  5. Experimentally induced stress validated by EMG activity.

    Directory of Open Access Journals (Sweden)

    Rosan Luijcks

    Full Text Available Experience of stress may lead to increased electromyography (EMG activity in specific muscles compared to a non-stressful situation. The main aim of this study was to develop and validate a stress-EMG paradigm in which a single uncontrollable and unpredictable nociceptive stimulus was presented. EMG activity of the trapezius muscles was the response of interest. In addition to linear time effects, non-linear EMG time courses were also examined. Taking into account the hierarchical structure of the dataset, a multilevel random regression model was applied. The stress paradigm, executed in N = 70 subjects, consisted of a 3-minute baseline measurement, a 3-minute pre-stimulus stress period and a 2-minute post-stimulus phase. Subjects were unaware of the precise moment of stimulus delivery and its intensity level. EMG activity during the entire experiment was conform a priori expectations: the pre-stimulus phase showed a significantly higher mean EMG activity level compared to the other two phases, and an immediate EMG response to the stimulus was demonstrated. In addition, the analyses revealed significant non-linear EMG time courses in all three phases. Linear and quadratic EMG time courses were significantly modified by subjective anticipatory stress level, measured just before the start of the stress task. Linking subjective anticipatory stress to EMG stress reactivity revealed that subjects with a high anticipatory stress level responded with more EMG activity during the pre-stimulus stress phase, whereas subjects with a low stress level showed an inverse effect. Results suggest that the stress paradigm presented here is a valid test to quantify individual differences in stress susceptibility. Further studies with this paradigm are required to demonstrate its potential use in mechanistic clinical studies.

  6. 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.

  7. Subauditory Speech Recognition based on EMG/EPG Signals

    Science.gov (United States)

    Jorgensen, Charles; Lee, Diana Dee; Agabon, Shane; Lau, Sonie (Technical Monitor)

    2003-01-01

    Sub-vocal electromyogram/electro palatogram (EMG/EPG) signal classification is demonstrated as a method for silent speech recognition. Recorded electrode signals from the larynx and sublingual areas below the jaw are noise filtered and transformed into features using complex dual quad tree wavelet transforms. Feature sets for six sub-vocally pronounced words are trained using a trust region scaled conjugate gradient neural network. Real time signals for previously unseen patterns are classified into categories suitable for primitive control of graphic objects. Feature construction, recognition accuracy and an approach for extension of the technique to a variety of real world application areas are presented.

  8. Estimating mood variation from MPF of EMG during walking.

    Science.gov (United States)

    Kinase, Yuta; Venture, Gentiane

    2013-01-01

    The information on the mood included in behavior is classified into nonverbal information, and is included in behavior without necessarily being based on the intention of an agent. Consequently, it is considered that we can estimate the mood from the measurement of the behavior. In this work, we estimate the mood from the surface electromyogram (EMG) information of the muscles of the upper limb during walking. Identification of emotion and mood using EMG information has been done with a variety of methods until now. In addition, it is known that human walking includes information that is specific to the individual and be affected by mood. Therefore, it is thought that the EMG analysis of walking is effective in the identification of human mood. In this work, we made a subject walk in the various mood states and answer psychological tests that measure the mood. We use two types of tasks (music listening and numerical calculation) for evoking different moods. Statistical features of EMG signals are calculated using Fast Fourier Transform (FFT) and Principal Component Analysis (PCA). These statistical features are related with psychological test scores, using regression analysis. In this paper, we have shown the statistical significance of the linear model to predict the variation of mood based on the information on the variation in MPF of EMG data of the muscles of the upper limb during walking with different moods. This shows the validity of such a mapping. However, since the interpretability of the model is still low, it cannot be said that the model is able to accurately represent the mood variation. Creating a model with high accuracy is a key issue in the future.

  9. 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.

  10. Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors.

    Science.gov (United States)

    Xi, Xugang; Tang, Minyan; Miran, Seyed M; Luo, Zhizeng

    2017-05-27

    As an essential subfield of context awareness, activity awareness, especially daily activity monitoring and fall detection, plays a significant role for elderly or frail people who need assistance in their daily activities. This study investigates the feature extraction and pattern recognition of surface electromyography (sEMG), with the purpose of determining the best features and classifiers of sEMG for daily living activities monitoring and fall detection. This is done by a serial of experiments. In the experiments, four channels of sEMG signal from wireless, wearable sensors located on lower limbs are recorded from three subjects while they perform seven activities of daily living (ADL). A simulated trip fall scenario is also considered with a custom-made device attached to the ankle. With this experimental setting, 15 feature extraction methods of sEMG, including time, frequency, time/frequency domain and entropy, are analyzed based on class separability and calculation complexity, and five classification methods, each with 15 features, are estimated with respect to the accuracy rate of recognition and calculation complexity for activity monitoring and fall detection. It is shown that a high accuracy rate of recognition and a minimal calculation time for daily activity monitoring and fall detection can be achieved in the current experimental setting. Specifically, the Wilson Amplitude (WAMP) feature performs the best, and the classifier Gaussian Kernel Support Vector Machine (GK-SVM) with Permutation Entropy (PE) or WAMP results in the highest accuracy for activity monitoring with recognition rates of 97.35% and 96.43%. For fall detection, the classifier Fuzzy Min-Max Neural Network (FMMNN) has the best sensitivity and specificity at the cost of the longest calculation time, while the classifier Gaussian Kernel Fisher Linear Discriminant Analysis (GK-FDA) with the feature WAMP guarantees a high sensitivity (98.70%) and specificity (98.59%) with a short

  11. Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors

    Directory of Open Access Journals (Sweden)

    Xugang Xi

    2017-05-01

    Full Text Available As an essential subfield of context awareness, activity awareness, especially daily activity monitoring and fall detection, plays a significant role for elderly or frail people who need assistance in their daily activities. This study investigates the feature extraction and pattern recognition of surface electromyography (sEMG, with the purpose of determining the best features and classifiers of sEMG for daily living activities monitoring and fall detection. This is done by a serial of experiments. In the experiments, four channels of sEMG signal from wireless, wearable sensors located on lower limbs are recorded from three subjects while they perform seven activities of daily living (ADL. A simulated trip fall scenario is also considered with a custom-made device attached to the ankle. With this experimental setting, 15 feature extraction methods of sEMG, including time, frequency, time/frequency domain and entropy, are analyzed based on class separability and calculation complexity, and five classification methods, each with 15 features, are estimated with respect to the accuracy rate of recognition and calculation complexity for activity monitoring and fall detection. It is shown that a high accuracy rate of recognition and a minimal calculation time for daily activity monitoring and fall detection can be achieved in the current experimental setting. Specifically, the Wilson Amplitude (WAMP feature performs the best, and the classifier Gaussian Kernel Support Vector Machine (GK-SVM with Permutation Entropy (PE or WAMP results in the highest accuracy for activity monitoring with recognition rates of 97.35% and 96.43%. For fall detection, the classifier Fuzzy Min-Max Neural Network (FMMNN has the best sensitivity and specificity at the cost of the longest calculation time, while the classifier Gaussian Kernel Fisher Linear Discriminant Analysis (GK-FDA with the feature WAMP guarantees a high sensitivity (98.70% and specificity (98.59% with a

  12. Engine classification using vibrations measured by Laser Doppler Vibrometer on different surfaces

    Science.gov (United States)

    Wei, J.; Liu, Chi-Him; Zhu, Zhigang; Vongsy, Karmon; Mendoza-Schrock, Olga

    2015-05-01

    In our previous studies, vehicle surfaces' vibrations caused by operating engines measured by Laser Doppler Vibrometer (LDV) have been effectively exploited in order to classify vehicles of different types, e.g., vans, 2-door sedans, 4-door sedans, trucks, and buses, as well as different types of engines, such as Inline-four engines, V-6 engines, 1-axle diesel engines, and 2-axle diesel engines. The results are achieved by employing methods based on an array of machine learning classifiers such as AdaBoost, random forests, neural network, and support vector machines. To achieve effective classification performance, we seek to find a more reliable approach to pick authentic vibrations of vehicle engines from a trustworthy surface. Compared with vibrations directly taken from the uncooperative vehicle surfaces that are rigidly connected to the engines, these vibrations are much weaker in magnitudes. In this work we conducted a systematic study on different types of objects. We tested different types of engines ranging from electric shavers, electric fans, and coffee machines among different surfaces such as a white board, cement wall, and steel case to investigate the characteristics of the LDV signals of these surfaces, in both the time and spectral domains. Preliminary results in engine classification using several machine learning algorithms point to the right direction on the choice of type of object surfaces to be planted for LDV measurements.

  13. 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.

  14. Motor imagery modulation of postural sway is accompanied by changes in the EMG-COP association.

    Science.gov (United States)

    Lemos, Thiago; Rodrigues, Erika C; Vargas, Claudia D

    2014-08-08

    Motor imagery (MI) performed in an upright stance promotes increases in postural sway without changes in usual amplitude measures of calf muscle EMG. However, postural muscle activity can also be determined from the temporal association between EMG and center of pressure (COP) displacements. In this study we investigated whether the MI modulation of postural sway is accompanied by changes in EMG-COP association. Surface EMG from the lateral gastrocnemius (LG) muscle and COP coordinates were collected from 12 subjects while they imagined themselves performing a rising on tiptoes movement via kinesthetic or visual imagery. As a control condition subjects were requested to imagine singing a song. The standard deviation of the forward-backward COP sway and the coefficient of variation of the EMG were calculated and compared across tasks. The degree of association between COP sways and LG activity was evaluated through a cross-correlation function. Kinesthetic imagery promoted a larger COP displacement than both visual and control imagery (pCOP association during kinesthetic imagery compared to control imagery (p=0.02), whereas the EMG-COP association in visual imagery was not different from that observed during kinesthetic or control imagery (p>0.19). In conclusion, kinesthetic imagery resulted in a higher EMG-COP temporal association. Subliminal fringe mechanisms may account for the imagery effects on muscle activity and postural sway during upright stance. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  15. Magnetic hysteresis classification of the lunar surface and the interpretation of permanent remanence in lunar surface samples

    Science.gov (United States)

    Wasilewski, P.

    1972-01-01

    A magnetic hysteresis classification of the lunar surface is presented. It was found that there is a distinct correlation between natural remanence (NRM), saturation magnetization, and the hysteresis ratios for the rock samples. The hysteresis classification is able to explain some aspects of time dependent magnetization in the lunar samples and relates the initial susceptibility to NRM, viscous remanence, and to other aspects of magnetization in lunar samples. It is also considered that since up to 60% of the iron in the lunar soil may be super paramagnetic at 400 K, and only 10% at 100 K, the 50% which becomes ferromagnetic over the cycle has the characteristics of thermoremanence and may provide for an enhancement in measurable field on the dark side during a subsatellite magnetometer circuit.

  16. Femoral anteversion influences vastus medialis and gluteus medius EMG amplitude: composite hip abductor EMG amplitude ratios during isometric combined hip abduction-external rotation.

    Science.gov (United States)

    Nyland, J; Kuzemchek, S; Parks, M; Caborn, D N M

    2004-04-01

    This prospective study evaluated differences in vastus medialis (VM) and gluteus medius (GM) EMG amplitude:composite hip abductor (gluteus maximus, gluteus medius, tensor fascia lata) EMG amplitude ratios among subjects with low or high relative femoral anteversion. Data were collected during the performance of a non-weight bearing, non-sagittal plane maximal volitional effort isometric combined hip abduction-external rotation maneuver. Eighteen nonimpaired athletically active females participated in this surface EMG study. Medial hip rotation (relative femoral anteversion estimate) was measured with a handheld goniometer. Subjects were grouped by medial hip rotation displacement (group 1 42 degrees =52.7+/-7 degrees ) for statistical analysis (Mann Whitney U-tests, p < 0.05). Group 2 had decreased VM (42+/-23% vs. 69+/-30%, U=19, p=0.034) and GM (62+/-25% vs. 96+/-39%, U=19, p=0.034) normalized mean peak EMG amplitude:composite mean peak hip abductor EMG amplitude ratios compared to group 1. Decreased normalized VM (-27%) and GM (-34%) EMG amplitudes among subjects with increased relative femoral anteversion suggest reduced dynamic frontal and transverse plane femoral control from these muscles, possibly contributing to the increased incidence of non-contact knee injury observed among athletic females.

  17. 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.

  18. Object-Based Mangrove Species Classification Using Unmanned Aerial Vehicle Hyperspectral Images and Digital Surface Models

    Directory of Open Access Journals (Sweden)

    Jingjing Cao

    2018-01-01

    Full Text Available Mangroves are one of the most important coastal wetland ecosystems, and the compositions and distributions of mangrove species are essential for conservation and restoration efforts. Many studies have explored this topic using remote sensing images that were obtained by satellite-borne and airborne sensors, which are known to be efficient for monitoring the mangrove ecosystem. With improvements in carrier platforms and sensor technology, unmanned aerial vehicles (UAVs with high-resolution hyperspectral images in both spectral and spatial domains have been used to monitor crops, forests, and other landscapes of interest. This study aims to classify mangrove species on Qi’ao Island using object-based image analysis techniques based on UAV hyperspectral images obtained from a commercial hyperspectral imaging sensor (UHD 185 onboard a UAV platform. First, the image objects were obtained by segmenting the UAV hyperspectral image and the UAV-derived digital surface model (DSM data. Second, spectral features, textural features, and vegetation indices (VIs were extracted from the UAV hyperspectral image, and the UAV-derived DSM data were used to extract height information. Third, the classification and regression tree (CART method was used to selection bands, and the correlation-based feature selection (CFS algorithm was employed for feature reduction. Finally, the objects were classified into different mangrove species and other land covers based on their spectral and spatial characteristic differences. The classification results showed that when considering the three features (spectral features, textural features, and hyperspectral VIs, the overall classification accuracies of the two classifiers used in this paper, i.e., k-nearest neighbor (KNN and support vector machine (SVM, were 76.12% (Kappa = 0.73 and 82.39% (Kappa = 0.801, respectively. After incorporating tree height into the classification features, the accuracy of species classification

  19. Surface feature based classification of plant organs from 3D laserscanned point clouds for plant phenotyping.

    Science.gov (United States)

    Paulus, Stefan; Dupuis, Jan; Mahlein, Anne-Katrin; Kuhlmann, Heiner

    2013-07-27

    Laserscanning recently has become a powerful and common method for plant parameterization and plant growth observation on nearly every scale range. However, 3D measurements with high accuracy, spatial resolution and speed result in a multitude of points that require processing and analysis. The primary objective of this research has been to establish a reliable and fast technique for high throughput phenotyping using differentiation, segmentation and classification of single plants by a fully automated system. In this report, we introduce a technique for automated classification of point clouds of plants and present the applicability for plant parameterization. A surface feature histogram based approach from the field of robotics was adapted to close-up laserscans of plants. Local geometric point features describe class characteristics, which were used to distinguish among different plant organs. This approach has been proven and tested on several plant species. Grapevine stems and leaves were classified with an accuracy of up to 98%. The proposed method was successfully transferred to 3D-laserscans of wheat plants for yield estimation. Wheat ears were separated with an accuracy of 96% from other plant organs. Subsequently, the ear volume was calculated and correlated to the ear weight, the kernel weights and the number of kernels. Furthermore the impact of the data resolution was evaluated considering point to point distances between 0.3 and 4.0 mm with respect to the classification accuracy. We introduced an approach using surface feature histograms for automated plant organ parameterization. Highly reliable classification results of about 96% for the separation of grapevine and wheat organs have been obtained. This approach was found to be independent of the point to point distance and applicable to multiple plant species. Its reliability, flexibility and its high order of automation make this method well suited for the demands of high throughput phenotyping.

  20. 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.

  1. Peak and average rectified EMG measures: which method of data reduction should be used for assessing core training exercises?

    Science.gov (United States)

    Hibbs, A E; Thompson, K G; French, D N; Hodgson, D; Spears, I R

    2011-02-01

    Core strengthening and stability exercises are fundamental for any conditioning training program. Although surface electromyography (sEMG) is used to quantify muscle activity there is a lack of research using this method to investigate the core musculature and core stability. Two types of data reduction are commonly used for sEMG; peak and average rectified EMG methods. Peak EMG has been infrequently reported in the literature with regard to the assessment of core training while even fewer studies have incorporated average rectified EMG data (ARV). The aim of the study was to establish the repeatability of peak and average rectified EMG data during core training exercises and their interrelationship. Ten male highly trained athletes (inter-subject repeatability group; age, 18 ± 1.2 years; height, 176.5 ± 3.2 cm; body mass, 71 ± 4.5 kg) and one female highly trained athlete (intra-subject repeatability group; age; 27 years old; height; 180 cm; weight; 53 kg) performed five maximal voluntary isometric contractions (MVIC) and five core exercises, chosen to represent a range of movement and muscle recruitment patterns. Peak EMG and ARV EMG were calculated for eight core muscles (rectus abdominis, RA; external oblique, EO; internal oblique, IO; multifidis, MF; latissimus dorsi, LD; longissimus, LG; gluteus maximus, GM; rectus femoris, RF) using sEMG. Average coefficient of variation (CV%) for peak EMG across all the exercises and muscles was 45%. This is in comparison to 35% for the ARV method, which was found to be a significant difference (Pexercise. Analysis of the inter-subject and intra-subject CV% values suggest that these exercises and muscles are sufficiently repeatable using sEMG. Five muscles were highly correlated (R>0.70; RA, EO, MF, GM, LG) between peak and ARV EMG suggesting, that for these core muscles, the two methods provide a similar evaluation of muscle activity. However, for other muscles (IO, RF, LD) the relationship was found to range from poor

  2. EMG spectral indices and muscle power fatigue during dynamic contractions.

    Science.gov (United States)

    González-Izal, M; Malanda, A; Navarro-Amézqueta, I; Gorostiaga, E M; Mallor, F; Ibañez, J; Izquierdo, M

    2010-04-01

    The purpose of this study was to examine acute exercise-induced changes on muscle power output and surface electromyography (sEMG) parameters (amplitude and spectral indices of muscle fatigue) during a dynamic fatiguing protocol. Fifteen trained subjects performed five sets consisting of 10 leg presses (10RM), with 2min rest between sets. Surface electromyography was recorded from vastus medialis (VM) and lateralis (VL) and biceps femoris (BF) muscles. A number of EMG-based parameters were compared for estimation accuracy and sensitivity to detect peripheral muscle fatigue. These were: Mean Average Voltage, median spectral frequency, Dimitrov spectral index of muscle fatigue (FI(nsm5)), as well as other parameters obtained from a time-frequency analysis (Choi-Williams distributions) such as mean and variance of the instantaneous frequency and frequency variance. The log FI(nsm5) as a single parameter predictor accounted for 37% of the performance variance of changes in muscle power and the log FI(nsm5) and MFM as a two factor combination predictor accounted for 44%. Peripheral impairments assessed by sEMG spectral index FI(nsm5) may be a relevant factor involved in the loss of power output after dynamic high-loading fatiguing task. 2009 Elsevier Ltd. All rights reserved.

  3. 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

    1998-11-01

    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.

  4. 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......: to show whether medical signal processing of EMG data is feasible for detection of epileptic seizures. Methods: EMG signals during generalised seizures were recorded from 3 patients (with 20 seizures in total). Two possible medical signal processing algorithms were tested. The first algorithm was based...... 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....

  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. 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

  7. 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...

  8. 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.

  9. EMG amplifier with wireless data transmission

    Science.gov (United States)

    Kowalski, Grzegorz; Wildner, Krzysztof

    2017-08-01

    Wireless medical diagnostics is a trend in modern technology used in medicine. This paper presents a concept of realization, architecture of hardware and software implementation of an elecromyography signal (EMG) amplifier with wireless data transmission. This amplifier consists of three components: analogue processing of bioelectric signal module, micro-controller circuit and an application enabling data acquisition via a personal computer. The analogue bioelectric signal processing circuit receives electromyography signals from the skin surface, followed by initial analogue processing and preparation of the signals for further digital processing. The second module is a micro-controller circuit designed to wirelessly transmit the electromyography signals from the analogue signal converter to a personal computer. Its purpose is to eliminate the need for wired connections between the patient and the data logging device. The third block is a computer application designed to display the transmitted electromyography signals, as well as data capture and analysis. Its purpose is to provide a graphical representation of the collected data. The entire device has been thoroughly tested to ensure proper functioning. In use, the device displayed the captured electromyography signal from the arm of the patient. Amplitude- frequency characteristics were set in order to investigate the bandwidth and the overall gain of the device.

  10. 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.

  11. Histamine induced airway response in pre-school children assessed by a non-invasive EMG technique

    NARCIS (Netherlands)

    Maarsingh, E. J. W.; van Eykern, LA; Sprikkelman, AB; van Aalderen, WMC

    The aim of the study was to investigate the association between surface electromyographic (EMG) activity of the diaphragm and intercostal muscles, and clinical symptoms (wheeze, cough, increased respiratory rate and prolonged expiration) during bronchial challenge testing and after administration of

  12. 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)

  13. Real-time Classification of Non-Weight Bearing Lower-Limb Movements Using EMG to Facilitate Phantom Motor Execution: Engineering and Case Study Application on Phantom Limb Pain

    Directory of Open Access Journals (Sweden)

    Eva Lendaro

    2017-09-01

    Full Text Available Phantom motor execution (PME, facilitated by myoelectric pattern recognition (MPR and virtual reality (VR, is positioned to be a viable option to treat phantom limb pain (PLP. A recent clinical trial using PME on upper-limb amputees with chronic intractable PLP yielded promising results. However, further work in the area of signal acquisition is needed if such technology is to be used on subjects with lower-limb amputation. We propose two alternative electrode configurations to conventional, bipolar, targeted recordings for acquiring surface electromyography. We evaluated their performance in a real-time MPR task for non-weight-bearing, lower-limb movements. We found that monopolar recordings using a circumferential electrode of conductive fabric, performed similarly to classical bipolar recordings, but were easier to use in a clinical setting. In addition, we present the first case study of a lower-limb amputee with chronic, intractable PLP treated with PME. The patient’s Pain Rating Index dropped by 22 points (from 32 to 10, 68% after 23 PME sessions. These results represent a methodological advancement and a positive proof-of-concept of PME in lower limbs. Further work remains to be conducted for a high-evidence level clinical validation of PME as a treatment of PLP in lower-limb amputees.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. Surface-enhanced Raman spectroscopy of cell lysates mixed with silver nanoparticles for tumor classification

    Directory of Open Access Journals (Sweden)

    Mohamed Hassoun

    2017-06-01

    Full Text Available The throughput of spontaneous Raman spectroscopy for cell identification applications is limited to the range of one cell per second because of the relatively low sensitivity. Surface-enhanced Raman scattering (SERS is a widespread way to amplify the intensity of Raman signals by several orders of magnitude and, consequently, to improve the sensitivity and throughput. SERS protocols using immuno-functionalized nanoparticles turned out to be challenging for cell identification because they require complex preparation procedures. Here, a new SERS strategy is presented for cell classification using non-functionalized silver nanoparticles and potassium chloride to induce aggregation. To demonstrate the principle, cell lysates were prepared by ultrasonication that disrupts the cell membrane and enables interaction of released cellular biomolecules to nanoparticles. This approach was applied to distinguish four cell lines – Capan-1, HepG2, Sk-Hep1 and MCF-7 – using SERS at 785 nm excitation. Six independent batches were prepared per cell line to check the reproducibility. Principal component analysis was applied for data reduction and assessment of spectral variations that were assigned to proteins, nucleotides and carbohydrates. Four principal components were selected as input for classification models based on support vector machines. Leave-three-batches-out cross validation recognized four cell lines with sensitivities, specificities and accuracies above 96%. We conclude that this reproducible and specific SERS approach offers prospects for cell identification using easily preparable silver nanoparticles.

  19. 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

  20. 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.

  1. A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction

    OpenAIRE

    W?hrle, Hendrik; Tabie, Marc; Kim, Su Kyoung; Kirchner, Frank; Kirchner, Elsa Andrea

    2017-01-01

    A current trend in the development of assistive devices for rehabilitation, for example exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality and usability, for example by predicting the patient?s upcoming movements using electroencephalography (EEG) or electromyography (EMG). However, these modalities have different temporal properties and classification accuracies, which results in specific advantages and disadvantages. To use physiological data an...

  2. NLR, MLP, SVM, and LDA: a comparative analysis on EMG data from people with trans-radial amputation.

    Science.gov (United States)

    Dellacasa Bellingegni, Alberto; Gruppioni, Emanuele; Colazzo, Giorgio; Davalli, Angelo; Sacchetti, Rinaldo; Guglielmelli, Eugenio; Zollo, Loredana

    2017-08-14

    Currently, the typically adopted hand prosthesis surface electromyography (sEMG) control strategies do not provide the users with a natural control feeling and do not exploit all the potential of commercially available multi-fingered hand prostheses. Pattern recognition and machine learning techniques applied to sEMG can be effective for a natural control based on the residual muscles contraction of amputated people corresponding to phantom limb movements. As the researches has reached an advanced grade accuracy, these algorithms have been proved and the embedding is necessary for the realization of prosthetic devices. The aim of this work is to provide engineering tools and indications on how to choose the most suitable classifier, and its specific internal settings for an embedded control of multigrip hand prostheses. By means of an innovative statistical analysis, we compare 4 different classifiers: Nonlinear Logistic Regression, Multi-Layer Perceptron, Support Vector Machine and Linear Discriminant Analysis, which was considered as ground truth. Experimental tests have been performed on sEMG data collected from 30 people with trans-radial amputation, in which the algorithms were evaluated for both performance and computational burden, then the statistical analysis has been based on the Wilcoxon Signed-Rank test and statistical significance was considered at p MLP and SVM shows that, for either classification performance and for the number of classification parameters, SVM attains the highest values followed by MLP, and then by NLR. However, using as unique constraint to evaluate the maximum acceptable complexity of each classifier one of the typically available memory of a high performance microcontroller, the comparison pointed out that for people with trans-radial amputation the algorithm that produces the best compromise is NLR closely followed by MLP. This result was also confirmed by the comparison with LDA with time domain features, which provided not

  3. Static optimization of muscle forces during gait in comparison to EMG-to-force processing approach.

    Science.gov (United States)

    Heintz, Sofia; Gutierrez-Farewik, Elena M

    2007-07-01

    models can arguably be more accurate than from those obtained from surface EMG during gait, though magnitude must still be validated.

  4. 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…

  5. Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

    Science.gov (United States)

    Phinyomark, A.; Hu, H.; Phukpattaranont, P.; Limsakul, C.

    2012-01-01

    The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier.

  6. Implementation of a real-time automatic onset time detection for surface electromyography measurement systems using NI myRIO

    Directory of Open Access Journals (Sweden)

    Lersviriyanantakul Chaiwat

    2016-01-01

    Full Text Available For using surface electromyography (sEMG in various applications, the process consists of three parts: an onset time detection for detecting the first point of movement signals, a feature extraction for extracting the signal attribution, and a feature classification for classifying the sEMG signals. The first and the most significant part that influences the accuracy of other parts is the onset time detection, particularly for automatic systems. In this paper, an automatic and simple algorithm for the real-time onset time detection is presented. There are two main processes in the proposed algorithm; a smoothing process for reducing the noise of the measured sEMG signals and an automatic threshold calculation process for determining the onset time. The results from the algorithm analysis demonstrate the performance of the proposed algorithm to detect the sEMG onset time in various smoothing-threshold equations. Our findings reveal that using a simple square integral (SSI as the smoothing-threshold equation with the given sEMG signals gives the best performance for the onset time detection. Additionally, our proposed algorithm is also implemented on a real hardware platform, namely NI myRIO. Using the real-time simulated sEMG data, the experimental results guarantee that the proposed algorithm can properly detect the onset time in the real-time manner.

  7. 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

  8. 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.

  9. Evaluating the performance and mapping of three fuel classification systems using Forest Inventory and Analysis surface fuel measurements

    Science.gov (United States)

    Robert E. Keane; Jason M. Herynk; Chris Toney; Shawn P. Urbanski; Duncan C. Lutes; Roger D. Ottmar

    2013-01-01

    Fuel Loading Models (FLMs) and Fuel Characteristic Classification System (FCCSs) fuelbeds are used throughout wildland fire science and management to simplify fuel inputs into fire behavior and effects models, but they have yet to be thoroughly evaluated with field data. In this study, we used a large dataset of Forest Inventory and Analysis (FIA) surface fuel...

  10. 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.

  11. fMRI analysis for motor paradigms using EMG-based designs: a validation study

    NARCIS (Netherlands)

    van Rootselaar, Anne-Fleur; Renken, Remco; de Jong, Bauke M.; Hoogduin, Johannes M.; Tijssen, Marina A. J.; Maurits, Natasha M.

    2007-01-01

    The goal of the present validation study is to show that continuous surface EMG recorded simultaneously with 3T fMRI can be used to identify local brain activity related to (1) motor tasks, and to (2) muscle activity independently of a specific motor task, i.e. spontaneous (abnormal) movements. Five

  12. FMRl analysis for motor paradigms using EMG-Based designs : A validation study

    NARCIS (Netherlands)

    Van Rootselaar, Anne-Fleur; Renken, Remco; De Jong, Bauke M.; Hoogduin, Johannes M.; Tijssen, Marina A. J.; Maurits, Natasha M.

    2007-01-01

    The goal of the present validation study is to show that continuous surface EMG recorded simultaneously with 3T fMRI can be used to identify local brain activity related to (1) motor tasks, and to (2) muscle activity independently of a specific motor task, i.e. spontaneous (abnormal) movements. Five

  13. The Reliability of Pattern Classification in Bloodstain Pattern Analysis-PART 2: Bloodstain Patterns on Fabric Surfaces.

    Science.gov (United States)

    Taylor, Michael C; Laber, Terry L; Kish, Paul E; Owens, Glynn; Osborne, Nikola K P

    2016-11-01

    This study was designed to produce the first baseline measure of the reliability of bloodstain pattern classifications on fabric surfaces. Experienced bloodstain pattern analysts classified bloodstain patterns on pairs of trousers that represented three fabric substrates. Patterns also varied in type (impact, cast-off, expiration, satellite stains from dripped blood, and transfer) and extent. In addition, case summaries that accompanied each pattern contained contextual cues that either supported the correct answer (i.e., positive bias), were misleading toward an incorrect answer (i.e., negative bias), or contained no directional information (i.e., neutral). Overall, 23% percent of the resulting classifications were erroneous. The majority (51%) of errors resulted from analysts misclassifying satellite stains from dripped blood. Relative to the neutral information, the positive-bias information increased correct classifications and decreased erroneous classifications, and the negative-bias information decreased correct classifications and increased erroneous classifications. The implications of these findings for BPA are discussed. © 2016 American Academy of Forensic Sciences.

  14. 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.

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

    Science.gov (United States)

    Zhang, Yi; Li, Peiyang; Zhu, Xuyang; Su, Steven W; Guo, Qing; Xu, Peng; Yao, Dezhong

    2017-01-01

    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%±0.88% which

  16. 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

  17. 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.

  18. 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.

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

    Science.gov (United States)

    Liu, Jie; Kang, Sang Hoon; Xu, Dali; Ren, Yupeng; Lee, Song Joo; Zhang, Li-Qun

    2017-01-01

    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. PMID:28890685

  20. 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

  1. The Reliability of Pattern Classification in Bloodstain Pattern Analysis, Part 1: Bloodstain Patterns on Rigid Non-absorbent Surfaces.

    Science.gov (United States)

    Taylor, Michael C; Laber, Terry L; Kish, Paul E; Owens, Glynn; Osborne, Nikola K P

    2016-07-01

    This study was designed to produce the first baseline measure of reliability in bloodstain pattern classification. A panel of experienced bloodstain pattern analysts examined over 400 spatter patterns on three rigid non-absorbent surfaces. The patterns varied in spatter type and extent. A case summary accompanied each pattern that either contained neutral information, information to suggest the correct pattern (i.e., was positively biasing), or information to suggest an incorrect pattern (i.e., was negatively biasing). Across the variables under examination, 13% of classifications were erroneous. Generally speaking, where the pattern was more difficult to recognize (e.g., limited staining extent or a patterned substrate), analysts became more conservative in their judgment, opting to be inconclusive. Incorrect classifications increased as a function of the negatively biasing contextual information. The implications of the findings for practice are discussed. © 2016 American Academy of Forensic Sciences.

  2. A characterization of the effect of limb position on EMG features to guide the development of effective prosthetic control schemes.

    Science.gov (United States)

    Radmand, A; Scheme, E; Englehart, K

    2014-01-01

    Electromyogram (EMG) pattern recognition has long been used for the control of upper limb prostheses. More recently, it has been shown that variability induced during functional use, such as changes in limb position and dynamic contractions, can have a substantial impact on the robustness of EMG pattern recognition. This work further investigates the reasons for pattern recognition performance degradation due to the limb position variation. The main focus is on the impact of limb position variation on features of the EMG, as measured using separability and repeatability metrics. The results show that when the limb is moved to a position different from the one in which the classifier is trained, both the separability and repeatability of the data decrease. It is shown how two previously proposed classification methods, multiple position training and dual-stage classification, resolve the position effect problem to some extent through increasing either separability or repeatability but not both. A hybrid classification method which exhibits a compromise between separability and repeatability is proposed in this work. It is shown that, when tested with the limb in 16 different positions, this method increases classification accuracy from an average of 70% (single position training) to 89% (hybrid approach). This hybrid method significantly (p<;0.05) outperforms multiple position training (an average of 86%) and dual-stage classification (an average of 85%).

  3. 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.

  4. High-density EMG E-textile systems for the control of active prostheses.

    Science.gov (United States)

    Farina, Dario; Lorrain, Thomas; Negro, Francesco; Jiang, Ning

    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 signals for myoelectric control. A sleeve covering the upper and lower arm, which contains 100 electrodes arranged in four grids of 5 × 5 electrodes, was used to record EMG signals in 3 subjects during the execution of 9 tasks of the wrist and hand. The signals were analyzed by extracting wavelet coefficients which were 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.

  5. Design, Development and Testing of a Low-Cost sEMG System and Its Use in Recording Muscle Activity in Human Gait

    Directory of Open Access Journals (Sweden)

    Tamara Grujic Supuk

    2014-05-01

    Full Text Available Surface electromyography (sEMG is an important measurement technique used in biomechanical, rehabilitation and sport environments. In this article the design, development and testing of a low-cost wearable sEMG system are described. The hardware architecture consists of a two-cascade small-sized bioamplifier with a total gain of 2,000 and band-pass of 3 to 500 Hz. The sampling frequency of the system is 1,000 Hz. Since real measured EMG signals are usually corrupted by various types of noises (motion artifacts, white noise and electromagnetic noise present at 50 Hz and higher harmonics, we have tested several denoising techniques, both on artificial and measured EMG signals. Results showed that a wavelet—based technique implementing Daubechies5 wavelet and soft sqtwolog thresholding is the most appropriate for EMG signals denoising. To test the system performance, EMG activities of six dominant muscles of ten healthy subjects during gait were measured (gluteus maximus, biceps femoris, sartorius, rectus femoris, tibialis anterior and medial gastrocnemius. The obtained EMG envelopes presented against the duration of gait cycle were compared favourably with the EMG data available in the literature, suggesting that the proposed system is suitable for a wide range of applications in biomechanics.

  6. Assessment of the paraspinal muscles of subjects presenting an idiopathic scoliosis: an EMG pilot study

    Directory of Open Access Journals (Sweden)

    Larivière Christian

    2005-03-01

    Full Text Available Abstract Background It is known that the back muscles of scoliotic subjects present abnormalities in their fiber type composition. Some researchers have hypothesized that abnormal fiber composition can lead to paraspinal muscle dysfunction such as poor neuromuscular efficiency and muscle fatigue. EMG parameters were used to evaluate these impairments. The purpose of the present study was to examine the clinical potential of different EMG parameters such as amplitude (RMS and median frequency (MF of the power spectrum in order to assess the back muscles of patients presenting idiopathic scoliosis in terms of their neuromuscular efficiency and their muscular fatigue. Methods L5/S1 moments during isometric efforts in extension were measured in six subjects with idiopathic scoliosis and ten healthy controls. The subjects performed three 7 s ramp contractions ranging from 0 to 100% maximum voluntary contraction (MVC and one 30 s sustained contraction at 75% MVC. Surface EMG activity was recorded bilaterally from the paraspinal muscles at L5, L3, L1 and T10. The slope of the EMG RMS/force (neuromuscular efficiency and MF/force (muscle composition relationships were computed during the ramp contractions while the slope of the EMG RMS/time and MF/time relationships (muscle fatigue were computed during the sustained contraction. Comparisons were performed between the two groups and between the left and right sides for the EMG parameters. Results No significant group or side differences between the slopes of the different measures used were found at the level of the apex (around T10 of the major curve of the spine. However, a significant side difference was seen at a lower level (L3, p = 0.01 for the MF/time parameter. Conclusion The EMG parameters used in this study could not discriminate between the back muscles of scoliotic subjects and those of control subject regarding fiber type composition, neuromuscular efficiency and muscle fatigue at the level

  7. Filter banks and the "Intensity Analysis" of EMG

    OpenAIRE

    Borg, Frank

    2010-01-01

    Vinzenz von Tscharner (2000) has presented an interesting mathematical method for analyzing EMG-data called "intensity analysis" (EMG = electromyography). Basically the method is a sort of bandpassing of the signal. The central idea of the method is to describe the "power" (or "intensity") of a non-stationary EMG signal as a function both of time and of frequency. The connection with wavelet theory is that the filter is constructed by rescaling a given mother wavelet using a special array of ...

  8. 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

  9. S-EMG signal compression based on domain transformation and spectral shape dynamic bit allocation.

    Science.gov (United States)

    Trabuco, Marcel Henrique; Costa, Marcus Vinícius Chaffim; Nascimento, Francisco Assis de Oliveira

    2014-02-27

    Surface electromyographic (S-EMG) signal processing has been emerging in the past few years due to its non-invasive assessment of muscle function and structure and because of the fast growing rate of digital technology which brings about new solutions and applications. Factors such as sampling rate, quantization word length, number of channels and experiment duration can lead to a potentially large volume of data. Efficient transmission and/or storage of S-EMG signals are actually a research issue. That is the aim of this work. This paper presents an algorithm for the data compression of surface electromyographic (S-EMG) signals recorded during isometric contractions protocol and during dynamic experimental protocols such as the cycling activity. The proposed algorithm is based on discrete wavelet transform to proceed spectral decomposition and de-correlation, on a dynamic bit allocation procedure to code the wavelets transformed coefficients, and on an entropy coding to minimize the remaining redundancy and to pack all data. The bit allocation scheme is based on mathematical decreasing spectral shape models, which indicates a shorter digital word length to code high frequency wavelets transformed coefficients. Four bit allocation spectral shape methods were implemented and compared: decreasing exponential spectral shape, decreasing linear spectral shape, decreasing square-root spectral shape and rotated hyperbolic tangent spectral shape. The proposed method is demonstrated and evaluated for an isometric protocol and for a dynamic protocol using a real S-EMG signal data bank. Objective performance evaluations metrics are presented. In addition, comparisons with other encoders proposed in scientific literature are shown. The decreasing bit allocation shape applied to the quantized wavelet coefficients combined with arithmetic coding results is an efficient procedure. The performance comparisons of the proposed S-EMG data compression algorithm with the established

  10. 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.

  11. 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.

  12. Detection of Simulated Vocal Dysfunctions Using Complex sEMG Patterns.

    Science.gov (United States)

    Smith, Nicholas R; Rivera, Luis A; Dietrich, Maria; Shyu, Chi-Ren; Page, Matthew P; DeSouza, Guilherme N

    2016-05-01

    Symptoms of voice disorder may range from slight hoarseness to complete loss of voice; from modest vocal effort to uncomfortable neck pain. But even minor symptoms may still impact personal and especially professional lives. While early detection and diagnosis can ameliorate that effect, to date, we are still largely missing reliable and valid data to help us better screen for voice disorders. In our previous study, we started to address this gap in research by introducing an ambulatory voice monitoring system using surface electromyography (sEMG) and a robust algorithm (HiGUSSS) for pattern recognition of vocal gestures. Here, we expand on that work by further analyzing a larger set of simulated vocal dysfunctions. Our goal is to demonstrate that such a system has the potential to recognize and detect real vocal dysfunctions from multiple individuals with high accuracy under both intra and intersubject conditions. The proposed system relies on four sEMG channels to simultaneously process various patterns of sEMG activation in the search for maladaptive laryngeal activity that may lead to voice disorders. In the results presented here, our pattern recognition algorithm detected from two to ten different classes of sEMG patterns of muscle activation with an accuracy as high as 99%, depending on the subject and the testing conditions.

  13. 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.

  14. 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.

  15. The averaged EMGs recorded from the arm muscles during bimanual rowing movements

    Directory of Open Access Journals (Sweden)

    Tomasz eTomiak

    2015-11-01

    Full Text Available The main purpose was to analyze quantitatively the the average surface EMGs of the muscles that function around the elbow and shoulder joints of both arms in similar bimanual ‘rowing’ movements, which were produced under identical elastic loads applied to the levers (‘oars’. The muscles of PM group (‘pulling’ muscles: elbow flexors, shoulder extensors generated noticeable velocity-dependent dynamic EMG components during the pulling and returning phases of movement and supported a steady-state activity during the hold phase. The muscles of RM group (‘returning’ muscles: elbow extensors, shoulder flexors co-contracted with PM group during the movement phases and decreased activity during the hold phase. The dynamic components of the EMGs strongly depended on the velocity factor in both muscle groups, whereas the side and load factors and combinations of various factors acted only in PM group muscles. Various subjects demonstrated diverse patterns of activity redistribution among muscles. We assume that central commands to the same muscles in two arms may be essentially different during execution of similar movement programs. Extent of the diversity in the EMG patterns of such muscles may reflect the subject’s skilling in motor performance; on the other hand, the diversity can reflect redistribution of activity between synergic muscles, thus providing a mechanism directed against development of the muscle fatigue.

  16. Effect of sex on torque, recovery, EMG, and MMG responses to fatigue

    Science.gov (United States)

    Hill, E.C.; Housh, T.J.; Smith, C.M.; Cochrane, K.C.; Jenkins, N.D.M.; Cramer, J.T.; Schmidt, R.J.; Johnson, G.O.

    2016-01-01

    Objective: The purpose of the present investigation was to examine the effect of sex on maximal voluntary isometric contraction (MVIC) torque and the EMG and MMG responses as a result of fatiguing, intermittent, submaximal (65% of MVIC), isometric elbow flexion muscle contractions. Methods: Eighteen men and women performed MVIC trials before (pretest), after (posttest), and 5-min after (5-min recovery) performing 50 intermittent, submaximal isometric muscle contractions. Surface electromyographic (EMG) and mechanomyographic (MMG) signals were simultaneously recorded from the biceps brachii muscle. Results: As a result of the fatiguing workbout torque decreased similarly from pretest to posttest for both the men (24.0%) and women (23.3%). After 5-min of recovery, torque had partially recovered for the men, while torque had returned to pretest levels for the women. For both sexes, from pretest to posttest EMG mean power frequency and MMG amplitude decreased, but returned to pretest levels after 5-min of recovery. Conclusions: In the present study, there were sex-related differences in muscle fatigue that were not associated with the EMG or MMG responses. PMID:27973383

  17. Influence of fatigue on hand muscle coordination and EMG-EMG coherence during three-digit grasping.

    Science.gov (United States)

    Danna-Dos Santos, Alessander; Poston, Brach; Jesunathadas, Mark; Bobich, Lisa R; Hamm, Thomas M; Santello, Marco

    2010-12-01

    Fingertip force control requires fine coordination of multiple hand muscles within and across the digits. While the modulation of neural drive to hand muscles as a function of force has been extensively studied, much less is known about the effects of fatigue on the coordination of simultaneously active hand muscles. We asked eight subjects to perform a fatiguing contraction by gripping a manipulandum with thumb, index, and middle fingers while matching an isometric target force (40% maximal voluntary force) for as long as possible. The coordination of 12 hand muscles was quantified as electromyographic (EMG) muscle activation pattern (MAP) vector and EMG-EMG coherence. We hypothesized that muscle fatigue would cause uniform changes in EMG amplitude across all muscles and an increase in EMG-EMG coherence in the higher frequency bands but with an invariant heterogeneous distribution across muscles. Muscle fatigue caused a 12.5% drop in the maximum voluntary contraction force (P EMG amplitude of all muscles increased during the fatiguing contraction (P muscle coordination pattern was used throughout the fatiguing contraction. Last, EMG-EMG coherence (0-35 Hz) was significantly greater at the end than at the beginning of the fatiguing contraction (P muscles. These findings suggest that similar mechanisms are involved for modulating and sustaining digit forces in nonfatiguing and fatiguing contractions, respectively.

  18. Young, Healthy Subjects Can Reduce the Activity of Calf Muscles When Provided with EMG Biofeedback in Upright Stance.

    Science.gov (United States)

    Vieira, Taian M; Baudry, Stéphane; Botter, Alberto

    2016-01-01

    Recent evidence suggests the minimization 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 minimizing 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 minimize the level of muscle activation during standing without increasing the excursion of the center of pressure (CoP). CoP data and surface EMG from gastrocnemii, soleus and tibialis anterior muscles were obtained from 10 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 muscle when standing with EMG biofeedback. These results may therefore posit the basis for the development of training protocols aimed at assisting subjects in more efficiently controlling leg muscle activity during standing.

  19. Speed dependence of averaged EMG profiles in walking

    NARCIS (Netherlands)

    Hof, AL; Elzinga, H; Grimmius, W; Halbertsma, JPK

    Electromyogram (EMG) profiles strongly depend on walking speed and, in pathological gait, patients do not usually walk at normal speeds. EMG data was collected from 14 muscles in two groups of healthy young subjects who walked at five different speeds ranging from 0.75 to 1.75 ms(-1). We found that

  20. EMGTools, an adaptive and versatile tool for detailed EMG analysis

    DEFF Research Database (Denmark)

    Nikolic, M; Krarup, C

    2010-01-01

    We have developed an EMG decomposition system called EMGTools that can extract the constituent MUAPs and firing patterns for quantitative analysis from the EMG signal recorded at slight effort for clinical evaluation. The aim was to implement a robust system able to handle the challenges...

  1. EMG MEDIAN POWER FREQUENCY IN AN EXHAUSTING EXERCISE

    NARCIS (Netherlands)

    AMENT, W; BONGA, GJJ; HOF, AL; VERKERKE, GJ

    1993-01-01

    EMG median power frequency of the calf muscles was investigated during an exhausting treadmill exercise. This exercise was an uphill run, the average endurance time was 1.5 min. Median power frequency of the calf muscles declined by more than 10% during this exercise. In addition EMG median power

  2. 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.

  3. Association of the Bedside Shivering Assessment Scale and derived EMG power during therapeutic hypothermia in survivors of cardiac arrest.

    Science.gov (United States)

    May, Teresa; Seder, David B; Fraser, Gilles L; Tu, Chunhao; McCrum, Barbara; Lucas, Lee; Riker, Richard R

    2011-08-01

    Shivering during therapeutic hypothermia (TH) after cardiac arrest (CA) is common, but the optimal means of detection and appropriate threshold for treatment are not established. In an effort to develop a quantitative, continuous tool to measure shivering, we hypothesized that continuous derived electromyography (dEMG) power detected by the Aspect A2000 or VISTA monitor would correlate with the intermittent Bedside Shivering Assessment Scale (BSAS) performed by nurses. Among 38 patients treated with TH after CA, 853 hourly BSAS measurements were compared to dEMG power measured every minute by a frontal surface electrode. Patients received intermittent vecuronium by protocol to treat clinically recognized shivering (BSAS>0). Mean dEMG power in decibels (dB) was determined for the hour preceding each BSAS measurement. dEMG and BSAS were compared using ANOVA. The median dEMG power for a BSAS score of 0 (no shivering) was 27 dB (IQR 26-31 dB), BSAS 1 was 30.5 dB (IQR 28-35 dB), BSAS 2 was 34 dB (IQR 30-38 dB), and BSAS 3 was 34.5 dB (IQR 32-44.25). The dEMG for BSAS≥1 (shivering) was statistically different from BSAS 0 (pShivering Assessment Scale. Given its continuous trending of dEMG power, the A2000 or VISTA may be a useful research and clinical tool for objectively monitoring shivering. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  4. Recidivemeting LEMA en EMG 2009 : Achtergrondkenmerken en strafrechtelijke recidive van de eerste LEMA- en EMG-deelnemers - tussentijdse rapportage

    NARCIS (Netherlands)

    Blom, M.

    2013-01-01

    In oktober 2008 zijn in Nederland de Lichte Educatieve Maatregel Alcohol en Verkeer (LEMA) en de Educatieve Maatregel Gedrag en Verkeer (EMG) ingevoerd. De volgende onderzoeksvragen staan centraal: Wat zijn de achtergrondkenmerken van LEMA- en EMG-deelnemers uit 2009?Wat is het recidivebeeld van

  5. 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.

  6. 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...

  7. 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.

  8. EMG evaluation of hip adduction exercises for soccer players: implications for exercise selection in prevention and treatment of groin injuries.

    Science.gov (United States)

    Serner, Andreas; Jakobsen, Markus Due; Andersen, Lars Louis; Hölmich, Per; Sundstrup, Emil; Thorborg, Kristian

    2014-07-01

    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. 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. 40 healthy male elite soccer players, training >5 h a week, participated in the study. Muscle activity using surface electromyography (sEMG) was measured bilaterally for the adductor longus during eight hip adduction strengthening exercises and peak EMG was normalised (nEMG) using an isometric maximal voluntary contraction (MVC) as reference. Furthermore, muscle activation of the gluteus medius, rectus abdominis and the external abdominal obliques was analysed during the exercises. There were large differences in peak nEMG of the adductor longus between the exercises, with values ranging from 14% to 108% nEMG (pinjuries. The Copenhagen Adduction and the hip adduction with an elastic band are dynamic high-intensity exercises, which can easily be performed at any training facility and could therefore be relevant to include in future prevention and treatment programmes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  9. Triceps Brachii in Incomplete Tetraplegia: EMG and Dynamometer Evaluation of Residual Motor Resources and Capacity for Strengthening

    Science.gov (United States)

    2013-01-01

    Background: Candidates for activity-based therapy after spinal cord injury (SCI) are often selected on the basis of manual muscle test scores and the classification of the injury as complete or incomplete. However, these scores may not adequately predict which individuals have sufficient residual motor resources for the therapy to be beneficial. Objective: We performed a preliminary study to see whether dynamometry and quantitative electromyography (EMG) can provide a more detailed assessment of residual motor resources. Methods: We measured elbow extension strength using a hand-held dynamometer and recorded fine-wire EMG from the triceps brachii muscles of 4 individuals with C5, C6, or C7 level SCI and 2 able-bodied controls. We used EMG decomposition to measure motor unit action potential (MUAP) amplitudes and motor unit (MU) recruitment and firing-rate profiles during constant and ramp contractions. Results: All 4 subjects with cervical SCI (cSCI) had increased MUAP amplitudes indicative of denervation. Two of the subjects with cSCI had very weak elbow extension strength (40 pps), suggesting profound loss of motoneurons. The other 2 subjects with cSCI had stronger elbow extension (>6 kg), more normal recruitment, and more normal firing rates, suggesting a substantial remaining motoneuron population. Conclusions: Dynamometry and quantitative EMG may provide information about the extent of gray matter loss in cSCI to help guide rehabilitation strategies. PMID:24244095

  10. 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

    Patients are not able to call for help during a generalized tonic–clonic epileptic seizure. Our objective was to develop a robust generic algorithm for automatic detection of tonic–clonic seizures, based on surface electromyography (sEMG) signals suitable for a portable device. Twenty-two seizure...

  11. FATIGUE ASSOCIATED EMG BEHAVIOR OF THE FIRST DORSAL INTEROSSEOUS AND ADDUCTOR POLLICIS MUSCLES IN DIFFERENT GROUPS OF SUBJECTS

    NARCIS (Netherlands)

    ZIJDEWIND, Inge; KERNELL, D

    We have studied the fatigue-associated behavior of surface EMG in two histochemically different muscles of the hand: fi rst dorsal interosseous (FDI) and adductor pollicis (AP; relatively more type I fibers in AP than in FDI). During a fatigue test evoked by electrical stimulation of the ulnar

  12. EMG Pattern Recognition based on Evidence Accumulation for Prosthesis Control

    Energy Technology Data Exchange (ETDEWEB)

    Lee, S.P. [Daewoo Electronics Co., Ltd., Seoul (Korea, Republic of); Park, S.H. [Yonsei University, Seoul (Korea, Republic of)

    1997-12-01

    We present a method of electromyography(EMG) pattern recognition to identify motion commands for the control of a prosthetic arm by evidence accumulation with multiple parameters. Integral absolute value, variance, autoregressive(AR) model coefficients, linear cepstrum coefficients, and adaptive cepstrum vector are extracted as feature parameters from several time segments of the EMG signals. Pattern recognition is carried out through the evidence accumulation procedure using the distances measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. Results are presented to support the feasibility of the suggested approach for EMG pattern recognition. (author). 29 refs., 11 figs., 7 tabs.

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

    Science.gov (United States)

    Contreras, Bret; Vigotsky, Andrew D; Schoenfeld, Brad J; Beardsley, Chris; Cronin, John

    2015-01-01

    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 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.

  15. A heuristic fuzzy logic approach to EMG pattern recognition for multifunctional prosthesis control.

    Science.gov (United States)

    Ajiboye, Abidemi Bolu; Weir, Richard F ff

    2005-09-01

    This paper presents a heuristic fuzzy logic approach to multiple electromyogram (EMG) pattern recognition for multifunctional prosthesis control. Basic signal statistics (mean and standard deviation) are used for membership function construction, and fuzzy c-means (FCMs) data clustering is used to automate the construction of a simple amplitude-driven inference rule base. The result is a system that is transparent to, and easily "tweaked" by, the prosthetist/clinician. Other algorithms in current literature assume a longer period of unperceivable delay, while the system we present has an update rate of 45.7 ms with little postprocessing time, making it suitable for real-time application. Five subjects were investigated (three with intact limbs, one with a unilateral transradial amputation, and one with a unilateral transradial limb-deficiency from birth). Four subjects were used for system offline analysis, and the remaining intact-limbed subject was used for system real-time analysis. We discriminated between four EMG patterns for subjects with intact limbs, and between three patterns for limb-deficient subjects. Overall classification rates ranged from 94% to 99%. The fuzzy algorithm also demonstrated success in real-time classification, both during steady state motions and motion state transitioning. This functionality allows for seamless control of multiple degrees-of-freedom in a multifunctional prosthesis.

  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. A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction.

    Science.gov (United States)

    Wöhrle, Hendrik; Tabie, Marc; Kim, Su Kyoung; Kirchner, Frank; Kirchner, Elsa Andrea

    2017-07-03

    A current trend in the development of assistive devices for rehabilitation, for example exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality and usability, for example by predicting the patient's upcoming movements using electroencephalography (EEG) or electromyography (EMG). However, these modalities have different temporal properties and classification accuracies, which results in specific advantages and disadvantages. To use physiological data analysis in rehabilitation devices, the processing should be performed in real-time, guarantee close to natural movement onset support, provide high mobility, and should be performed by miniaturized systems that can be embedded into the rehabilitation device. We present a novel Field Programmable Gate Array (FPGA) -based system for real-time movement prediction using physiological data. Its parallel processing capabilities allows the combination of movement predictions based on EEG and EMG and additionally a P300 detection, which is likely evoked by instructions of the therapist. The system is evaluated in an offline and an online study with twelve healthy subjects in total. We show that it provides a high computational performance and significantly lower power consumption in comparison to a standard PC. Furthermore, despite the usage of fixed-point computations, the proposed system achieves a classification accuracy similar to systems with double precision floating-point precision.

  18. 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

    2017-06-13

    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).

  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. Test-retest reliability of cardinal plane isokinetic hip torque and EMG.

    Science.gov (United States)

    Claiborne, Tina L; Timmons, Mark K; Pincivero, Danny M

    2009-10-01

    The objective of the present study was to establish test-retest reliability of isokinetic hip torque and prime mover electromyogram (EMG) through the three cardinal planes of motion. Thirteen healthy young adults participated in two experimental sessions, separated by approximately one week. During each session, isokinetic hip torque was evaluated on the Biodex Isokinetic Dynamometer at a velocity of 60 deg/s. Subjects performed three maximal-effort concentric and eccentric contractions, separately, for right and left hip abduction/adduction, flexion/extension, and internal/external rotation. Surface EMGs were sampled from the gluteus maximus, gluteus medius, adductor, medial and lateral hamstring, and rectus femoris muscles during all contractions. Intraclass correlation coefficients (ICC - 2,1) and standard errors of measurement (SEM) were calculated for peak torque for each movement direction and contraction mode, while ICCs were only computed for the EMG data. Motions that demonstrated high torque reliability included concentric hip abduction (right and left), flexion (right and left), extension (right) and internal rotation (right and left), and eccentric hip abduction (left), adduction (left), flexion (right), and extension (right and left) (ICC range=0.81-0.91). Motions with moderate torque reliability included concentric hip adduction (right), extension (left), internal rotation (left), and external rotation (right), and eccentric hip abduction and adduction (right), flexion (left), internal rotation (right and left), and external rotation (right and left) (ICC range=0.49-0.79). The majority of the EMG sampled muscles (n=12 and n=11 for concentric and eccentric contractions, respectively) demonstrated high reliability (ICC=0.81-0.95). Instances of low, or unacceptable, EMG reliability values occurred for the medial hamstring muscle of the left leg (both contraction modes) and the adductor muscle of the right leg during eccentric internal rotation. The major

  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. Anal sphincter EMG in the diagnosis of parkinsonian syndromes

    DEFF Research Database (Denmark)

    Winge, K; Jennum, Poul Jørgen; Løkkegaard, Annemette

    2010-01-01

    The role of electromyography (EMG) recorded from the external anal sphincter (EAS) in the diagnosis of atypical parkinsonian syndromes is a matter for continuous debate. Most studies addressing this issue are retrospective.......The role of electromyography (EMG) recorded from the external anal sphincter (EAS) in the diagnosis of atypical parkinsonian syndromes is a matter for continuous debate. Most studies addressing this issue are retrospective....

  3. 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

  4. 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.

  5. Speedup computation of HD-sEMG signals using a motor unit-specific electrical source model.

    Science.gov (United States)

    Carriou, Vincent; Boudaoud, Sofiane; Laforet, Jeremy

    2018-01-23

    Nowadays, bio-reliable modeling of muscle contraction is becoming more accurate and complex. This increasing complexity induces a significant increase in computation time which prevents the possibility of using this model in certain applications and studies. Accordingly, the aim of this work is to significantly reduce the computation time of high-density surface electromyogram (HD-sEMG) generation. This will be done through a new model of motor unit (MU)-specific electrical source based on the fibers composing the MU. In order to assess the efficiency of this approach, we computed the normalized root mean square error (NRMSE) between several simulations on single generated MU action potential (MUAP) using the usual fiber electrical sources and the MU-specific electrical source. This NRMSE was computed for five different simulation sets wherein hundreds of MUAPs are generated and summed into HD-sEMG signals. The obtained results display less than 2% error on the generated signals compared to the same signals generated with fiber electrical sources. Moreover, the computation time of the HD-sEMG signal generation model is reduced to about 90% compared to the fiber electrical source model. Using this model with MU electrical sources, we can simulate HD-sEMG signals of a physiological muscle (hundreds of MU) in less than an hour on a classical workstation. Graphical Abstract Overview of the simulation of HD-sEMG signals using the fiber scale and the MU scale. Upscaling the electrical source to the MU scale reduces the computation time by 90% inducing only small deviation of the same simulated HD-sEMG signals.

  6. 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...

  7. A comparison of surface marker analysis and FAB classification in acute myeloid leukemia

    NARCIS (Netherlands)

    van der Reijden, H. J.; van Rhenen, D. J.; Lansdorp, P. M.; van't Veer, M. B.; Langenhuijsen, M. M.; Engelfriet, C. P.; von dem Borne, A. E.

    1983-01-01

    Surface marker analysis with rosette tests and a large panel of xenoantisera and monoclonal antibodies was done on the malignant cells of 55 patients with acute myeloid leukemia (AML). The diagnosis was made on morphological and cytochemical grounds, and the leukemias were classified according to

  8. 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....

  9. 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.

  10. Prosthetic EMG control enhancement through the application of man-machine principles

    Science.gov (United States)

    Simcox, W. A.

    1977-01-01

    An area in medicine that appears suitable to man-machine principles is rehabilitation research, particularly when the motor aspects of the body are involved. If one considers the limb, whether functional or not, as the machine, the brain as the controller and the neuromuscular system as the man-machine interface, the human body is reduced to a man-machine system that can benefit from the principles behind such systems. The area of rehabilitation that this paper deals with is that of an arm amputee and his prosthetic device. Reducing this area to its man-machine basics, the problem becomes one of attaining natural multiaxis prosthetic control using Electromyographic activity (EMG) as the means of communication between man and prothesis. In order to use EMG as the communication channel it must be amplified and processed to yield a high information signal suitable for control. The most common processing scheme employed is termed Mean Value Processing. This technique for extracting the useful EMG signal consists of a differential to single ended conversion to the surface activity followed by a rectification and smoothing.

  11. Neuromuscular interfacing: a novel approach to EMG-driven multiple DOF physiological models.

    Science.gov (United States)

    Pau, James W L; Xie, Shane S Q; Xu, W L

    2013-01-01

    This paper presents a novel approach that involves first identifying and verifying the available superficial muscles that can be recorded by surface electromyography (EMG) signals, and then developing a musculoskeletal model based on these findings, which have specifically independent DOFs for movement. Such independently controlled multiple DOF EMG-driven models have not been previously developed and a two DOF model for the masticatory system was achieved by implementing independent antagonist muscle combinations for vertical and lateral movements of the jaw. The model has six channels of EMG signals from the bilateral temporalis, masseter and digastric muscles to predict the motion of the mandible. This can be used in a neuromuscular interface to manipulate a jaw exoskeleton for rehabilitation. For a range of different complexities of jaw movements, the presented model is able to consistently identify movements with 0.28 - 0.46 average normalized RMSE. The results demonstrate the feasibility of the approach at determining complex multiple DOF movements and its applicability to any joint system.

  12. 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.

  13. Facial EMG responses to odors in solitude and with an audience.

    Science.gov (United States)

    Jäncke, L; Kaufmann, N

    1994-04-01

    Two experiments were undertaken to examine whether facial responses to odors correlate with the hedonic odor evaluation. Experiment 1 examined whether subjects (n = 20) spontaneously generated facial movements associated with odor evaluation when they are tested in private. To measure facial responses, EMG was recorded over six muscle regions (M. corrugator supercilii, M. procerus, M. nasalis, M. levator, M. orbicularis oculi and M. zygomaticus major) using surface electrodes. In experiment 2 the experimental group (n = 10) smelled the odors while they were visually inspected by the experimenter sitting in front of the test subjects. The control group (n = 10) performed the same experimental condition as those subjects participating in experiment 1. Facial EMG over four mimetic muscle regions (M. nasalis, M. levator, M. zygomaticus major, M. orbicularis oculi) was measured while subjects smelled different odors. The main findings of this study may be summarized as follows: (i) there was no correlation between valence rating and facial EMG responses; (ii) pleasant odors did not evoke smiles when subjects smelled the odors in private; (iii) in solitude, highly concentrated malodors evoked facial EMG reactions of those mimetic muscles which are mainly involved in generating a facial display of disgust; (iv) those subjects confronted with an audience showed stronger facial reactions over the periocular and cheek region (indicative of a smile) during the smelling of pleasant odors than those who smelled these odors in private; (v) those subjects confronted with an audience showed stronger facial reactions over the M. nasalis region (indicative of a display of disgust) during the smelling of malodors than those who smelled the malodors in private. These results were taken as evidence for a more social communicative function of facial displays and strongly mitigates the reflexive-hedonic interpretation of facial displays to odors as supposed by Steiner.

  14. Determination of Fatigue Following Maximal Loaded Treadmill Exercise by Using Wavelet Packet Transform Analysis and MLPNN from MMG-EMG Data Combinations.

    Science.gov (United States)

    Bilgin, Gürkan; Hindistan, I Ethem; Özkaya, Y Gül; Köklükaya, Etem; Polat, Övünç; Çolak, Ömer H

    2015-10-01

    The muscle fatigue can be expressed as decrease in maximal voluntary force generating capacity of the neuromuscular system as a result of peripheral changes at the level of the muscle, and also failure of the central nervous system to drive the motoneurons adequately. In this study, a muscle fatigue detection method based on frequency spectrum of electromyogram (EMG) and mechanomyogram (MMG) has been presented. The EMG and MMG data were obtained from 31 healthy, recreationally active men at the onset, and following exercise. All participants were performed a maximally exercise session in a motor-driven treadmill by using standard Bruce protocol which is the most widely used test to predict functional capacity. The method used in the present study consists of pre-processing, determination of the energy value based on wavelet packet transform, and classification phases. The results of the study demonstrated that changes in the MMG 176-234 Hz and EMG 254-313 Hz bands are critical to determine for muscle fatigue occurred following maximally exercise session. In conclusion, our study revealed that an algorithm with EMG and MMG combination based on frequency spectrum is more effective for the detection of muscle fatigue than EMG or MMG alone.

  15. Exhaustive comparison and classification of ligand-binding surfaces in proteins

    OpenAIRE

    Murakami, Yoichi; Kinoshita, Kengo; Kinjo, Akira R; Nakamura, Haruki

    2013-01-01

    Many proteins function by interacting with other small molecules (ligands). Identification of ligand-binding sites (LBS) in proteins can therefore help to infer their molecular functions. A comprehensive comparison among local structures of LBSs was previously performed, in order to understand their relationships and to classify their structural motifs. However, similar exhaustive comparison among local surfaces of LBSs (patches) has never been performed, due to computational complexity. To e...

  16. 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.

  17. Assessing three fuel classification systems and their maps using Forest Inventory and Analysis (FIA) surface fuel measurements

    Science.gov (United States)

    Robert E. Keane; Jason M. Herynk; Chris Toney; Shawn P. Urbanski; Duncan C. Lutes; Roger D. Ottmar

    2015-01-01

    Fuel classifications are integral tools in fire management and planning because they are used as inputs to fire behavior and effects simulation models. Fuel Loading Models (FLMs) and Fuel Characteristic Classification System (FCCSs) fuelbeds are the most popular classifications used throughout wildland fire science and management, but they have yet to be thoroughly...

  18. 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.

  19. 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

    Current pig house cleaning procedures are hazardous to the health of farm workers, and yet necessary if the spread of disease between batches of animals is to be satisfactorily controlled. Autonomous cleaning using robot technology offers salient benefits. This report addresses the feasibility...... 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...

  20. 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

  1. 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

  2. Multi-subject/daily-life activity EMG-based control of mechanical hands

    Directory of Open Access Journals (Sweden)

    Fiorilla Angelo

    2009-11-01

    Full Text Available Abstract Background Forearm surface electromyography (EMG has been in use since the Sixties to feed-forward control active hand prostheses in a more and more refined way. Recent research shows that it can be used to control even a dexterous polyarticulate hand prosthesis such as Touch Bionics's i-LIMB, as well as a multifingered, multi-degree-of-freedom mechanical hand such as the DLR II. In this paper we extend previous work and investigate the robustness of such fine control possibilities, in two ways: firstly, we conduct an analysis on data obtained from 10 healthy subjects, trying to assess the general applicability of the technique; secondly, we compare the baseline controlled condition (arm relaxed and still on a table with a "Daily-Life Activity" (DLA condition in which subjects walk, raise their hands and arms, sit down and stand up, etc., as an experimental proxy of what a patient is supposed to do in real life. We also propose a cross-subject model analysis, i.e., training a model on a subject and testing it on another one. The use of pre-trained models could be useful in shortening the time required by the subject/patient to become proficient in using the hand. Results A standard machine learning technique was able to achieve a real-time grip posture classification rate of about 97% in the baseline condition and 95% in the DLA condition; and an average correlation to the target of about 0.93 (0.90 while reconstructing the required force. Cross-subject analysis is encouraging although not definitive in its present state. Conclusion Performance figures obtained here are in the same order of magnitude of those obtained in previous work about healthy subjects in controlled conditions and/or amputees, which lets us claim that this technique can be used by reasonably any subject, and in DLA situations. Use of previously trained models is not fully assessed here, but more recent work indicates it is a promising way ahead.

  3. 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.

  4. 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.

  5. 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.

  6. sEMG Sensor Using Polypyrrole-Coated Nonwoven Fabric Sheet for Practical Control of Prosthetic Hand.

    Science.gov (United States)

    Jiang, Yinlai; Togane, Masami; Lu, Baoliang; Yokoi, Hiroshi

    2017-01-01

    One of the greatest challenges of using a myoelectric prosthetic hand in daily life is to conveniently measure stable myoelectric signals. This study proposes a novel surface electromyography (sEMG) sensor using polypyrrole-coated nonwoven fabric sheet as electrodes (PPy electrodes) to allow people with disabilities to control prosthetic limbs. The PPy electrodes are sewn on an elastic band to guarantee close contact with the skin and thus reduce the contact electrical impedance between the electrodes and the skin. The sensor is highly customizable to fit the size and the shape of the stump so that people with disabilities can attach the sensor by themselves. The performance of the proposed sensor was investigated experimentally by comparing measurements of Ag/AgCl electrodes with electrolytic gel and the sEMG from the same muscle fibers. The high correlation coefficient (0.87) between the two types of sensors suggests the effectiveness of the proposed sensor. Another experiment of sEMG pattern recognition to control myoelectric prosthetic hands showed that the PPy electrodes are as effective as Ag/AgCl electrodes for measuring sEMG signals for practical myoelectric control. We also investigated the relation between the myoelectric signals' signal-to-noise ratio and the source impedances by simultaneously measuring the source impedances and the myoelectric signals with a switching circuit. The results showed that differences in both the norm and the phase of the source impedance greatly affect the common mode noise in the signal.

  7. Preliminary Study on Continuous Recognition of Elbow Flexion/Extension Using sEMG Signals for Bilateral Rehabilitation

    Directory of Open Access Journals (Sweden)

    Zhibin Song

    2016-10-01

    Full Text Available Surface electromyography (sEMG signals are closely related to the activation of human muscles and the motion of the human body, which can be used to estimate the dynamics of human limbs in the rehabilitation field. They also have the potential to be used in the application of bilateral rehabilitation, where hemiplegic patients can train their affected limbs following the motion of unaffected limbs via some rehabilitation devices. Traditional methods to process the sEMG focused on motion pattern recognition, namely, discrete patterns, which are not satisfactory for use in bilateral rehabilitation. In order to overcome this problem, in this paper, we built a relationship between sEMG signals and human motion in elbow flexion and extension on the sagittal plane. During the conducted experiments, four participants were required to perform elbow flexion and extension on the sagittal plane smoothly with only an inertia sensor in their hands, where forearm dynamics were not considered. In these circumstances, sEMG signals were weak compared to those with heavy loads or high acceleration. The contrastive experimental results show that continuous motion can also be obtained within an acceptable precision range.

  8. 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.

  9. 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.

  10. Surface Electromyography for Speech and Swallowing Systems: Measurement, Analysis, and Interpretation

    Science.gov (United States)

    Stepp, Cara E.

    2012-01-01

    Purpose: Applying surface electromyography (sEMG) to the study of voice, speech, and swallowing is becoming increasingly popular. An improved understanding of sEMG and building a consensus as to appropriate methodology will improve future research and clinical applications. Method: An updated review of the theory behind recording sEMG for the…

  11. 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....

  12. 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

  13. 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...... for infants younger than 9 weeks, whereas a short-lasting (10-20 ms) central peak was observed for EMG-EMG synchronization in older infants. This peak was largest for infants aged 9-25 weeks. These data suggest that the corticospinal drive to lower and upper limb muscles shows significant developmental...... changes with an increase in functional coupling in infants aged 9-25 weeks, a period which coincides partly with the developmental period of normal fidgety movements. We propose that these neurophysiological findings may reflect the existence of a sensitive period where the functional connections between...

  14. EMG-based detection of muscle fatigue during low-level isometric contraction by recurrence quantification analysis and monopolar configuration.

    Science.gov (United States)

    Ito, Kenichi; Hotta, Yu

    2012-01-01

    The center frequency (CF) of the power spectral density of a bipolar-configured surface electromyogram is typically used as an index of muscle fatigue. However, this index may be inadequate for measuring wave slowing due to muscle fatigue during low-level contractions. A previous study in which strong muscle fatigue was mimicked by compressing the proximal region of the forearm during isometric contractions showed that the differences in the degree of fatigue under compression and non-compression conditions were undetectable. The purpose of this study was to improve detection sensitivity of surface EMG variation caused by muscle fatigue using two approaches. The first approach employed recurrence quantification analysis (RQA) instead of traditional frequency analysis (FA) to compute the muscle fatigue index. The second approach employed a monopolar configuration for measuring surface EMG. We measured the surface EMG signal by using monopolar and bipolar configurations simultaneously during low-level isometric contractions under blood flow-restricted (BFR) and unrestricted (CON) conditions, and then compared and evaluated the detected differences in muscle fatigue. The results showed that the effect of BFR was better detected by RQA than by FA, and that the fatigability change was larger in the monopolar configuration than in the bipolar configuration.

  15. 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.

  16. The EMG activity-acceleration relationship to quantify the optimal vibration load when applying synchronous whole-body vibration.

    Science.gov (United States)

    Di Giminiani, Riccardo; Masedu, Francesco; Padulo, Johnny; Tihanyi, Jozsef; Valenti, Marco

    2015-12-01

    To date are lacking methodological approaches to individualizing whole-body vibration (WBV) intensity. The aim of this study was: (1) to determine the surface-electromyography-root-mean-square (sEMG(RMS))-acceleration load relationship in the vastus lateralis (VL), vastus medialis (VM), rectus femoris (RF), lateral gastrocnemius (LG) muscles during synchronous WBV, and (2) to assess the reliability of the acceleration corresponding to the maximal sEMG(RMS). Twenty-five sportsman voluntarily took part in this study with a single-group, repeated-measures design. All subjects postured themselves in an isometric half-squat during nine trials in the following conditions: no vibrations and random vibrations of different acceleration loads (from 0.12 to 5.72 g). The sEMG(RMS) were dependent on the acceleration loads in the VL (p = 0.0001), LG (p = 0.0001) and VM (p = 0.011) muscles; while RF was not affected by the acceleration loads (p = 0.508). The comparisons among the sEMG(RMS)-accelerations relationships revealed a significant difference between the LG and the others muscles (p = 0.001). No significant difference was found between the different thigh muscles (p > 0.05). The intra-class correlation coefficient ranged from 0.87 to 0.99 for the measurements performed on the LG, VL and VM. The sEMG(RMS)-acceleration relationship in the VL, VM and LG is a reliable test to individualize the WBV intervention. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. 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

  18. Does EMG activation differ among fatigue-resistant leg muscles ...

    African Journals Online (AJOL)

    The participants (N=32) were divided into two groups according to the Fatigue Index value [Group I: Less Fatigue Resistant (LFR), n=17; Group II: More Fatigue Resistant (MFR), n=15]. The repeated EMG activities of four leg muscles [rectus femoris, biceps femoris, vastus lateralis and vastus medialis] were analysed during ...

  19. 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.

  20. 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

  1. Comparison of the EMG Activities in the Vastus Medialis Oblique ...

    African Journals Online (AJOL)

    The purpose of this study was to compare the electromyographic (EMG) activities in the vastus medialis oblique (VMO) and vastus lateralis (VL) muscles during two open chain exercises commonly used in the management of patellofemoral pain syndrome (PFPS). Twenty-five (14 female and 11 male) healthy subjects ...

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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.

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

    Science.gov (United States)

    Shair, E F; Ahmad, S A; Marhaban, M H; Mohd Tamrin, S B; 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.

  8. 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.

  9. EMG-based simultaneous and proportional estimation of wrist/hand kinematics in uni-lateral trans-radial amputees

    Science.gov (United States)

    2012-01-01

    We propose a method for estimating wrist kinematics during dynamic wrist contractions from multi-channel surface electromyography (EMG). The algorithm extracts features from the surface EMG and uses dedicated multi-layer perceptron networks to estimate individual joint angles of the 3 degrees of freedom (DoFs) of the wrist. The method was designed with the aim of proportional and simultaneous control of multiple DoFs of active prostheses by unilateral amputees. Therefore, the proposed approach was tested in both unilateral transradial amputees and in intact-limbed control subjects. It was shown that the joint angles at the 3 DoFs of amputees can be estimated from surface EMG recordings , during mirrored bi-lateral contractions that simultaneously and proportionally articulated the 3 DoFs. The estimation accuracies of amputee subjects with long stumps were 62.5% ± 8.50% across all 3 DoFs, while accuracies of the intact-limbed control subjects were 72.0% ± 8.29%. The estimation results from intact-limbed subjects were consistent with earlier studies. The results from the current study demonstrated the feasibility of the proposed myoelectric control approach to provide a more intuitive myoelectric control strategy for unilateral transradial amputees. PMID:22742707

  10. EMG-based simultaneous and proportional estimation of wrist/hand kinematics in uni-lateral trans-radial amputees

    Directory of Open Access Journals (Sweden)

    Jiang Ning

    2012-06-01

    Full Text Available Abstract We propose a method for estimating wrist kinematics during dynamic wrist contractions from multi-channel surface electromyography (EMG. The algorithm extracts features from the surface EMG and uses dedicated multi-layer perceptron networks to estimate individual joint angles of the 3 degrees of freedom (DoFs of the wrist. The method was designed with the aim of proportional and simultaneous control of multiple DoFs of active prostheses by unilateral amputees. Therefore, the proposed approach was tested in both unilateral transradial amputees and in intact-limbed control subjects. It was shown that the joint angles at the 3 DoFs of amputees can be estimated from surface EMG recordings , during mirrored bi-lateral contractions that simultaneously and proportionally articulated the 3 DoFs. The estimation accuracies of amputee subjects with long stumps were 62.5% ± 8.50% across all 3 DoFs, while accuracies of the intact-limbed control subjects were 72.0% ± 8.29%. The estimation results from intact-limbed subjects were consistent with earlier studies. The results from the current study demonstrated the feasibility of the proposed myoelectric control approach to provide a more intuitive myoelectric control strategy for unilateral transradial amputees.

  11. Reflex-mediated dynamic neuromuscular stabilization in stroke patients: EMG processing and ultrasound imaging.

    Science.gov (United States)

    Yoon, Hyun S; You, Joshua Sung H

    2017-07-20

    Postural core instability is associated with poor dynamic balance and a high risk of serious falls. Both neurodevelopmental treatment (NDT) and dynamic neuromuscular stabilization (DNS) core stabilization exercises have been used to improve core stability, but the outcomes of these treatments remain unclear. This study was undertaken to examine the therapeutic effects of NDT and DNS core stabilization exercises on muscular activity, core stability, and core muscle thickness. Ten participants (5 healthy adults; 5 hemiparetic stroke patients) were recruited. Surface electromyography (EMG) was used to determine core muscle activity of the transversus abdominis/internal oblique (TrA/IO), external oblique (EO), and rectus abdominis (RA) muscles. Ultrasound imaging was used to measure transversus abdominals/internal oblique (TrA/IO) thickness, and a pressure biofeedback unit (PBU) was used to measure core stability during the DNS and NDT core exercise conditions. Data are reported as median and range and were compared using nonparametric Mann - Whitney U test and Wilcoxon signed rank test at p< 0.05. Both healthy and hemiparetic stroke groups showed greater median EMG amplitude in the TrA/IO muscles, core stability, and muscle thickness values during the DNS exercise condition than during the NDT core exercise condition, respectively (p< 0.05). However, the relative changes in the EMG amplitude, core stability, and muscle thickness values were greater during the DNS exercise condition than during the NDT core exercise condition in the hemiparetic stroke patient group (p< 0.05). Our novel results provide the first clinical evidence that DNS is more effective than NDT in both healthy and hemiparetic stroke subjects to provide superior deep core muscle activation, core stabilization, and muscle thickness. Moreover, such advantageous therapeutic benefits of the DNS core stabilization exercise over the NDT exercise were more apparent in the hemiparetis stroke patients than

  12. Slow-time changes in human EMG muscle fatigue states are fully represented in movement kinematics.

    Science.gov (United States)

    Song, Miao; Segala, David B; Dingwell, Jonathan B; Chelidze, David

    2009-02-01

    The ability to identify physiologic fatigue and related changes in kinematics can provide an important tool for diagnosing fatigue-related injuries. This study examined an exhaustive cycling task to demonstrate how changes in movement kinematics and variability reflect underlying changes in local muscle states. Motion kinematics data were used to construct fatigue features. Their multivariate analysis, based on smooth orthogonal decomposition, was used to reconstruct physiological fatigue. Two different features composed of (1) standard statistical metrics (SSM), which were a collection of standard long-time measures, and (2) phase space warping (PSW)-based metrics, which characterized short-time variations in the phase space trajectories, were considered. Movement kinematics and surface electromyography (EMG) signals were measured from the lower extremities of seven highly trained cyclists as they cycled to voluntary exhaustion on a stationary bicycle. Mean and median frequencies from the EMG time series were computed to measure the local fatigue dynamics of individual muscles independent of the SSM- and PSW-based features, which were extracted solely from the kinematics data. A nonlinear analysis of kinematic features was shown to be essential for capturing full multidimensional fatigue dynamics. A four-dimensional fatigue manifold identified using a nonlinear PSW-based analysis of kinematics data was shown to adequately predict all EMG-based individual muscle fatigue trends. While SSM-based analyses showed similar dominant global fatigue trends, they failed to capture individual muscle activities in a low-dimensional manifold. Therefore, the nonlinear PSW-based analysis of strictly kinematic time series data directly predicted all of the local muscle fatigue trends in a low-dimensional systemic fatigue trajectory. These results provide the first direct quantitative link between changes in muscle fatigue dynamics and resulting changes in movement kinematics.

  13. Towards the control of an active hand orthosis for people with Duchenne muscular dystrophy : Design and Validation of a wireless sEMG sleeve

    NARCIS (Netherlands)

    Nizamis, Kostas; Ganseij, Maarten; Koopman, H.F.J.M.

    2017-01-01

    Duchenne Muscular Dystrophy (DMD) is a progressive muscular disease. Active hand orthoses can greatly improve the quality of life of people with DMD. Surface Electromyography (sEMG) is commonly used for the control of active devices. The interfacing between the human and the sensor is regularly done

  14. 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).

  15. EMG signal morphology in essential tremor and Parkinson's disease.

    Science.gov (United States)

    Ruonala, V; Meigal, A; Rissanen, S M; Airaksinen, O; Kankaanpaa, M; Karjalainen, P A

    2013-01-01

    The aim of this work was to differentiate patients with essential tremor from patients with Parkinson's disease. The electromyographic signal from the biceps brachii muscle was measured during isometric tension from 17 patients with essential tremor, 35 patients with Parkinson's disease, and 40 healthy controls. The EMG signals were high pass filtered and divided to smaller segments from which histograms were calculated using 200 histogram bins. EMG signal histogram shape was analysed with a feature dimension reduction method, the principal component analysis, and the shape parameters were used to differentiate between different patient groups. The height of the histogram and the side difference between left and right hand were the best discriminators between essential tremor and Parkinson's disease groups. With this method, it was possible to discriminate 13/17 patients with essential tremor from 26/35 patients with Parkinson's disease and 14/17 patients with essential tremor from 29/40 healthy controls.

  16. 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.

  17. Bizarre repetitive discharges recorded with single fibre EMG.

    OpenAIRE

    Trontelj, J; Stålberg, E

    1983-01-01

    Single fibre EMG was used to record bizarre repetitive discharges in patients with chronic denervation or muscle disorders. The low variability of intervals between individual spike components on successive discharges suggests that the bizarre repetitive discharges are based on ephaptic impulse transmission from the muscle fibre starting the discharge (principal pacemaker) to the adjacent muscle fibres. The low variability of the interdischarge intervals is explained by ephaptic reactivation ...

  18. Fuzzy Control of a Robotic Arm using EMG Signals

    OpenAIRE

    Hidalgo, M.; Tene, G.; Sánchez Terán, Alberto

    2007-01-01

    This paper presents the control design of a robotic arm employing Fuzzy algorithms to interpret electromiographic (EMG) signals from the Flexor Carpi Radialis, Extensor Carpi Radialis and Biceps Brachii muscles. The control and aquisition systems is composed of a microprocessor, analog ?ltering, digital ?ltering and frequency analysis, and ?nally a fuzzy control system. The system has been implemented over a MICROCHIP PIC 16F876 and LabVIEW.

  19. 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.

  20. 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.

  1. 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

  2. Effects of innovative virtual reality game and EMG biofeedback on neuromotor control in cerebral palsy.

    Science.gov (United States)

    Yoo, Ji Won; Lee, Dong Ryul; Sim, Yon Ju; You, Joshua H; Kim, Cheol J

    2014-01-01

    Sensorimotor control dysfunction or dyskinesia is a hallmark of neuromuscular impairment in children with cerebral palsy (CP), and is often implicated in reaching and grasping deficiencies due to a neuromuscular imbalance between the triceps and biceps. To mitigate such muscle imbalances, an innovative electromyography (EMG)-virtual reality (VR) biofeedback system were designed to provide accurate information about muscle activation and motivation. However, the clinical efficacy of this approach has not yet been determined in children with CP. The purpose of this study was to investigate the effectiveness of a combined EMG biofeedback and VR (EMG-VR biofeedback) intervention system to improve muscle imbalance between triceps and biceps during reaching movements in children with spastic CP. Raw EMG signals were recorded at a sampling rate of 1,000 Hz, band-pass filtered between 20-450 Hz, and notch-filtered at 60 Hz during elbow flexion and extension movements. EMG data were then processed using MyoResearch Master Edition 1.08 XP software. All participants underwent both interventions consisting of the EMG-VR biofeedback combination and EMG biofeedback alone. EMG analysis resulted in improved muscle activation in the underactive triceps while decreasing overactive or hypertonic biceps in the EMG-VR biofeedback compared with EMG biofeedback. The muscle imbalance ratio between the triceps and biceps was consistently improved. The present study is the first clinical trial to provide evidence for the additive benefits of VR intervention for enhancing the upper limb function of children with spastic CP.

  3. Terrain surfaces and 3-D landcover classification from small footprint full-waveform lidar data: application to badlands

    Directory of Open Access Journals (Sweden)

    F. Bretar

    2009-08-01

    Full Text Available This article presents the use of new remote sensing data acquired from airborne full-waveform lidar systems for hydrological applications. Indeed, the knowledge of an accurate topography and a landcover classification is a prior knowledge for any hydrological and erosion model. Badlands tend to be the most significant areas of erosion in the world with the highest erosion rate values. Monitoring and predicting erosion within badland mountainous catchments is highly strategic due to the arising downstream consequences and the need for natural hazard mitigation engineering.

    Additionally, beyond the elevation information, full-waveform lidar data are processed to extract the amplitude and the width of echoes. They are related to the target reflectance and geometry. We will investigate the relevancy of using lidar-derived Digital Terrain Models (DTMs and the potentiality of the amplitude and the width information for 3-D landcover classification. Considering the novelty and the complexity of such data, they are presented in details as well as guidelines to process them. The morphological validation of DTMs is then performed via the computation of hydrological indexes and photo-interpretation. Finally, a 3-D landcover classification is performed using a Support Vector Machine classifier. The use of an ortho-rectified optical image in the classification process as well as full-waveform lidar data for hydrological purposes is finally discussed.

  4. 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.

  5. 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

  6. 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.

  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. Classifying Classifications

    DEFF Research Database (Denmark)

    Debus, Michael S.

    2017-01-01

    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......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...... into the topic of game classifications....

  9. [Anatomical names of skeletal surfaces: analysis and classification of Latin names, and comparison with corresponding Japanese names].

    Science.gov (United States)

    Shikano, Shun-ichi; Yamashita, Yasuo; Sato, Tatsuo

    2007-12-01

    For better understanding of the structures comprising the human body and in view of possible need for future revision, Latin anatomical names (Terminologia Anatomica) of the skeletal surfaces were analyzed and classified, and compared with the corresponding Japanese anatomical names. The words following Facies indicated: 1) morphological resemblance of the surface; 2) the structure that articulates with the surface; 3) the structure attached to the surface; 4) the structure in contact with the surface; 5) the way of connection between the surface and the structure that faces it; 6) the structure of which the surface is a component; 7) the structure that the surface faces; 8) the site that the surface faces; 9) the relative position of the surface; 10) the non-relative position of the surface; 11) an articulation of the surface; or 12) both the structure with which the surface articulates and the structure of which the surface is a component. Analysis of Latin names and comparison with Japanese names clarified some characteristics of both names and revealed some problems in them.

  10. Classification complexity in myoelectric pattern recognition.

    Science.gov (United States)

    Nilsson, Niclas; Håkansson, Bo; Ortiz-Catalan, Max

    2017-07-10

    Limb prosthetics, exoskeletons, and neurorehabilitation devices can be intuitively controlled using myoelectric pattern recognition (MPR) to decode the subject's intended movement. In conventional MPR, descriptive electromyography (EMG) features representing the intended movement are fed into a classification algorithm. The separability of the different movements in the feature space significantly affects the classification complexity. Classification complexity estimating algorithms (CCEAs) were studied in this work in order to improve feature selection, predict MPR performance, and inform on faulty data acquisition. CCEAs such as nearest neighbor separability (NNS), purity, repeatability index (RI), and separability index (SI) were evaluated based on their correlation with classification accuracy, as well as on their suitability to produce highly performing EMG feature sets. SI was evaluated using Mahalanobis distance, Bhattacharyya distance, Hellinger distance, Kullback-Leibler divergence, and a modified version of Mahalanobis distance. Three commonly used classifiers in MPR were used to compute classification accuracy (linear discriminant analysis (LDA), multi-layer perceptron (MLP), and support vector machine (SVM)). The algorithms and analytic graphical user interfaces produced in this work are freely available in BioPatRec. NNS and SI were found to be highly correlated with classification accuracy (correlations up to 0.98 for both algorithms) and capable of yielding highly descriptive feature sets. Additionally, the experiments revealed how the level of correlation between the inputs of the classifiers influences classification accuracy, and emphasizes the classifiers' sensitivity to such redundancy. This study deepens the understanding of the classification complexity in prediction of motor volition based on myoelectric information. It also provides researchers with tools to analyze myoelectric recordings in order to improve classification performance.

  11. Real-time detection, classification, and quantification of apneic episodes using miniature surface motion sensors in rats.

    Science.gov (United States)

    Waisman, Dan; Lev-Tov, Lior; Levy, Carmit; Faingersh, Anna; Colman Klotzman, Ifat; Bibi, Haim; Rotschild, Avi; Landesberg, Amir

    2015-07-01

    Real-time detection and classification of apneic episodes remain significant challenges. This study explores the applicability of a novel method of monitoring the respiratory effort and dynamics for rapid detection and classification of apneic episodes. Obstructive apnea (OA) and hypopnea/central apnea (CA) were induced in nine tracheostomized rats, by short-lived airway obstruction and administration of succinylcholine, respectively. Esophageal pressure (EP), EtCO2, arterial O2 saturation (SpO2), heart rate, and blood pressure were monitored. Respiratory dynamics were monitored utilizing three miniature motion sensors placed on the chest and epigastrium. Three indices were derived from these sensors: amplitude of the tidal chest wall displacement (TDi), breath time length (BTL), that included inspiration and rapid expiration phases, and amplitude time integral (ATI), the integral of breath amplitude over time. OA induced a progressive 6.42 ± 3.48-fold increase in EP from baseline, which paralleled a 3.04 ± 1.19-fold increase in TDi (P classification of central and obstructive apneic episodes, which tightly correlates with the EP.

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

    Science.gov (United States)

    Colyer, Steffi L; McGuigan, Polly M

    2018-03-01

    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.

  13. 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.

  14. 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.

  15. Postural and dynamic masseter and anterior temporalis muscle EMG repeatability in serial assessments.

    Science.gov (United States)

    Suvinen, T I; Malmberg, J; Forster, C; Kemppainen, P

    2009-11-01

    Electromyographic (EMG) assessment has been used as a non-invasive tool to objectively assess muscle function, although with controversial research and clinical potential. The aim of this study was to assess within-, inter-subject and between-day repeatability of serial EMG recordings. The study sample included 10 asymptomatic subjects with no history of temporomandibular disorders or muscle parafunctions. Bilateral masseter and anterior temporalis muscle EMG parameters were assessed in two standardized serial recordings (day 1 to day 2) using a portable EMG equipment (ME 6000 recorder, Mega Electronics, Kuopio, Finland). The functional tasks included postural/resting activities as pre- and post-recording series of 30 s each and jaw opening/closing, intercuspal and maximal voluntary clenching activities of 5 s, repeated three times. The assessed EMG parameters included the mean amplitude, s.d. and error. In addition, the power spectrum EMG parameter assessment included the median power frequencies and the averaged EMG spectrum data values. The results of the intraclass correlation coefficient analysis indicated reliability for nearly all of the intercuspal and all clenching EMG amplitude and power spectrum parameters. This was complemented by the repeated measures anova and post hoc analyses that indicated non-significant differences between day 1 and 2 in task- and muscle-related analyses. Most variability was noted in postural and some in opening/closing tasks. In conclusion this study assessed the reliability, repeatability and limitations of postural and various dynamic masseter and temporalis EMG recordings for serial assessment.

  16. 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 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.

  17. Performances evaluation of textile electrodes for EMG remote measurements.

    Science.gov (United States)

    Sumner, B; Mancuso, C; Paradiso, R

    2013-01-01

    This work focus on the evaluation of textile electrodes for EMG signals acquisition. Signals have been acquired simultaneously from textile electrode and from gold standard electrodes, by using the same acquisition system; tests were done across subjects and with multiple trials to enable a more complete analysis. This research activity was done in the frame of the European Project Interaction, aiming at the development of a system for a continuous daily-life monitoring of the functional performance of stroke survivors in their physical interaction with the environment.

  18. Two degrees of freedom quasi-static EMG-force at the wrist using a minimum number of electrodes.

    Science.gov (United States)

    Clancy, Edward A; Martinez-Luna, Carlos; Wartenberg, Marek; Dai, Chenyun; Farrell, Todd R

    2017-06-01

    Surface electromyogram-controlled powered hand/wrist prostheses return partial upper-limb function to limb-absent persons. Typically, one degree of freedom (DoF) is controlled at a time, with mode switching between DoFs. Recent research has explored using large-channel EMG systems to provide simultaneous, independent and proportional (SIP) control of two joints-but such systems are not practical in current commercial prostheses. Thus, we investigated site selection of a minimum number of conventional EMG electrodes in an EMG-force task, targeting four sites for a two DoF controller. In a laboratory experiment with 10 able-bodied subjects and three limb-absent subjects, 16 electrodes were placed about the proximal forearm. Subjects produced 1-DoF and 2-DoF slowly force-varying contractions up to 30% maximum voluntary contraction (MVC). EMG standard deviation was related to forces via regularized regression. Backward stepwise selection was used to retain those progressively fewer electrodes that exhibited minimum error. For 1-DoF models using two retained electrodes (which mimics the current state of the art), subjects had average RMS errors of (depending on the DoF): 7.1-9.5% MVC for able-bodied and 13.7-17.1% MVC for limb-absent subjects. For 2-DoF models, subjects using four electrodes had errors on 1-DoF trials of 6.7-8.5% MVC for able-bodied and 11.9-14.0% MVC for limb-absent; and errors on 2-DoF trials of 9.9-11.2% MVC for able-bodied and 15.8-16.7% MVC for limb-absent subjects. For each model, retaining more electrodes did not statistically improve performance. The able-bodied results suggest that backward selection is a viable method for minimum error selection of as few as four electrode sites for these EMG-force tasks. Performance evaluation in a prosthesis control task is a necessary and logical next step for this site selection method. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. 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

  20. 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

  1. 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

  2. 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

  3. EMG-driven models of human-machine interaction in individuals wearing the H2 exoskeleton

    NARCIS (Netherlands)

    Durandau, Guillaume; Sartori, Massimo; Bortole, Magdo; Moreno, Juan C.; Pons, José L.; Farina, Dario

    2016-01-01

    EMG-driven modeling has been mostly used offline and on powerful desktop computers, limiting the application of this technique to neurorehabilitation settings. In this paper, we demonstrate the use of EMG-driven modeling in online (i.e. in real-time) running on a fully portable embedded system and

  4. 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.

  5. 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.

  6. The influence of mental fatigue on facial EMG activity during a simulated workday

    NARCIS (Netherlands)

    Veldhuizen, I.J.T.; Gaillard, A.W.K.; Vries, J. de

    2003-01-01

    The present study investigated whether facial EMG measures are sensitive to the effects of fatigue. EMG activity of the corrugator and frontalis muscles was recorded during and after a simulated workday. Fatigue was evaluated in four ways: (a) the building up of fatigue effects during the workday,

  7. 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.

  8. Respiratory muscle activity measured with a noninvasive EMG technique : technical aspects and reproducibility

    NARCIS (Netherlands)

    Maarsingh, EJW; Van Eykern, LA; Sprikkelman, AB; Hoekstra, MO; Van Aalderen, WMC

    A new method is being developed to investigate airway obstruction in young children by means of noninvasive electromyography (EMG) of diaphragmatic and intercostal muscles. The purpose of this study was to evaluate the reproducibility of the EMG measurements. Eleven adults, 39 school children (20

  9. THE EFFECT OF EARLY MOVEMENT RESTRICTION - AN EMG STUDY IN THE RAT

    NARCIS (Netherlands)

    WESTERGA, J; GRAMSBERGEN, A

    1993-01-01

    The effect of early immobilization upon the adult locomotor pattern was studied. One hindlimb of neonatal rats was immobilized during 20 days and the EMG pattern was studied 3-8 weeks after termination of movement restriction. All rats showed a fluent locomotion pattern at these ages, but the EMG

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

    DEFF Research Database (Denmark)

    Henneberg, Kaj-åge; R., Plonsey

    1993-01-01

    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...

  11. Hardware System for Real-Time EMG Signal Acquisition and Separation Processing during Electrical Stimulation.

    Science.gov (United States)

    Hsueh, Ya-Hsin; Yin, Chieh; Chen, Yan-Hong

    2015-09-01

    The study aimed to develop a real-time electromyography (EMG) signal acquiring and processing device that can acquire signal during electrical stimulation. Since electrical stimulation output can affect EMG signal acquisition, to integrate the two elements into one system, EMG signal transmitting and processing method has to be modified. The whole system was designed in a user-friendly and flexible manner. For EMG signal processing, the system applied Altera Field Programmable Gate Array (FPGA) as the core to instantly process real-time hybrid EMG signal and output the isolated signal in a highly efficient way. The system used the power spectral density to evaluate the accuracy of signal processing, and the cross correlation showed that the delay of real-time processing was only 250 μs.

  12. Surface Electromyographic Sensor for Human Motion Estimation Based on Arm Wrestling Robot

    Directory of Open Access Journals (Sweden)

    Zhen GAO

    2010-06-01

    Full Text Available In this paper, the surface electromyographic (EMG sensor is developed to acquire the EMG signals from the upper limb when the participants compete with the arm wrestling robot (AWR which is fabricated to play arm wrestling game with human on a table with pegs for entertainment and human motion modeling of upper limbs muscle. As the EMG signal is a measurement of the anatomical and physiological characteristic of the specific muscle, the macroscopical movement patterns of the human body can be classified and recognized. The high-frequency noises are eliminated effectively and the characteristics of EMG signals can be extracted through wavelet packet transformation. Auto-regressive model of EMG is conducted to effectively simulate the stochastic time sequences with a series of auto-regressive coefficients. The win/lose pattern is recognized by neural network based on extracted characteristics of surface EMG signal.

  13. EMG amplitude, fatigue threshold, and time to task failure: A meta-analysis.

    Science.gov (United States)

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

    2017-11-11

    Electromyographic (EMG) fatigue threshold (EMG FT ) is utilised as a correlate of critical power, torque, and force thresholds that establishes a theoretical exercise intensity-the power, torque, or force at which the rate of change of EMG amplitude (ΔEM¯G) is zero-below which neuromuscular fatigue is negligible and unpredictable. Recent studies demonstrating neuromuscular fatigue below critical thresholds raise questions about the construct validity of EMG FT . The purpose of this analysis is to evaluate the construct validity of EMGFT by aggregating ΔEM¯G and time to task failure (T lim ) data. Meta-analysis. Database search of MEDLINE, SPORTDiscus, Web of Science, and Cochrane (inception - September 2016) conducted using terms relevant to EMG and muscle fatigue. Inclusion criteria were studies reporting agonist muscle EMG amplitude data during constant force voluntary isometric contractions taken to task failure. Linear and nonlinear regression models were used to relate ΔEM¯G and T lim data extracted from included studies. Regression analyses included data from 837 healthy adults from 43 studies. Relationships between ΔEM¯G and T lim were strong in both nonlinear (R 2 =0.65) and linear (R 2 =0.82) models. ΔEM¯G at EMG FT was significantly nonzero overall and in 3 of 5 cohorts in the nonlinear model (pEMG FT lacks face validity as currently calculated; models for more precise EMG FT calculation are proposed. A new framework for prediction of task failure using EMG amplitude data alone is presented. The ΔEM¯G vs. Tlim relationship remains consistent across sexes and force vs. position tasks. Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  14. 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.

  15. EMG analysis of lumbar paraspinal muscles as a predictor of the risk of low-back pain

    OpenAIRE

    Heydari, Abbas; Nargol, Antoni V. F.; Jones, Anthony P. C.; Humphrey, Anthony R.; Greenough, Charles G.

    2010-01-01

    Studies of EMG power spectra have established associations between low-back pain (LBP) and median frequency (MF). This 2-year prospective study investigates the association of LBP with EMG variables over time. 120 health care workers underwent paraspinal EMG measurements and assessment of back pain disability. The EMG recordings were performed under isometric trunk extension at 2/3 maximum voluntary contraction and acquired from erector spinae muscles at the level of L4/L5. 108 (90%) subjects...

  16. Instrumentation for ENG and EMG recordings in FES systems.

    Science.gov (United States)

    Nikolić, Z M; Popović, D B; Stein, R B; Kenwell, Z

    1994-07-01

    An electronic circuit for analog processing of neural (electroneurogram or ENG) and muscular (electromyogram or EMG) signals in functional electrical stimulation (FES) systems is described in this paper. The basic circuit consists of a low-noise gated preamplifier, band-pass filter, amplifier, and a blanking circuit to minimize stimulation artifacts during electrical stimulation. This device was tested in chronic recordings using a triphasic cuff electrode for nerves and epimysial electrodes for muscles in the hind limbs of cats. The device was used for nerve recordings in the presence of electrical stimulation of muscles in the same leg. The recordings showed rejection of stimulation and muscle (M-wave) artifacts, while retaining the information of interest.

  17. AUTOMATED CLASSIFICATION OF LAND COVER USING LANDSAT 8 OLI SURFACE REFLECTANCE PRODUCT AND SPECTRAL PATTERN ANALYSIS CONCEPT - CASE STUDY IN HANOI, VIETNAM

    Directory of Open Access Journals (Sweden)

    D. Nguyen Dinh

    2016-06-01

    Full Text Available Recently USGS released provisional Landsat 8 Surface Reflectance product, which allows conducting land cover mapping over large composed of number of image scenes without necessity of atmospheric correction. In this study, the authors present a new concept for automated classification of land cover. This concept is based on spectral patterns analysis of reflected bands and can be automated using predefined classification rule set constituted of spectral pattern shape, total reflected radiance index (TRRI and ratios of spectral bands. Given a pixel vector B6 = {b1,b2,b3,b4,b5,b6} where b1, b2,...,b6 denote bands 2, 3, ...,7 of OLI sensor respectively. By using the pixel vector B6 we can construct spectral reflectance curve. Each spectral curve is featured by a shape, which can be described in simplified form of an analogue pattern, which is consisted of 15 digits of 0, 1 and 2 showing mutual relative position of spectral vertices. Value of comparison between band i and j is 2 if bj > bi, 1 if bj = bi and 0 if bj i. Simplified spectral pattern is defined by 15 digits as m1,2m1,3m1,4m1,5m1,6m2,3m2,4m2,5m2,6m3,4m3,5m3,6m4,5m4,6m5,6 where mi,j is result of comparison of reflectance between bi and bj and has values of 0, 1 and 2. After construction of SSP for each pixel in the input image, the original image will be decomposed to component images, which contain pixels with the same SRCS pattern. The decomposition can be written analytically by equation A = Σnk=1Ck where A stands for original image with 6 spectral bands, n is number of component images decomposed from A and Ck is component image. For this study, we use Landsat 8 OLI reflectance image LC81270452013352LGN00 and LC81270452015182LGN00. For the decomposition, we use only six reflective bands. Each land cover class is defined by SSP code, threshold values for TRRI and band ratios. Automated classification of land cover was realized with 8 classes: forest, shrub, grass, water, wetland

  18. 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…

  19. Differentiation and classification of bacteria using vancomycin functionalized silver nanorods array based surface-enhanced raman spectroscopy an chemometric analysis

    Science.gov (United States)

    The intrinsic surface-enhanced Raman scattering (SERS) was used for differentiating and classifying bacterial species with chemometric data analysis. Such differentiation has often been conducted with an insufficient sample population and strong interference from the food matrices. To address these ...

  20. 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.

  1. 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

  2. Muscle fiber conduction velocity and fractal dimension of EMG during fatiguing contraction of young and elderly active men.

    Science.gov (United States)

    Boccia, Gennaro; Dardanello, Davide; Beretta-Piccoli, Matteo; Cescon, Corrado; Coratella, Giuseppe; Rinaldo, Nicoletta; Barbero, Marco; Lanza, Massimo; Schena, Federico; Rainoldi, Alberto

    2016-01-01

    Over the past decade, linear and nonlinear surface electromyography (EMG) variables highlighting different components of fatigue have been developed. In this study, we tested fractal dimension (FD) and conduction velocity (CV) rate of changes as descriptors, respectively, of motor unit synchronization and peripheral manifestations of fatigue. Sixteen elderly (69  ±  4 years) and seventeen young (23  ±  2 years) physically active men (almost 3-5 h of physical activity per week) executed one knee extensor contraction at 70% of a maximal voluntary contraction for 30 s. Muscle fiber CV and FD were calculated from the multichannel surface EMG signal recorded from the vastus lateralis and medialis muscles. The main findings were that the two groups showed a similar rate of change of CV, whereas FD rate of change was higher in the young than in the elderly group. The trends were the same for both muscles. CV findings highlighted a non-different extent of peripheral manifestations of fatigue between groups. Nevertheless, FD rate of change was found to be steeper in the elderly than in the young, suggesting a greater increase in motor unit synchronization with ageing. These findings suggest that FD analysis could be used as a complementary variable providing further information on central mechanisms with respect to CV in fatiguing contractions.

  3. Text classification

    OpenAIRE

    Deveikis, Karolis

    2016-01-01

    This paper investigates the problem of text classification. The task of text classification is to assign a piece of text to one of several categories based on its content. Text classification is one of the tasks of natural language processing. Like the others, it is often solved using machine learning algorithms. There are many algorithms suitable for text classification. As a result, a problem of choice arises. In an effort to solve this problem, this paper analyzes various feature extractio...

  4. 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.

  5. 10 CFR 61.55 - Waste classification.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 2 2010-01-01 2010-01-01 false Waste classification. 61.55 Section 61.55 Energy NUCLEAR... 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...

  6. 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 (pmyofascial TMD (median=3.31 μV and mean=4.98 μV) than for control women (median=2.83 μV and mean=3.88 μV) with median activity in 72% of cases 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

  7. 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

  8. Analysis of sEMG signals using discrete wavelet transform for muscle fatigue detection

    Science.gov (United States)

    Flórez-Prias, L. A.; Contreras-Ortiz, S. H.

    2017-11-01

    The purpose of the present article is to characterize sEMG signals to determine muscular fatigue levels. To do this, the signal is decomposed using the discrete wavelet transform, which offers noise filtering features, simplicity and efficiency. sEMG signals on the forearm were acquired and analyzed during the execution of cyclic muscular contractions in the presence and absence of fatigue. When the muscle fatigues, the sEMG signal shows a more erratic behavior of the signal as more energy is required to maintain the effort levels.

  9. 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.

  10. Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

    Science.gov (United States)

    Bulea, Thomas C.; Kilicarslan, Atilla; Ozdemir, Recep; Paloski, William H.; Contreras-Vidal, Jose L.

    2013-01-01

    Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG. PMID:23912203

  11. Increasing Elbow Torque Output of Stroke Patients by EMG-Controlled External Torque

    National Research Council Canada - National Science Library

    Lin, C

    2001-01-01

    .... The control signal to the manipulator is the difference between the weighted biceps and triceps EMG, so that the system moves with the forearm and provides assisting torque proportional to the voluntary effort...

  12. Electrical stimulation of the upper extremity in stroke: cyclic versus EMG-triggered stimulation

    NARCIS (Netherlands)

    de Kroon, Joke R.; IJzerman, Maarten Joost

    2008-01-01

    Objective: To compare the effect of cyclic and electromyography (EMG)-triggered electrical stimulation on motor impairment and function of the affected upper extremity in chronic stroke. Design: Randomized controlled trial. Setting: Outpatient clinic of a rehabilitation centre. Subjects and

  13. Tremor Frequency Assessment by iPhone® Applications: Correlation with EMG Analysis.

    Science.gov (United States)

    Araújo, Rui; Tábuas-Pereira, Miguel; Almendra, Luciano; Ribeiro, Joana; Arenga, Marta; Negrão, Luis; Matos, Anabela; Morgadinho, Ana; Januário, Cristina

    2016-10-19

    Tremor frequency analysis is usually performed by EMG studies but accelerometers are progressively being more used. The iPhone® contains an accelerometer and many applications claim to be capable of measuring tremor frequency. We tested three applications in twenty-two patients with a diagnosis of PD, ET and Holmes' tremor. EMG needle assessment as well as accelerometry was performed at the same time. There was very strong correlation (Pearson >0.8, p < 0.001) between the three applications, the EMG needle and the accelerometry. Our data suggests the apps LiftPulse®, iSeismometer® and Studymytremor® are a reliable alternative to the EMG for tremor frequency assessment.

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

    DEFF Research Database (Denmark)

    Castrillon, Eduardo

    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......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...

  15. Sleep telemetry in the rat: I. a miniaturized FM--AM transmitter for EEG and EMG.

    Science.gov (United States)

    Ruedin, P; Bisang, J; Waser, P G; Borbely, A A

    1978-01-01

    The article describes a miniature 2-channel FM-AM transmitter for recording EEG and EMG in unrestrained, small animals. Field changes during head movements yield a signal which can serve as a measure of motor activity.

  16. Identification of a Hammerstein Model of the Stretch Reflex EMG using Cubic Splines

    National Research Council Canada - National Science Library

    Dempsey, Erika

    2001-01-01

    .... The identification algorithm based on a separable least squares Levenberg-Marquardt optimization is used to identify a Hammerstein model of the stretch reflex EMG recorded from a spinal cord injured patient...

  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. 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.

  19. 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

  20. 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.

  1. 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.

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

    Science.gov (United States)

    Gomez-Gil, Jaime; San-Jose-Gonzalez, Israel; Nicolas-Alonso, Luis Fernando; Alonso-Garcia, Sergio

    2011-01-01

    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. PMID:22164006

  3. 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.

  4. 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.

  5. Muscle fatigue detection in EMG using time-frequency methods, ICA and neural networks.

    Science.gov (United States)

    Subasi, Abdulhamit; Kiymik, M Kemal

    2010-08-01

    The electromyography (EMG) signals give information about different features of muscle function. Real-time measurements of EMG have been used to observe the dissociation between the electrical and mechanical measures that occurs with fatigue. The purpose of this study was to detect fatigue of biceps brachia muscle using time-frequency methods and independent component analysis (ICA). In order to realize this aim, EMG activity obtained from activated muscle during a phasic voluntary movement was recorded for 14 healthy young persons and EMG signals were observed in time-frequency domain for determination of fatigue. Time-frequency methods are used for the processing of signals that are non-stationary and time varying. The EMG contains transient signals related to muscle activity. The proposed method for the detection of muscle fatigue is automated by using artificial neural networks (ANN). The results show that ANN with ICA separates EMG signals from fresh and fatigued muscles, hence providing a visualization of the onset of fatigue over time. The system is adaptable to different subjects and conditions since the techniques used are not subject or workload regime specific.

  6. 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.

  7. 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.

  8. Reproducibility of 3D kinematics and surface electromyography measurements of mastication

    NARCIS (Netherlands)

    Remijn, L.; Groen, B.E.; Speyer, R.; Limbeek, J. van; Sanden, M.W. van der

    2016-01-01

    The aim of this study was to determine the measurement reproducibility for a procedure evaluating the mastication process and to estimate the smallest detectable differences of 3D kinematic and surface electromyography (sEMG) variables. Kinematics of mandible movements and sEMG activity of the

  9. 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.

  10. Learning to modulate the partial powers of a single sEMG power spectrum through a novel human-computer interface.

    Science.gov (United States)

    Skavhaug, Ida-Maria; Lyons, Kenneth R; Nemchuk, Anna; Muroff, Shira D; Joshi, Sanjay S

    2016-06-01

    New human-computer interfaces that use bioelectrical signals as input are allowing study of the flexibility of the human neuromuscular system. We have developed a myoelectric human-computer interface which enables users to navigate a cursor to targets through manipulations of partial powers within a single surface electromyography (sEMG) signal. Users obtain two-dimensional control through simultaneous adjustments of powers in two frequency bands within the sEMG spectrum, creating power profiles corresponding to cursor positions. It is unlikely that these types of bioelectrical manipulations are required during routine muscle contractions. Here, we formally establish the neuromuscular ability to voluntarily modulate single-site sEMG power profiles in a group of naïve subjects under restricted and controlled conditions using a wrist muscle. All subjects used the same pre-selected frequency bands for control and underwent the same training, allowing a description of the average learning progress throughout eight sessions. We show that subjects steadily increased target hit rates from 48% to 71% and exhibited greater control of the cursor's trajectories following practice. Our results point towards an adaptable neuromuscular skill, which may allow humans to utilize single muscle sites as limited general-purpose signal generators. Ultimately, the goal is to translate this neuromuscular ability to practical interfaces for the disabled by using a spared muscle to control external machines. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. 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.

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

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    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.

  13. Heart rate variability and surface electromyography of trained cyclists at different cadences

    Directory of Open Access Journals (Sweden)

    Bruno Saraiva

    2016-06-01

    Full Text Available The heart rate variability (HRV and surface electromyography (sEMG are important tools in the evaluation of cardiac autonomic system and neuromuscular parameters, respectively. The aim of the study was to evaluate the behavior of HRV and sEMG of the vastus lateralis in two exercise protocols on a cycle ergometer at 60 and 80 rpm. Eight healthy men cyclists who have trained for at least two years were evaluated. Reduction was observed followed by stabilization of RMSSD and SDNN indices of HRV (p<0.05 along with increases in the amplitude of the sEMG signal (p<0.05 in both protocols. Significant correlations were observed between the responses of HRV and sEMG in the cadence of 60 rpm (RMSSD and sEMG: r = -0.42, p=0.03; SDNN and sEMG: r = -0.45, p=0.01 and 80 rpm (RMSSD and sEMG: r = -0.47, p=0.02; SDNN and sEMG: r = -0.49, p=0.01, yet no difference was observed for these variables between the two protocols. We concluded that the parasympathetic cardiac responses and sEMG are independent of cadences applied at the same power output.

  14. Low-amplitude craniofacial EMG power spectral density and 3D muscle reconstruction from MRI

    Directory of Open Access Journals (Sweden)

    Lukas Wiedemann

    2015-03-01

    Full Text Available Improving EEG signal interpretation, specificity, and sensitivity is a primary focus of many current investigations, and the successful application of EEG signal processing methods requires a detailed knowledge of both the topography and frequency spectra of low-amplitude, high-frequency craniofacial EMG. This information remains limited in clinical research, and as such, there is no known reliable technique for the removal of these artifacts from EEG data. The results presented herein outline a preliminary investigation of craniofacial EMG high-frequency spectra and 3D MRI segmentation that offers insight into the development of an anatomically-realistic model for characterizing these effects. The data presented highlights the potential for confounding signal contribution from around 60 to 200 Hz, when observed in frequency space, from both low and high-amplitude EMG signals. This range directly overlaps that of both low γ (30-50 Hz and high γ (50-80 Hz waves, as defined traditionally in standatrd EEG measurements, and mainly with waves presented in dense-array EEG recordings. Likewise, average EMG amplitude comparisons from each condition highlights the similarities in signal contribution of low-activity muscular movements and resting, control conditions. In addition to the FFT analysis performed, 3D segmentation and reconstruction of the craniofacial muscles whose EMG signals were measured was successful. This recapitulation of the relevant EMG morphology is a crucial first step in developing an anatomical model for the isolation and removal of confounding low-amplitude craniofacial EMG signals from EEG data. Such a model may be eventually applied in a clinical setting to ultimately help to extend the use of EEG in various clinical roles.

  15. Comparative Analysis of Wavelet-based Feature Extraction for Intramuscular EMG Signal Decomposition.

    Science.gov (United States)

    Ghofrani Jahromi, M; Parsaei, H; Zamani, A; Dehbozorgi, M

    2017-12-01

    Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impact on the performance of a decomposition system. EMG decomposition has been studied well and several systems were proposed, but feature extraction step has not been investigated in detail. Several EMG signals were generated using a physiologically-based EMG signal simulation algorithm. For each signal, the firing patterns of motor units (MUs) provided by the simulator were used to extract MUPs of each MU. For feature extraction, different wavelet families including Daubechies (db), Symlets, Coiflets, bi-orthogonal, reverse bi-orthogonal and discrete Meyer were investigated. Moreover, the possibility of reducing the dimensionality of MUP feature vector is explored in this work. The MUPs represented using wavelet-domain features are transformed into a new coordinate system using Principal Component Analysis (PCA). The features were evaluated regarding their capability in discriminating MUPs of individual MUs. Extensive studies on different mother wavelet functions revealed that db2, coif1, sym5, bior2.2, bior4.4, and rbior2.2 are the best ones in differentiating MUPs of different MUs. The best results were achieved at the 4th detail coefficient. Overall, rbior2.2 outperformed all wavelet functions studied; nevertheless for EMG signals composed of more than 12 MUPTs, syms5 wavelet function is the best function. Applying PCA slightly enhanced the results.

  16. Single-Trial EEG-EMG coherence analysis reveals muscle fatigue-related progressive alterations in corticomuscular coupling.

    Science.gov (United States)

    Siemionow, Vlodek; Sahgal, Vinod; Yue, Guang H

    2010-04-01

    Voluntary muscle fatigue is a progressive process. A recent study demonstrated muscle fatigue-induced weakening of functional corticomuscular coupling measured by coherence between the brain [electroencephalogram (EEG)] and muscle [electromyogram (EMG)] signals after a relatively long-duration muscle contraction. Comparing the EEG-EMG coherence before versus after fatigue or between data of two long-duration time blocks is not adequate to reveal the dynamic nature of the fatigue process. The purpose of this study was to address this issue by quantifying single-trial EEG-EMG coherence and EEG, EMG power based on wavelet transform. Eight healthy subjects performed 200 maximal intermittent handgrip contractions in a single session with handgrip force, EEG and EMG signals acquired simultaneously. The EEG and EMG data during each 2-s handgrip was subjected to single trial EEG-EMG wavelet energy spectrum and coherence computation. The EEG-EMG coherence and energy spectrum at beta (15 ~ 35 Hz) and gamma (35-50 Hz) frequency bands were statistically analyzed in 2-block (75 trials per block), 5-block (30 trials/block), and 10-block (15 trials/block) data settings. The energy of both the EEG and EMG signals decreased significantly with muscle fatigue. The EEG-EMG coherence had a significant reduction for the 2-block comparison. More detailed dynamical changing and inter-subject variation of the EEG-EMG coherence and energy were revealed by 5- and 10-block comparisons. These results show feasibility of wavelet transform-based measurement of the EEG-EMG coherence and corresponding energy based on single-trial data, which provides extra information to demonstrate a time course of dynamic adaptations of the functional corticomuscular coupling, as well as brain and muscle signals during muscle fatigue.

  17. 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.

  18. Comparison of EMG activity on abdominal muscles during plank exercise with unilateral and bilateral additional isometric hip adduction.

    Science.gov (United States)

    Kim, Soo-Yong; Kang, Min-Hyeok; Kim, Eui-Ryong; Jung, In-Gui; Seo, Eun-Young; Oh, Jae-Seop

    2016-10-01

    The aim of this study was to investigate the effects of additional isometric hip adduction during the plank exercise on the abdominal muscles. Twenty healthy young men participated in this study. Surface electromyography (EMG) was used to monitor the activity of the bilateral rectus abdominis (RA), the internal oblique (IO), and the external oblique (EO) muscles. The participants performed three types of plank exercise; the standard plank exercise, the plank exercise with bilateral isometric hip adduction, and the plank exercise with unilateral isometric hip adduction. All abdominal muscle activity was significantly increased during the plank exercise combined with the bilateral and unilateral isometric hip adduction compared with the standard plank exercise (pmuscle activity was significantly increased during the unilateral isometric hip adduction compared with the bilateral isometric hip adduction (pabdominal muscle activity. In particular, the unilateral isometric hip adduction is a more beneficial exercise than the bilateral isometric hip adduction. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. A modified multi-channel EMG feature for upper limb motion pattern recognition.

    Science.gov (United States)

    Tsai, An-Chih; Luh, Jer-Junn; Lin, Ta-Te

    2012-01-01

    The EMG signal is a well-known and useful biomedical signal. Much information related to muscles and human motions is included in EMG signals. Many approaches have proposed various methods that tried to recognize human motion via EMG signals. However, one of the critical problems of motion pattern recognition is that the performance of recognition is easily affected by the normalization procedure and may not work well on different days. In this paper, a modified feature of the multi-channel EMG signal is proposed and the normalization procedure is also simplified by using this modified feature. To recognize motion pattern, we applied the support vector machine (SVM) to build the motion pattern recognition model. In training and validation procedures, we used the 2-DoF exoskeleton robot arm system to do the designed pose, and the multi-channel EMG signals were obtained while the user resisted the robot. Experiment results indicate that the performance of applying the proposed feature (94.9%) is better than that of conventional features. Moreover, the performances of the recognition model, which applies the modified feature to recognize the motions on different days, are more stable than other conventional features.

  20. 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.

  1. 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.

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

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    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.

  3. Prediction of distal arm joint angles from EMG and shoulder orientation for prosthesis control.

    Science.gov (United States)

    Akhtar, Aadeel; Hargrove, Levi J; Bretl, Timothy

    2012-01-01

    Current state-of-the-art upper limb myoelectric prostheses are limited by only being able to control a single degree of freedom at a time. However, recent studies have separately shown that the joint angles corresponding to shoulder orientation and upper arm EMG can predict the joint angles corresponding to elbow flexion/extension and forearm pronation/ supination, which would allow for simultaneous control over both degrees of freedom. In this preliminary study, we show that the combination of both upper arm EMG and shoulder joint angles may predict the distal arm joint angles better than each set of inputs alone. Also, with the advent of surgical techniques like targeted muscle reinnervation, which allows a person with an amputation intuitive muscular control over his or her prosthetic, our results suggest that including a set of EMG electrodes around the forearm increases performance when compared to upper arm EMG and shoulder orientation. We used a Time-Delayed Adaptive Neural Network to predict distal arm joint angles. Our results show that our network's root mean square error (RMSE) decreases and coefficient of determination (R(2)) increases when combining both shoulder orientation and EMG as inputs.

  4. 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

  5. Achieving professional success in US government, academia, and industry: an EMGS commentary.

    Science.gov (United States)

    Poirier, Miriam C; Schwartz, Jeffrey L; Aardema, Marilyn J

    2014-08-01

    One of the goals of the EMGS is to help members achieve professional success in the fields they have trained in. Today, there is greater competition for jobs in genetic toxicology, genomics, and basic research than ever before. In addition, job security and the ability to advance in one's career is challenging, regardless of whether one works in a regulatory, academic, or industry environment. At the EMGS Annual Meeting in Monterey, CA (September, 2013), the Women in EMGS Special Interest Group held a workshop to discuss strategies for achieving professional success. Presentations were given by three speakers, each representing a different employment environment: Government (Miriam C. Poirier), Academia (Jeffrey L. Schwartz), and Industry (Marilyn J. Aardema). Although some differences in factors or traits affecting success in the three employment sectors were noted by each of the speakers, common factors considered important for advancement included networking, seeking out mentors, and developing exceptional communication skills. © 2014 Wiley Periodicals, Inc.

  6. EMG parameters and EEG α Index change at fatigue period during different types of muscle contraction

    Science.gov (United States)

    Zhang, Li; Zhou, Bin; Song, Gaoqing

    2011-03-01

    The purpose of this study is to measure and analyze the characteristics in change of EMG and EEG parameters at muscle fatigue period in participants with different exercise capacity. Twenty participants took part in the tests. They were divided into two groups, Group A (constant exerciser) and Group B (seldom-exerciser). MVC dynamic and 1/3 isometric exercises were performed; EMG and EEG signals were recorded synchronously during different type of muscle contraction. Results indicated that values of MVC, RMS and IEMG in Group A were greater than Group B, but isometric exercise time was shorter than the time of dynamic exercise although its intensity was light. Turning point of IEMG and α Index occurred synchronously during constant muscle contraction of isometric or dynamic exercise. It is concluded that IEMG turning point may be an indication to justify muscle fatigue. Synchronization of EEG and EMG reflects its common characteristics on its bio-electric change.

  7. Task discrimination from myoelectric activity: a learning scheme for EMG-based interfaces.

    Science.gov (United States)

    Liarokapis, Minas V; Artemiadis, Panagiotis K; Kyriakopoulos, Kostas J

    2013-06-01

    A learning scheme based on Random Forests is used to discriminate the task to be executed using only myoelectric activity from the upper limb. Three different task features can be discriminated: subspace to move towards, object to be grasped and task to be executed (with the object). The discrimination between the different reach to grasp movements is accomplished with a random forests classifier, which is able to perform efficient features selection, helping us to reduce the number of EMG channels required for task discrimination. The proposed scheme can take advantage of both a classifier and a regressor that cooperate advantageously to split the task space, providing better estimation accuracy with task-specific EMG-based motion decoding models, as reported in [1] and [2]. The whole learning scheme can be used by a series of EMG-based interfaces, that can be found in rehabilitation cases and neural prostheses.

  8. 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

    TITLE: Comparison of Jaw Muscle EMG Activity in Awake and Sleep Bruxers AUTHORS: E. E. Castrillon, P. Dreyer, M. Haugland, W. Yachida, T. Arima, P. Svensson AUTHORS/INSTITUTIONS: E.E. Castrillon, P. Dreyer, P. Svensson, Aarhus School of Dentistry, Aarhus C, DENMARK; E.E. Castrillon, P. Svensson, ...... of the jaw muscle activity in different populations of self-reported bruxers and non-bruxers. Financial Interest Disclosure: Morten Haughland works for DELTA A/S that has commercial agreement with SUNSTAR that produces Grindcare (portable EMG device)...... 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...

  9. 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.

  10. Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction: a review.

    Science.gov (United States)

    Quitadamo, L R; Cavrini, F; Sbernini, L; Riillo, F; Bianchi, L; Seri, S; Saggio, G

    2017-02-01

    Support vector machines (SVMs) are widely used classifiers for detecting physiological patterns in human-computer interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the applications of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.

  11. Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction: a review

    Science.gov (United States)

    Quitadamo, L. R.; Cavrini, F.; Sbernini, L.; Riillo, F.; Bianchi, L.; Seri, S.; Saggio, G.

    2017-02-01

    Support vector machines (SVMs) are widely used classifiers for detecting physiological patterns in human-computer interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the applications of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.

  12. A Novel EMG Interface for Individuals With Tetraplegia to Pilot Robot Hand Grasping.

    Science.gov (United States)

    Tigra, Wafa; Navarro, Benjamin; Cherubini, Andrea; Gorron, X; Gelis, Anthony; Fattal, Charles; Guiraud, David; Azevedo Coste, Christine

    2018-02-01

    This paper introduces a new human-machine interface for individuals with tetraplegia. We investigated the feasibility of piloting an assistive device by processing supra-lesional muscle responses online. The ability to voluntarily contract a set of selected muscles was assessed in five spinal cord-injured subjects through electromyographic (EMG) analysis. Two subjects were also asked to use the EMG interface to control palmar and lateral grasping of a robot hand. The use of different muscles and control modalities was also assessed. These preliminary results open the way to new interface solutions for high-level spinal cord-injured patients.

  13. 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 signals...... for myoelectric control. A sleeve covering the upper and lower arm, which contains 100 electrodes arranged in four grids of 5 * 5 electrodes, was used to record EMG signals in 3 subjects during the execution of 9 tasks of the wrist and hand. The signals were analyzed by extracting wavelet coefficients which were...

  14. 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...

  15. 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. M...

  16. Compensation of the effects of muscle fatigue on EMG-based control using fuzzy rules based scheme.

    Science.gov (United States)

    Lalitharatne, Thilina Dulantha; Hayashi, Yoshiaki; Teramoto, Kenbu; Kiguchi, Kazuo

    2013-01-01

    Estimation of the correct motion intention of the user is very important for most of the Electromyography (EMG) based control applications such as prosthetics, power-assist exoskeletons, rehabilitation and teleoperation robots. On the other hand, safety and long term reliability are also vital for those applications, as they interact with human users. By considering these requirements, many EMG-based control applications have been proposed and developed. However, there are still many challenges to be addressed in the case of EMG based control systems. One of the challenges that had not been considered in such EMG-based control in common is the muscle fatigue. The muscle fatiguing effects of the user can deteriorate the effectiveness of the EMG-based control in the long run, which makes the EMG-based control to produce less accurate results. Therefore, in this study we attempted to develop a fuzzy rule based scheme to compensate the effects of muscle fatigues on EMG based control. Fuzzy rule based weights have been estimated based on time and frequency domain features of the EMG signals. Eventually, these weights have been used to modify the controller output according with the muscle fatigue condition in the muscles. The effectiveness of the proposed method has been evaluated by experiments.

  17. 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

  18. Synergy of EMG patterns in gait as an objective measure of muscle selectivity in children with spastic cerebral palsy

    NARCIS (Netherlands)

    Zwaan, E.; Becher, J.G.; Harlaar, J.

    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

  19. Comparison of EMG during passive stretching and shortening phases of each muscle for the investigation of parkinsonian rigidity.

    Science.gov (United States)

    Kwon, Yuri; Kim, Ji-Won; Kim, Ji-Sun; Koh, Seong-Beom; Eom, Gwang-Moon; Lim, Tae-Hong

    2015-01-01

    The aim of this study was to test the hypothesis in the literature that torque resistance of parkinsonian rigidity is the difference between the independent contributions of stretched and shortened muscles. The hypothesis was tested using muscle-specific stretch-shortening (MSSS) EMG ratio in this study. Nineteen patients with idiopathic Parkinson's disease (PD) and 18 healthy subjects (the mean age comparable to that of patients) participated in this study. The EMG activity was measured in the four muscles involved in wrist joint movement, i.e. flexor carpi radialis, flexor carpi ulnaris, extensor carpi radialis and extensor carpi ulnaris. The passive flexion-extension movement with a range of ±30∘ was applied at wrist joint. Root mean squared (RMS) mean was calculated from the envelope of the EMG for each of stretching and shortening phases. MSSS EMG ratio was defined as the ratio of RMS EMG of stretching phase and RMS EMG of shortening phase of a single muscle, and it was calculated for each muscle. MSSS EMG ratios were smaller than one in all muscles. These results indicate that all wrist muscles generate greater mean EMG during shortening than during stretching. Therefore, the torque resistance of parkinsonian rigidity cannot be explained as the simple summation of independent antagonistic torque pair.

  20. Effect of EMG-triggered stimulation combined with comprehensive rehabilitation training on muscle tension in poststroke hemiparetic patients.

    Science.gov (United States)

    Xu, H; Jie, J; Hailiang, Z; Ma, C

    2015-11-01

    The aim of this study was to investigate the effect of electromyography stimulation (EMGS) combined with comprehensive rehabilitation training on muscle tension of paretic limb in poststroke hemiparetic patients. Forty poststroke hemiparetic patients were randomly divided into 2 groups (N.=20 each): control group that received conventional therapy and experimental group that underwent EMGS combined with comprehensive rehabilitation training in addition to conventional therapy. The outcome was assessed by Fugl-Meyer Score, functional ambulation category (FAC) Scale and integrated electromyography (iEMG) for both pretreatment and post-treatment. The results were analyzed using paired t-test and group t-test. No statistical significance was observed for Fugl-Meyer Score, FAC Score and iEMG values between control and experimental groups prior to the treatment (P>0.05). However, Fugl-Meyer and FAC scores were improved and iEMG values of gastrocnemius muscle were significantly decreased (PFugl-Meyer Score, FAC score and iEMG values (PFugl-Meyer and FAC scores. EMGS combined with comprehensive rehabilitation training can synergistically reduce muscle tension and relieve muscular spasticity of paretic limb in post-stroke patients. The iEMG proved to be a potential candidate for the evaluation of motor function in these patients.

  1. 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.

  2. Spontaneous mechanical and electrical activities of human calf musculature at rest assessed by repetitive single-shot diffusion-weighted MRI and simultaneous surface electromyography.

    Science.gov (United States)

    Schwartz, Martin; Steidle, Günter; Martirosian, Petros; Ramos-Murguialday, Ander; Preißl, Hubert; Stemmer, Alto; Yang, Bin; Schick, Fritz

    2018-05-01

    Assessment of temporal and spatial relations between spontaneous mechanical activities in musculature (SMAM) at rest as revealed by diffusion-weighted imaging (DWI) and electrical muscular activities in surface EMG (sEMG). Potential influences of static and radiofrequency magnetic fields on muscular activity on sEMG measurements at rest were examined systematically. Series of diffusion-weighted stimulated echo planar imaging were recorded with concurrent sEMG measurements. Electrical activities in sEMG were analyzed by non-parametric Friedman and two-sample Kolmogorov-Smirnov test. Direct correlation of both modalities was investigated by temporal mapping of electrical activity in sEMG to DWI repetition interval. Electrical activities in sEMG and number of visible SMAMs in DWI showed a strong correlation (ρ = 0.9718). High accordance between sEMG activities and visible SMAMs in DWI in a near-surface region around sEMG electrodes was achieved. Characteristics of sEMG activities were almost similar under varying magnetic field conditions. Visible SMAMs in DWI have shown a close and direct relation to concurrent signals recorded by sEMG. MR-related magnetic fields had no significant effects on findings in sEMG. Hence, appearance of SMAMs in DWI should not be considered as imaging artifact or as effects originating from the special conditions of MR examinations. Spatial and temporal distributions of SMAMs indicate characteristics of spontaneous (microscopic) mechanical muscular action at rest. Therefore, DWI techniques should be considered as non-invasive tools for studying physiology and pathophysiology of spontaneous activities in resting muscle. Magn Reson Med 79:2784-2794, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  3. Xenolog classification.

    Science.gov (United States)

    Darby, Charlotte A; Stolzer, Maureen; Ropp, Patrick J; Barker, Daniel; Durand, Dannie

    2017-03-01

    Orthology analysis is a fundamental tool in comparative genomics. Sophisticated methods have been developed to distinguish between orthologs and paralogs and to classify paralogs into subtypes depending on the duplication mechanism and timing, relative to speciation. However, no comparable framework exists for xenologs: gene pairs whose history, since their divergence, includes a horizontal transfer. Further, the diversity of gene pairs that meet this broad definition calls for classification of xenologs with similar properties into subtypes. We present a xenolog classification that uses phylogenetic reconciliation to assign each pair of genes to a class based on the event responsible for their divergence and the historical association between genes and species. Our classes distinguish between genes related through transfer alone and genes related through duplication and transfer. Further, they separate closely-related genes in distantly-related species from distantly-related genes in closely-related species. We present formal rules that assign gene pairs to specific xenolog classes, given a reconciled gene tree with an arbitrary number of duplications and transfers. These xenology classification rules have been implemented in software and tested on a collection of ∼13 000 prokaryotic gene families. In addition, we present a case study demonstrating the connection between xenolog classification and gene function prediction. The xenolog classification rules have been implemented in N otung 2.9, a freely available phylogenetic reconciliation software package. http://www.cs.cmu.edu/~durand/Notung . Gene trees are available at http://dx.doi.org/10.7488/ds/1503 . durand@cmu.edu. Supplementary data are available at Bioinformatics online.

  4. 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.

  5. A study of ureteric peristalsis using a single catheter to record EMG, impedance, and pressure changes

    NARCIS (Netherlands)

    Roshani, H.; Dabhoiwala, N. F.; tee, S.; Dijkhuis, T.; Kurth, K. H.; Ongerboer de Visser, B. W.; de Jong, J. M.; Lamers, W. H.

    1999-01-01

    Ureteric peristalsis transports a urinary bolus from the renal pelvis to the bladder. We developed an intraluminal catheter with a pressure transducer on it to study intraluminal pressure changes and a twin bipolar electrode to record the ureteric EMG and impedance (Z) changes during a peristaltic

  6. Detection of the onset of gait initiation using kinematic sensors and EMG in transfemoral amputees

    NARCIS (Netherlands)

    Wentink, E.C.; Schut, V.G.H.; Prinsen, E.C.; Prinsen, Erik Christiaan; Rietman, Johan Swanik; Veltink, Petrus H.

    In this study we determined if detection of the onset of gait initiation in transfemoral amputees can be useful for voluntary control of upper leg prostheses. From six transfemoral amputees inertial sensor data and EMG were measured at the prosthetic leg during gait initiation. First, initial

  7. 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.

  8. Control of Leg Movements Driven by EMG Activity of Shoulder Muscles

    Science.gov (United States)

    La Scaleia, Valentina; Sylos-Labini, Francesca; Hoellinger, Thomas; Wang, Letian; Cheron, Guy; Lacquaniti, Francesco; Ivanenko, Yuri P.

    2014-01-01

    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 co-ordination 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 over-ground 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. PMID:25368569

  9. Macro EMG follow-up study in post-poliomyelitis patients

    NARCIS (Netherlands)

    Ivanyi, B.; Ongerboer de Visser, B. W.; Nelemans, P. J.; de Visser, M.

    1994-01-01

    We investigated the muscle strength and motor unit (MU) territory of five patients with postpolio syndrome (PPS), six stable patients with prior poliomyelitis, and five healthy volunteers. The MU territory was assessed by measuring amplitudes of motor unit potentials (MUPs) recorded by the macro EMG

  10. Sammenligning af to 3D-ganganalysesystemer – understøttet af EMG

    DEFF Research Database (Denmark)

    Koblauch, Henrik; Heilskov-Hansen, Thomas

    2010-01-01

    forsøges ændringer i moment forklaret ved hjælpaf elektromyografi (EMG).Metode10 raske unge mænd (alder 29,7 år, range 25-32) deltog i forsøget. Refleksmarkører svarende tilde to ovennævnte modeller blev påsat, hvorpå forsøgspersonen foretog 12 gennemgange med 7forskellige gangarter. EMG og gangsekvenser...... blev optaget af et VICON-MX-system(OxfordMetrics, Limited, Oxford, England). Data for Helen Hayes-modellen blev analyseret i VICONprogrammetNexus. Vaughan-modellen blev analyseret i et speciallavet MATLAB-program. Datafor de to modeller blev statistisk bearbejdet ved hjælp af en mixed model. EMG data...... forløb. De største forskelle, modellerne imellem, er fundet ianklens sagittalplan og knæets frontalplan. Disse forskelle synes at aftage, jo mere proximaltbeliggende leddet er. Sekundært blev det undersøgt, hvorledes de enkelte gangarter adskilte sigfra hinanden i henholdsvis momenter, vinkler og EMG...

  11. A new technique for simultaneously recording EMG and movements in experimental animals

    NARCIS (Netherlands)

    van Eykern, LA; Geisler, HC; Gramsbergen, A

    In this protocol a new system is presented fur recording EMG signals from leg and trunk muscles along with video-recording of leg and trunk movements. The system comprises a front-end amplifier consisting of a reference amplifier, a differential amplifier with a filter combination and an analog to

  12. 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.

  13. Effects of using dynamic office chairs on posture and EMG in standardized office tasks

    NARCIS (Netherlands)

    Ellegast, R.; Hamburger, R.; Keller, K.; Krause, F.; Groenesteijn, L.; Vink, P.; Berger, H.

    2007-01-01

    In the paper a measuring system for the comparative posture and EMG analysis of office chairs is presented. With the system four specific dynamic office chairs that promote dynamic sitting and therefore aim to prevent musculoskeletal disorders (MSD), were analyzed in comparison to a reference chair

  14. Statistical processing of facial electromyography (EMG) signals in emotional film scenes

    NARCIS (Netherlands)

    Westerink, Joyce; van den Broek, Egon; van Herk, Jan; Tuinenbreijer, Kees; Schut, Marleen

    To improve human-computer interaction, computers need to recognize and respond properly to their users’ emotional state. As a first step to such systems, we investigated how emotional experiences are expressed in various statistical parameters of facial EMG signals. 22 Subjects were presented with 8

  15. Calibration of EMG to force for knee muscles is applicable with submaximal voluntary contractions

    NARCIS (Netherlands)

    Doorenbosch, C.A.M.; Joosten, A.; Harlaar, J.

    2005-01-01

    Purpose: In this study, the influence of using submaximal isokinetic contractions about the knee compared to maximal voluntary contractions as input to obtain the calibration of an EMG-force model for knee muscles is investigated. Methods: Isokinetic knee flexion and extension contractions were

  16. Toward attenuating the impact of arm positions on electromyography pattern-recognition based motion classification in transradial amputees

    Science.gov (United States)

    2012-01-01

    Background Electromyography (EMG) pattern-recognition based control strategies for multifunctional myoelectric prosthesis systems have been studied commonly in a controlled laboratory setting. Before these myoelectric prosthesis systems are clinically viable, it will be necessary to assess the effect of some disparities between the ideal laboratory setting and practical use on the control performance. One important obstacle is the impact of arm position variation that causes the changes of EMG pattern when performing identical motions in different arm positions. This study aimed to investigate the impacts of arm position variation on EMG pattern-recognition based motion classification in upper-limb amputees and the solutions for reducing these impacts. Methods With five unilateral transradial (TR) amputees, the EMG signals and tri-axial accelerometer mechanomyography (ACC-MMG) signals were simultaneously collected from both amputated and intact arms when performing six classes of arm and hand movements in each of five arm positions that were considered in the study. The effect of the arm position changes was estimated in terms of motion classification error and compared between amputated and intact arms. Then the performance of three proposed methods in attenuating the impact of arm positions was evaluated. Results With EMG signals, the average intra-position and inter-position classification errors across all five arm positions and five subjects were around 7.3% and 29.9% from amputated arms, respectively, about 1.0% and 10% low in comparison with those from intact arms. While ACC-MMG signals could yield a similar intra-position classification error (9.9%) as EMG, they had much higher inter-position classification error with an average value of 81.1% over the arm positions and the subjects. When the EMG data from all five arm positions were involved in the training set, the average classification error reached a value of around 10.8% for amputated arms. Using a

  17. Toward attenuating the impact of arm positions on electromyography pattern-recognition based motion classification in transradial amputees.

    Science.gov (United States)

    Geng, Yanjuan; Zhou, Ping; Li, Guanglin

    2012-10-05

    Electromyography (EMG) pattern-recognition based control strategies for multifunctional myoelectric prosthesis systems have been studied commonly in a controlled laboratory setting. Before these myoelectric prosthesis systems are clinically viable, it will be necessary to assess the effect of some disparities between the ideal laboratory setting and practical use on the control performance. One important obstacle is the impact of arm position variation that causes the changes of EMG pattern when performing identical motions in different arm positions. This study aimed to investigate the impacts of arm position variation on EMG pattern-recognition based motion classification in upper-limb amputees and the solutions for reducing these impacts. With five unilateral transradial (TR) amputees, the EMG signals and tri-axial accelerometer mechanomyography (ACC-MMG) signals were simultaneously collected from both amputated and intact arms when performing six classes of arm and hand movements in each of five arm positions that were considered in the study. The effect of the arm position changes was estimated in terms of motion classification error and compared between amputated and intact arms. Then the performance of three proposed methods in attenuating the impact of arm positions was evaluated. With EMG signals, the average intra-position and inter-position classification errors across all five arm positions and five subjects were around 7.3% and 29.9% from amputated arms, respectively, about 1.0% and 10% low in comparison with those from intact arms. While ACC-MMG signals could yield a similar intra-position classification error (9.9%) as EMG, they had much higher inter-position classification error with an average value of 81.1% over the arm positions and the subjects. When the EMG data from all five arm positions were involved in the training set, the average classification error reached a value of around 10.8% for amputated arms. Using a two-stage cascade classifier

  18. Toward attenuating the impact of arm positions on electromyography pattern-recognition based motion classification in transradial amputees

    Directory of Open Access Journals (Sweden)

    Geng Yanjuan

    2012-10-01

    Full Text Available Abstract Background Electromyography (EMG pattern-recognition based control strategies for multifunctional myoelectric prosthesis systems have been studied commonly in a controlled laboratory setting. Before these myoelectric prosthesis systems are clinically viable, it will be necessary to assess the effect of some disparities between the ideal laboratory setting and practical use on the control performance. One important obstacle is the impact of arm position variation that causes the changes of EMG pattern when performing identical motions in different arm positions. This study aimed to investigate the impacts of arm position variation on EMG pattern-recognition based motion classification in upper-limb amputees and the solutions for reducing these impacts. Methods With five unilateral transradial (TR amputees, the EMG signals and tri-axial accelerometer mechanomyography (ACC-MMG signals were simultaneously collected from both amputated and intact arms when performing six classes of arm and hand movements in each of five arm positions that were considered in the study. The effect of the arm position changes was estimated in terms of motion classification error and compared between amputated and intact arms. Then the performance of three proposed methods in attenuating the impact of arm positions was evaluated. Results With EMG signals, the average intra-position and inter-position classification errors across all five arm positions and five subjects were around 7.3% and 29.9% from amputated arms, respectively, about 1.0% and 10% low in comparison with those from intact arms. While ACC-MMG signals could yield a similar intra-position classification error (9.9% as EMG, they had much higher inter-position classification error with an average value of 81.1% over the arm positions and the subjects. When the EMG data from all five arm positions were involved in the training set, the average classification error reached a value of around 10.8% for

  19. 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)...

  20. Circadian force and EMG activity in hindlimb muscles of rhesus monkeys

    Science.gov (United States)

    Hodgson, J. A.; Wichayanuparp, S.; Recktenwald, M. R.; Roy, R. R.; McCall, G.; Day, M. K.; Washburn, D.; Fanton, J. W.; Kozlovskaya, I.; Edgerton, V. R.; hide

    2001-01-01

    Continuous intramuscular electromyograms (EMGs) were recorded from the soleus (Sol), medial gastrocnemius (MG), tibialis anterior (TA), and vastus lateralis (VL) muscles of Rhesus during normal cage activity throughout 24-h periods and also during treadmill locomotion. Daily levels of MG tendon force and EMG activity were obtained from five monkeys with partial datasets from three other animals. Activity levels correlated with the light-dark cycle with peak activities in most muscles occurring between 08:00 and 10:00. The lowest levels of activity generally occurred between 22:00 and 02:00. Daily EMG integrals ranged from 19 mV/s in one TA muscle to 3339 mV/s in one Sol muscle: average values were 1245 (Sol), 90 (MG), 65 (TA), and 209 (VL) mV/s. The average Sol EMG amplitude per 24-h period was 14 microV, compared with 246 microV for a short burst of locomotion. Mean EMG amplitudes for the Sol, MG, TA, and VL during active periods were 102, 18, 20, and 33 microV, respectively. EMG amplitudes that approximated recruitment of all fibers within a muscle occurred for 5-40 s/day in all muscles. The duration of daily activation was greatest in the Sol [151 +/- 45 (SE) min] and shortest in the TA (61 +/- 19 min). The results show that even a "postural" muscle such as the Sol was active for only approximately 9% of the day, whereas less active muscles were active for approximately 4% of the day. MG tendon forces were generally very low, consistent with the MG EMG data but occasionally reached levels close to estimates of the maximum force generating potential of the muscle. The Sol and TA activities were mutually exclusive, except at very low levels, suggesting very little coactivation of these antagonistic muscles. In contrast, the MG activity usually accompanied Sol activity suggesting that the MG was rarely used in the absence of Sol activation. The results clearly demonstrate a wide range of activation levels among muscles of the same animal as well as among different

  1. Quantitative analysis of surface electromyography during epileptic and nonepileptic convulsive seizures

    DEFF Research Database (Denmark)

    Beniczky, Sándor; Conradsen, Isa; Moldovan, Mihai

    2014-01-01

    Objective: To investigate the characteristics of sustained muscle activation during convulsive epileptic and psychogenic nonepileptic seizures (PNES), as compared to voluntary muscle activation. The main goal was to find surface electromyography (EMG) features that can distinguish between convuls...

  2. G-LOC Warning Algorithms Based on EMG Features of the Gastrocnemius Muscle.

    Science.gov (United States)

    Kim, Sungho; Cho, Taehwan; Lee, Yongkyun; Koo, Hyojin; Choi, Booyong; Kim, Dongsoo

    2017-08-01

    G-induced loss of consciousness (G-LOC) is mainly caused by failure to sustain an oxygenated blood supply to the pilot's brain because of the sudden acceleration in the direction of the +Gz axis, and is considered a critical safety issue. The purpose of this study was to develop G-LOC warning algorithms based on monitoring electromyograms (EMG) of the gastrocnemius muscle on the calf. EMG data was retrieved from a total of 67 pilots and pilot trainees of the Korean Air Force during high-G training on a human centrifugal simulator. Seven EMG features were obtained from root mean square (RMS), integrated absolute value (IAV), and mean absolute value (MAV) for muscle contraction, slope sign changes (SSC), waveform length (WL), zero crossing (ZC), and median frequency (MF) for muscle contraction and fatigue. Out of seven EMG features, IAV and WL showed a rapid decay before G-LOC. Based on these findings, this study developed two algorithms which can detect G-LOC during flight and provide warning signals to the pilots. The probability of G-LOC occurrence was detected through monitoring the decay trend for representing muscle endurance and climb rate of the IAV and WL value during sudden acceleration above 6 G, representing muscle power. The sensitivity of the algorithms using IAV and WL features was 100% and the specificity was 66.7%. This study suggests that a G-LOC detecting and warning system may be a customized, real-time countermeasure by improving the accuracy of detecting G-LOC.Kim S, Cho T, Lee Y, Koo H, Choi B, Kim D. G-LOC warning algorithms based on EMG features of the gastrocnemius muscle. Aerosp Med Hum Perform. 2017; 88(8):737-742.

  3. 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....... Although other methods exist, we concentrate on Bayesian modeling approaches, in which generative image models are constructed and subsequently ‘inverted’ to obtain automated segmentations. This general framework encompasses a large number of segmentation methods, including those implemented in widely used...

  4. Torque prediction using stimulus evoked EMG and its identification for different muscle fatigue states in SCI subjects.

    Science.gov (United States)

    Zhang, Qin; Hayashibe, Mitsuhiro; Papaiordanidou, Maria; Fraisse, Philippe; Fattal, Charles; Guiraud, David

    2010-01-01

    Muscle fatigue is an unavoidable problem when electrical stimulation is applied to paralyzed muscles. The detection and compensation of muscle fatigue is essential to avoid movement failure and achieve desired trajectory. This work aims to predict ankle plantar-flexion torque using stimulus evoked EMG (eEMG) during different muscle fatigue states. Five spinal cord injured patients were recruited for this study. An intermittent fatigue protocol was delivered to triceps surae muscle to induce muscle fatigue. A hammerstein model was used to capture the muscle contraction dynamics to represent eEMG-torque relationship. The prediction of ankle torque was based on measured eEMG and past measured or past predicted torque. The latter approach makes it possible to use eEMG as a synthetic force sensor when force measurement is not available in daily use. Some previous researches suggested to use eEMG information directly to detect and predict muscle force during fatigue assuming a fixed relationship between eEMG and generated force. However, we found that the prediction became less precise with the increase of muscle fatigue when fixed parameter model was used. Therefore, we carried out the torque prediction with an adaptive parameters using the latest measurement. The prediction of adapted model was improved with 16.7%-50.8% comparing to the fixed model.

  5. 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

  6. Surface EMG to assess arm function in boys with DMD: A pilot study

    NARCIS (Netherlands)

    Janssen, M.M.H.P.; Harlaar, J.; Groot, I.J.M. de

    2015-01-01

    INTRODUCTION: Preserving functional abilities of the upper extremities is a major concern in boys with Duchenne Muscular Dystrophy (DMD). To assess disease progression and treatments, good knowledge on arm function in boys with DMD is essential. Therefore, feasibility and validity of the use of

  7. Surface EMG to assess arm function in boys with DMD: A pilot study

    NARCIS (Netherlands)

    Janssen, M.M.H.P.; Harlaar, J.; de Groot, I.J.M.

    2015-01-01

    Introduction: Preserving functional abilities of the upper extremities is a major concern in boys with Duchenne Muscular Dystrophy (DMD). To assess disease progression and treatments, good knowledge on arm function in boys with DMD is essential. Therefore, feasibility and validity of the use of

  8. Surface EMG signals in very late-stage of Duchenne muscular dystrophy: a case study

    NARCIS (Netherlands)

    Lobo-Prat, J.; Janssen, M.M.H.P.; Koopman, B.; Stienen, A.H.A.; Groot, I.J.M. de

    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.

  9. 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

  10. 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.

  11. 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.

  12. 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  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.

  13. Motor unit action potential conduction velocity estimated from surface electromyographic signals using image processing techniques.

    Science.gov (United States)

    Soares, Fabiano Araujo; Carvalho, João Luiz Azevedo; Miosso, Cristiano Jacques; de Andrade, Marcelino Monteiro; da Rocha, Adson Ferreira

    2015-09-17

    In surface electromyography (surface EMG, or S-EMG), conduction velocity (CV) refers to the velocity at which the motor unit action potentials (MUAPs) propagate along the muscle fibers, during contractions. The CV is related to the type and diameter of the muscle fibers, ion concentration, pH, and firing rate of the motor units (MUs). The CV can be used in the evaluation of contractile properties of MUs, and of muscle fatigue. The most popular methods for CV estimation are those based on maximum likelihood estimation (MLE). This work proposes an algorithm for estimating CV from S-EMG signals, using digital image processing techniques. The proposed approach is demonstrated and evaluated, using both simulated and experimentally-acquired multichannel S-EMG signals. We show that the proposed algorithm is as precise and accurate as the MLE method in typical conditions of noise and CV. The proposed method is not susceptible to errors associated with MUAP propagation direction or inadequate initialization parameters, which are common with the MLE algorithm. Image processing -based approaches may be useful in S-EMG analysis to extract different physiological parameters from multichannel S-EMG signals. Other new methods based on image processing could also be developed to help solving other tasks in EMG analysis, such as estimation of the CV for individual MUs, localization and tracking of innervation zones, and study of MU recruitment strategies.

  14. Rhesus leg muscle EMG activity during a foot pedal pressing task on Bion 11

    Science.gov (United States)

    Hodgson, J. A.; Riazansky, S. N.; Goulet, C.; Badakva, A. M.; Kozlovskaya, I. B.; Recktenwald, M. R.; McCall, G.; Roy, R. R.; Fanton, J. W.; Edgerton, V. R.

    2000-01-01

    Rhesus monkeys (Macaca mulatta) were trained to perform a foot lever pressing task for a food reward. EMG activity was recorded from selected lower limb muscles of 2 animals before, during, and after a 14-day spaceflight and from 3 animals during a ground-based simulation of the flight. Integrated EMG activity was calculated for each muscle during the 20-min test. Comparisons were made between data recorded before any experimental manipulations and during flight or flight simulation. Spaceflight reduced soleus (Sol) activity to 25% of preflight levels, whereas it was reduced to 50% of control in the flight simulation. During flight, medial gastrocnemius (MG) activity was reduced to 25% of preflight activity, whereas the simulation group showed normal activity levels throughout all tests. The change in MG activity was apparent in the first inflight recording, suggesting that some effect of microgravity on MG activity was immediate.

  15. 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

    for oxygen saturation (StO(2)%) were initial slope at contraction onset, peak drop, and recovery slope at contraction end. Electromyography produced the root mean square to indicate muscle activation and mean power frequency changes over time (decreasing slope) to indicate fatigue development. For StO(2......Muscle oxygenation responses are reportedly greater in the distal muscle region than in the proximal muscle region. We combined near infrared spectroscopy and electromyography (EMG) to determine whether regional differences in oxygenation are associated with differences in (1) muscle activation and....../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...

  16. EMG burst presence probability: a joint time-frequency representation of muscle activity and its application to onset detection.

    Science.gov (United States)

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

    2015-04-13

    The purpose of this study was to quantify muscle activity in the time-frequency domain, therefore providing an alternative tool to measure muscle activity. This paper presents a novel method to measure muscle activity by utilizing EMG burst presence probability (EBPP) in the time-frequency domain. The EMG signal is grouped into several Mel-scale subbands, and the logarithmic power sequence is extracted from each subband. Each log-power sequence can be regarded as a dynamic process that transits between the states of EMG burst and non-burst. The hidden Markov model (HMM) was employed to elaborate this dynamic process since HMM is intrinsically advantageous in modeling the temporal correlation of EMG burst/non-burst presence. The EBPP was eventually yielded by HMM based on the criterion of maximum likelihood. Our approach achieved comparable performance with the Bonato method. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. 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.

  18. Reproducibility and responsiveness of a noninvasive EMG technique of the respiratory muscles in COPD patients and in healthy subjects

    NARCIS (Netherlands)

    Duiverman, ML; van Eykern, LA; Vennik, PW; Koeter, GH; Maarsingh, EJW; Wijkstra, PJ

    2004-01-01

    In the present study, we assessed the reproducibility and responsiveness of transcutaneous electromyography (EMG) of the respiratory muscles in patients with chronic obstructive pulmonary disease ( COPD) and healthy subjects during breathing against an inspiratory load. In seven healthy subjects and

  19. Number of sources uncertainty in blind source separation. Application to EMG signal processing.

    Science.gov (United States)

    Snoussi, Hichem; Khanna, Saurabh; Hewson, David; Duchene, Jacques

    2007-01-01

    This contribution deals with the number of components uncertainty in blind source separation. The number of components is estimated by maximizing its marginal a posteriori probability which favors the simplest explanation of the observed data. Marginalizing (integrating over all the parameters) is implemented through the Laplace approximation based on an efficient wavelet spectral matching separating algorithm. The effectiveness of the proposed method is shown on EMG data processing.

  20. EMG and strength in trunk and hip muscles : particular the iliopsoas

    OpenAIRE

    Andersson, Eva A.

    1997-01-01

    EMG AND STRENGTH IN TRUNK AND HIP MUSCLES - PARTICULARLY THE ILIOPSOAS Eva A. Andersson Dissertation from the Department of Neuroscience, Karolinska Institute, and the Department of Human Biology, University College of Physical Education and Sports, Box 5626, S-l 14 86, Stockholm, Sweden. . The overall aim of this thesis was to study the myoelectric activity of all major muscles involved in the movements and stabilization of the trunk, pelvis and hips ...

  1. Statistically significant contrasts between EMG waveforms revealed using wavelet-based functional ANOVA

    Science.gov (United States)

    McKay, J. Lucas; Welch, Torrence D. J.; Vidakovic, Brani

    2013-01-01

    We developed wavelet-based functional ANOVA (wfANOVA) as a novel approach for comparing neurophysiological signals that are functions of time. Temporal resolution is often sacrificed by analyzing such data in large time bins, increasing statistical power by reducing the number of comparisons. We performed ANOVA in the wavelet domain because differences between curves tend to be represented by a few temporally localized wavelets, which we transformed back to the time domain for visualization. We compared wfANOVA and ANOVA performed in the time domain (tANOVA) on both experimental electromyographic (EMG) signals from responses to perturbation during standing balance across changes in peak perturbation acceleration (3 levels) and velocity (4 levels) and on simulated data with known contrasts. In experimental EMG data, wfANOVA revealed the continuous shape and magnitude of significant differences over time without a priori selection of time bins. However, tANOVA revealed only the largest differences at discontinuous time points, resulting in features with later onsets and shorter durations than those identified using wfANOVA (P < 0.02). Furthermore, wfANOVA required significantly fewer (∼¼×; P < 0.015) significant F tests than tANOVA, resulting in post hoc tests with increased power. In simulated EMG data, wfANOVA identified known contrast curves with a high level of precision (r2 = 0.94 ± 0.08) and performed better than tANOVA across noise levels (P < <0.01). Therefore, wfANOVA may be useful for revealing differences in the shape and magnitude of neurophysiological signals (e.g., EMG, firing rates) across multiple conditions with both high temporal resolution and high statistical power. PMID:23100136

  2. Compression des signaux EMG par la Transformée dite « impaire ...

    African Journals Online (AJOL)

    Le problème étudié dans cet article est la compression de données des signaux ElectroMyographiques (EMG) par la Transformée dite « impaire ». Cette nouvelle méthode est la version du Lifting Scheme Modifié. La technique utilisée est celle d\\'un sous-échantillonnage des signaux d\\'indices pair et impair. La réduction ...

  3. 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.

  4. Tension-type headache: pain, fatigue, tension, and EMG responses to mental activation.

    Science.gov (United States)

    Bansevicius, D; Westgaard, R H; Sjaastad, O M

    1999-06-01

    Twenty patients with tension-type headache (14 chronic and 6 episodic) and 20 group-matched controls were selected for this study. They participated in a 1-hour, complex, two-choice, reaction-time test, as well as 5-minute pretest and 20-minute posttest periods. Subjects reported any pain in the forehead, temples, neck, and shoulders, as well as any feelings of fatigue and tension during the pretest, and every 10 minutes during the test and posttest by visual analog scales. Superficial electromyography was recorded simultaneously from positions representing the frontal and temporal muscles, neck (mostly splenius), and trapezius muscles. The location of pain corresponded to the position of the electrodes, but extended over a larger area. The test provoked pain in the forehead, neck, and shoulders of patients, i.e., pain scores from these regions increased significantly during the test. The pain scores continued to increase posttest. In patients, the EMG response of the trapezius (first 10 minutes of the test) was elevated relative to pretest. In controls, only the frontal muscles showed an EMG test response. Patients showed significantly higher EMG responses than controls in the neck (whole test period) and trapezius (first 10 minutes of the test period). There were significant differences in pain and fatigue scoring between patients and controls in all three periods and in tension scoring posttest. Fatigue correlated with pain, with increasing significance for all locations examined, while tension was mainly associated with the neck pain. The meaning of the variables "tension" and "fatigue" in headache, and their association with recorded muscle activity in various regions is discussed. The EMG response of the trapezius muscle to the test is discussed in comparison with similar responses observed in patients with other pain syndromes.

  5. 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.

  6. Spectral analysis of erector spinae EMG during intermittent isometric fatiguing exercise.

    Science.gov (United States)

    van Dieën, J H; Toussaint, H M; Thissen, C; van de Ven, A

    1993-04-01

    The applicability of EMG spectral analysis in the study of muscular fatigue of the erector spinae muscle was investigated. At three locations (L1, L2, L5) of the erector spinae muscle, representing different functional parts, EMG was sampled during fatiguing intermittent isometric extension of the trunk. The multifidus muscle (L5) appeared to show the most consistent changes of the EMG power spectrum as a consequence of fatigue. Whether the effects of the increase in muscle temperature on the power spectrum could be eliminated by low-pass filtering the data (60 Hz and 40 Hz) was also investigated. It was expected that this would make it possible to detect better the effects of fatigue on the firing characteristics of the motorunits by the inherent changes in the power spectrum. Low-pass filtering did not cause a more significant trend of the median frequency of the power spectrum. Future research will have to explore which parts of the power spectrum are affected by an increase of the muscle temperature.

  7. Predicting Blood Lactate Concentration and Oxygen Uptake from sEMG Data during Fatiguing Cycling Exercise

    Directory of Open Access Journals (Sweden)

    Petras Ražanskas

    2015-08-01

    Full Text Available This article presents a study of the relationship between electromyographic (EMG signals from vastus lateralis, rectus femoris, biceps femoris and semitendinosus muscles, collected during fatiguing cycling exercises, and other physiological measurements, such as blood lactate concentration and oxygen consumption. In contrast to the usual practice of picking one particular characteristic of the signal, e.g., the median or mean frequency, multiple variables were used to obtain a thorough characterization of EMG signals in the spectral domain. Based on these variables, linear and non-linear (random forest models were built to predict blood lactate concentration and oxygen consumption. The results showed that mean and median frequencies are sub-optimal choices for predicting these physiological quantities in dynamic exercises, as they did not exhibit significant changes over the course of our protocol and only weakly correlated with blood lactate concentration or oxygen uptake. Instead, the root mean square of the original signal and backward difference, as well as parameters describing the tails of the EMG power distribution were the most important variables for these models. Coefficients of determination ranging from R2 = 0:77 to R2 = 0:98 (for blood lactate and from R2 = 0:81 to R2 = 0:97 (for oxygen uptake were obtained when using random forest regressors.

  8. Different fatigue-resistant leg muscles and EMG response during whole-body vibration.

    Science.gov (United States)

    Simsek, Deniz

    2017-12-01

    The purpose of this study was to determine the effects of static whole-body vibration (WBV) on the Electromyograhic (EMG) responses of leg muscles, which are fatigue-resistant in different manner. The study population was divided into two groups according to the values obtained by the Fatigue Index [Group I: Less Fatigue Resistant (LFR), n=11; Group II: More Fatigue Resistant (MFR), n=11]. The repeated electromyographic (EMG) activities of four leg muscles were analyzed the following determinants: (1) frequency (30 Hz, 35 Hz and 40 Hz); (2) stance position (static squat position); (3) amplitude (2 mm and 4 mm) and (4) knee flexion angle (120°), (5) vertical vibration platform. Vibration data were analyzed using Minitab 16 (Minitab Ltd, State College, PA, USA). The significance level was set at pmuscle fatigue (pEMG activation at higher frequencies (max at 40 Hz) and amplitudes (4 mm) (p<.05). The present study can be used for the optimal prescription of vibration exercise and can serve to guide the development of training programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Predicting Blood Lactate Concentration and Oxygen Uptake from sEMG Data during Fatiguing Cycling Exercise.

    Science.gov (United States)

    Ražanskas, Petras; Verikas, Antanas; Olsson, Charlotte; Viberg, Per-Arne

    2015-08-19

    This article presents a study of the relationship between electromyographic (EMG) signals from vastus lateralis, rectus femoris, biceps femoris and semitendinosus muscles, collected during fatiguing cycling exercises, and other physiological measurements, such as blood lactate concentration and oxygen consumption. In contrast to the usual practice of picking one particular characteristic of the signal, e.g., the median or mean frequency, multiple variables were used to obtain a thorough characterization of EMG signals in the spectral domain. Based on these variables, linear and non-linear (random forest) models were built to predict blood lactate concentration and oxygen consumption. The results showed that mean and median frequencies are sub-optimal choices for predicting these physiological quantities in dynamic exercises, as they did not exhibit significant changes over the course of our protocol and only weakly correlated with blood lactate concentration or oxygen uptake. Instead, the root mean square of the original signal and backward difference, as well as parameters describing the tails of the EMG power distribution were the most important variables for these models. Coefficients of determination ranging from R(2) = 0:77 to R(2) = 0:98 (for blood lactate) and from R(2) = 0:81 to R(2) = 0:97 (for oxygen uptake) were obtained when using random forest regressors.

  10. 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.

  11. Relationship among the myelography, MRI and EMG in young patients with low back pain or radiating pain

    Energy Technology Data Exchange (ETDEWEB)

    Jang, Ji Youn [Soonchunhyang University Hospital, Seoul (Korea, Republic of); Kim, Dong Hun [Chosun University Hospital, Gwangju (Korea, Republic of); Park, Young Jae [Gwang-Ju City Geriatiric Hospital, Gwangju (Korea, Republic of)

    2006-06-15

    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 ({rho} = 0.298) and EMG findings ({rho} = 0.372). The EMG findings were not related to either the myelography findings ({rho} = 0.435) or the spinal geometric measurements ({rho} > 0.05) on MRI. Nerve root compression that was noted on myelography was related to the thecal sac AP diameter ({rho} = 0.016) and the width of the lateral recess ({rho} = 0.011). There were no correlations between myelography and the findings of root deviation on MRI ({rho} = 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.

  12. 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...

  13. Effect of EMG biofeedback training of gluteus maximus muscle on gait parameters in incomplete spinal cord injury.

    Science.gov (United States)

    Govil, Kanika; Noohu, Majumi M

    2013-01-01

    A Pretest -Posttest Experimental Design. Patients with incomplete spinal cord injury (ISCI) retain or regain the ability to walk, but due to limitations in gait parameters, walking may not be the practical method of mobility in the community. Specific muscle training plays an important role in gait training. The purpose of this study was to determine the effect of EMG Biofeedback training of gluteus maximus muscle on gait parameters in ISCI patients. Indian Spinal Injury Center, New Delhi, India. 30 incomplete spinal cord injured (ISCI) patients were included and randomly assigned to two groups. Group 1 received EMG Biofeedback (EMG BF), Traditional Rehabilitation and Gait Training. Group 2 received Traditional Rehabilitation and Gait Training. Gait parameters were measured prior to the intervention for all 30 ISCI patients. EMG Biofeedback was given specifically over gluteus maximus muscle along with traditional rehabilitation and gait training to Group 1 for 5 days/week for 4 weeks. Group 2 received traditional rehabilitation and gait training for 5 days/week for 4 weeks. The results were interpreted on the basis of: EMG amplitude, step length, walking velocity and cadence. Results showed significant difference between two groups for EMG amplitude (t = 6.06, p = 0.001), walking velocity (t = 2.12, p = 0.043), cadence (t = 1.96, p = 0.05). Step length did not show any significant difference (t = 0.66, p = 0.512). The study concluded that EMG BF when given specifically over gluteus maximus resulted in improvement of EMG amplitude and various gait parameters (walking velocity, cadence).

  14. 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.

  15. 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...

  16. Surface electromyography assessment of back muscle intrinsic properties.

    Science.gov (United States)

    Larivière, Christian; Arsenault, A Bertrand; Gravel, Denis; Gagnon, Denis; Loisel, Patrick

    2003-08-01

    The purpose of this study was to assess (1) the reliability and (2) the sensitivity to low back pain status and gender of different EMG indices developed for the assessment of back muscle weakness, muscle fiber composition and fatigability. Healthy subjects (men and women) and chronic low back pain patients (men only) performed, in a static dynamometer, maximal and submaximal static trunk extension tasks (short and long duration) to assess weakness, fiber composition and fatigue. Surface EMG signals were recorded from four (bilateral) pairs of back muscles and three pairs of abdominal muscles. To assess reliability of the different EMG parameters, 40 male volunteers (20 controls and 20 chronic low back pain patients) were assessed on three occasions. Reliable EMG indices were achieved for both healthy and chronic low back pain subjects when specific measurement strategies were applied. The EMG parameters used to quantify weakness and fiber composition were insensitive to low back status and gender. The EMG fatigue parameters did not detect differences between genders but unexpectedly, healthy men showed higher fatigability than back pain patients. This result was attributed to the smaller absolute load that was attributed to the patients, a load that was defined relative to their maximal strength, a problematic measure with this population. An attempt was made to predict maximal back strength from anthropometric measurements but this prediction was prone to errors. The main difficulties and some potential solutions related to the assessment of back muscle intrinsic properties were discussed.

  17. Standardization of surface electromyography utilized to evaluate patients with dysphagia

    Directory of Open Access Journals (Sweden)

    Vaiman Michael

    2007-06-01

    Full Text Available Abstract Backgorund Patients suspected of having swallowing disorders, could highly benefit from simple diagnostic screening before being referred to specialist evaluations. We introduce surface electromyography (sEMG to carry out rapid assessment of such patients and propose suggestions for standardizing sEMGs in order to identify abnormal deglutition. Methods Specifics steps for establishing standards for applying the technique for screening purposes (e.g., evaluation of specific muscles, the requirements for diagnostic sEMG equipment, the sEMG technique itself, and defining the tests suitable for assessing deglutition (e.g., saliva, normal, and excessive swallows and uninterrupted drinking of water are presented in detail. A previously described normative database for single swallowing and drinking and standard approach to analysis was compared to data on the duration and electric activity of muscles involved in deglutition and with sEMG recordings in order to estimate stages of a swallow. Conclusion SEMG of swallowing is a simple and reliable method for screening and preliminary differentiation among dysphagia and odynophagia of various origins. This noninvasive radiation-free examination has a low level of discomfort, and is simple, timesaving and inexpensive to perform. With standardization of the technique and an established normative database, sEMG can serve as a reliable screening method for optimal patient management.

  18. 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

  19. 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.

  20. 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....

  1. 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

  2. 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.

  3. Oynophagia in patients after dental extraction: surface electromyography study

    Directory of Open Access Journals (Sweden)

    Nahlieli Oded

    2006-10-01

    Full Text Available Abstract Objectives Surface electromyographic (sEMG studies were performed on 40 adult patients following extraction of lower third and second molars to research the approach and limitations of sEMG evaluation of their odynophagia complaints. Methods Parameters evaluated during swallowing and drinking include the timing, number of swallows per 100 cc of water, and range (amplitude of EMG activity of m. masseter, infrahyoid and submental-submandibular group. The above mentioned variables (mean + standard deviation were measured for the group of dental patients (n = 40 and control group of healthy adults (n = 40. Results The duration of swallows and drinking in all tests showed increase in dental patients' group, in which this tendency is statistically significant. There was no statistically significant difference between male and female adults' duration and amplitude of muscle activity during continuous drinking in both groups (p = 0.05. The mean of electric activity (in μV of m. masseter was significantly lower in the dental patients' group in comparison with control group. The electric activity of submental-submandimular and infrahyoid muscle groups was the same in both groups. Conclusion Surface EMG of swallowing is a simple and reliable noninvasive method for evaluation of odynophagia/dysphagia complaints following dental extraction with low level of discomfort of the examination. The surface EMG studies prove that dysphagia following dental extraction and molar surgery has oral origin, does not affect pharingeal segment and submental-submandibular muscle group. This type of dysphagia has clear EMG signs: increased duration of single swallow, longer drinking time, low range of electric activity of m. masseter, normal range of activity of submental-submandibular muscle group, and the "dry swalow" aftereffect. The data can be used for evaluation of complaints and symptoms, as well as for comparison purposes in pre- and postoperative stages and

  4. 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

  5. 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

  6. 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.

  7. An EMG-driven biomechanical model that accounts for the decrease in moment generation capacity during a dynamic fatigued condition.

    Science.gov (United States)

    Rao, Guillaume; Berton, Eric; Amarantini, David; Vigouroux, Laurent; Buchanan, Thomas S

    2010-07-01

    Although it is well known that fatigue can greatly reduce muscle forces, it is not generally included in biomechanical models. The aim of the present study was to develop an electromyographic-driven (EMG-driven) biomechanical model to estimate the contributions of flexor and extensor muscle groups to the net joint moment during a nonisokinetic functional movement (squat exercise) performed in nonfatigued and in fatigued conditions. A methodology that aims at balancing the decreased muscle moment production capacity following fatigue was developed. During an isometric fatigue session, a linear regression was created linking the decrease in force production capacity of the muscle (normalized force/EMG ratio) to the EMG mean frequency. Using the decrease in mean frequency estimated through wavelet transforms between dynamic squats performed before and after the fatigue session as input to the previous linear regression, a coefficient accounting for the presence of fatigue in the quadriceps group was computed. This coefficient was used to constrain the moment production capacity of the fatigued muscle group within an EMG-driven optimization model dedicated to estimate the contributions of the knee flexor and extensor muscle groups to the net joint moment. During squats, our results showed significant increases in the EMG amplitudes with fatigue (+23.27% in average) while the outputs of the EMG-driven model were similar. The modifications of the EMG amplitudes following fatigue were successfully taken into account while estimating the contributions of the flexor and extensor muscle groups to the net joint moment. These results demonstrated that the new procedure was able to estimate the decrease in moment production capacity of the fatigued muscle group.

  8. 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.

  9. 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.

  10. Towards Whole Body Fatigue Assessment of Human Movement: A Fatigue-Tracking System Based on Combined sEMG and Accelerometer Signals

    Directory of Open Access Journals (Sweden)

    Haiwei Dong

    2014-01-01

    Full Text Available This paper proposes a method to assess the overall fatigue of human body movement. First of all, according to previous research regarding localized muscular fatigue, a linear relation is assumed between the mean frequency and the muscular working time when the muscle is experiencing fatigue. This assumption is verified with a rigorous statistical analysis. Based on this proven linearity, localized muscular fatigue is simplified as a linear model. Furthermore, localized muscular fatigue is considered a dynamic process and, hence, the localized fatigue levels are tracked by updating the parameters with the most current surface electromyogram (sEMG measurements. Finally, an overall fatigue level is computed by fusing localized muscular fatigue levels. The developed fatigue-tracking system is evaluated with two fatigue experiments (in which 10 male subjects and seven female subjects participated, including holding self-weight (dip start position training and lifting weight with one arm (arm curl training.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. EMG analysis of human inspiratory muscle resistance to fatigue during exercise.

    Science.gov (United States)

    Segizbaeva, M O; Donina, Zh A; Timofeev, N N; Korolyov, Yu N; Golubev, V N; Aleksandrova, N P

    2013-01-01

    The aim of this study was to characterize the pattern of inspiratory muscle fatigue and to assess the resistance to fatigue of the diaphragm (D), parasternal (PS), sternocleidomastoid (SCM), and scalene (SC) muscles. Nine healthy, untrained male subjects participated in this study. Electromyographic activity (EMG) of D, PS, SCM, and SC was recorded during an incremental cycling test to exhaustion (workload of 1.0 W/kg with 0.5 W/kg increments every 5 min). The before-to-after exercise measurements of maximal inspiratory pressure (MIP) and EMG power spectrum changes were performed. The maximal inspiratory pressure declined about 8.1 % after exercise compared with that in the control condition (124.3 ± 8.5 vs. 114.2 ± 8.9 cmH2O) (P > 0.05), whereas the peak magnitude of integrated electrical activity of D, PS, SCM, and SC during the post-exercise Müller maneuver was significantly greater in all subjects than that pre-exercise. The extent of inspiratory muscles fatigue was evaluated by analysis of a shift in centroid frequency (fc) of EMG power spectrum. Exercise-induced D fatigue was present in three subjects and PS fatigue was another in two; whereas both D and PC fatigue were observed in four subjects. All subjects demonstrated a significant reduction in fc of SCM and SC. Results indicate that early signs of the fatiguing process might be detected in the D, PS, SCM, and SC muscles during exercise to exhaustion. Fatigue of either D or PS muscles develops selectively or together during exhaustive exercise, depending on the recruitment pattern of respiratory muscles. Accessory inspiratory muscles of the neck are less resistant to fatigue compared with the D and PS muscles.

  16. Torque-EMG-velocity relationship in female workers with chronic neck muscle pain

    DEFF Research Database (Denmark)

    Andersen, Lars L; Nielsen, Pernille K; Søgaard, Karen

    2008-01-01

    The present study investigated the effect of chronic neck muscle pain (defined as trapezius myalgia) on neck/shoulder muscle function during concentric, eccentric and static contraction. Forty-two female office workers with trapezius myalgia (MYA) and 20 healthy matched controls (CON) participated....... Isokinetic (-60, 60 and 180 degrees s(-1)) and static maximal voluntary shoulder abductions were performed in a Biodex dynamometer, and electromyography (EMG) obtained in the trapezius and deltoideus muscles. Muscle thickness in the trapezius was measured with ultrasound. Pain and perceived exertion were...... were not significantly different between the groups. While perceived exertion increased in both groups in response to the test (ppain increased in MYA only (ppainful...

  17. Kahden eri istuma-asennon vaikutus lantionpohjan lihasten EMG-aktiviteettiin

    OpenAIRE

    Anttonen, Elina; Jukarainen, Satu

    2010-01-01

    Opinnäytetyön tavoitteena on selvittää kahden eri istuma-asennon vaikutusta lantionpohjan lihasten ja vatsalihasten EMG-aktiviteettiin. Opinnäytetyö koostuu kirjallisuuskatsauksesta ja tutkimusosuudesta. Opinnäytetyö toteutettiin yhteistyössä Keski-Suomen keskussairaalan kanssa. Kirjallisuuskatsaus käsittelee keskivartalon syvän lihasjärjestelmän merkitystä lannerangan hallinnassa istuma-asennon aikana sekä lantionpohjan lihasten toimintaa yhdessä muiden keskivartalon syvää...

  18. 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.

  19. 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.

  20. Differential EMG biofeedback for children with ADHD: a control method for neurofeedback training with a case illustration.

    Science.gov (United States)

    Maurizio, S; Liechti, M D; Brandeis, D; Jäncke, L; Drechsler, R

    2013-06-01

    The objective of the present paper was to develop a differential electromyographic biofeedback (EMG-BF) training for children with attention-deficit/hyperactivity disorder (ADHD) matching multiple neurofeedback training protocols in order to serve as a valid control training. This differential EMG-BF training method feeds back activity from arm muscles involved in fine motor skills such as writing and grip force control. Tonic EMG-BF training (activation and deactivation blocks, involving bimanual motor tasks) matches the training of EEG frequency bands, while phasic EMG-BF training (short activation and deactivation trials) was developed as an equivalent to the training of slow cortical potentials. A case description of a child who learned to improve motor regulation in most task conditions and showed a clinically relevant reduction of behavioral ADHD symptoms illustrates the training course and outcome. Differential EMG-BF training is feasible and provides well-matched control conditions for neurofeedback training in ADHD research. Future studies should investigate its value as a specific intervention for children diagnosed with ADHD and comorbid sensorimotor problems.

  1. 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...

  2. 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.

  3. 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.

  4. High efficiency and simple technique for controlling mechanisms by EMG signals

    Science.gov (United States)

    Dugarte, N.; Álvarez, A.; Balacco, J.; Mercado, G.; Gonzalez, A.; Dugarte, E.; Javier, F.; Ceballos, G.; Olivares, A.

    2016-04-01

    This article reports the development of a simple and efficient system that allows control of mechanisms through electromyography (EMG) signals. The novelty about this instrument is focused on individual control of each motion vector mechanism through independent electronic circuits. Each of electronic circuit does positions a motor according to intensity of EMG signal captured. This action defines movement in one mechanical axis considered from an initial point, based on increased muscle tension. The final displacement of mechanism depends on individual’s ability to handle the levels of muscle tension at different body parts. This is the design of a robotic arm where each degree of freedom is handled with a specific microcontroller that responds to signals taken from a defined muscle. The biophysical interaction between the person and the final positioning of the robotic arm is used as feedback. Preliminary tests showed that the control operates with minimal positioning error margins. The constant use of system with the same operator showed that the person adapts and progressively improves at control technique.

  5. Muscular co-operation during joint stabilisation, as reflected by EMG.

    Science.gov (United States)

    Kornecki, S; Kebel, A; Siemieński, A

    2001-05-01

    The experiment that was carried out consisted of subjects pushing an external object (a heavy pendulum) using stable and unstable handles of increasing mobility. Using this protocol it was possible to distinguish between the motor and stabilising functions of the muscles of the upper extremity. The motor functions were realised by the extensors of the upper extremity, whereas stabilising functions were effected by the muscles spanning the wrist joint. The experiment involved synchronised measurements of the electromyographic (EMG) activity of the muscles in question together with several mechanical quantities revealed against the external object: force, velocity and power. As a result, the instantaneous and global EMG contributions of the extensor and stabilising muscles were determined. It was found that it is the equilibrium state of the object being set in motion and not its mobility (expressed in terms of the number of degrees of freedom) that influences the forces produced by individual muscles. We also suggest that the realisation of stabilising functions by skeletal muscles is a necessary condition of performing any voluntary and co-ordinated movement.

  6. 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

  7. Estimating Isometric Tension of Finger Muscle Using Needle EMG Signals and the Twitch Contraction Model

    Science.gov (United States)

    Tachibana, Hideyuki; Suzuki, Takafumi; Mabuchi, Kunihiko

    We address an estimation method of isometric muscle tension of fingers, as fundamental research for a neural signal-based prosthesis of fingers. We utilize needle electromyogram (EMG) signals, which have approximately equivalent information to peripheral neural signals. The estimating algorithm comprised two convolution operations. The first convolution is between normal distribution and a spike array, which is detected by needle EMG signals. The convolution estimates the probability density of spike-invoking time in the muscle. In this convolution, we hypothesize that each motor unit in a muscle activates spikes independently based on a same probability density function. The second convolution is between the result of the previous convolution and isometric twitch, viz., the impulse response of the motor unit. The result of the calculation is the sum of all estimated tensions of whole muscle fibers, i.e., muscle tension. We confirmed that there is good correlation between the estimated tension of the muscle and the actual tension, with >0.9 correlation coefficients at 59%, and >0.8 at 89% of all trials.

  8. 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.

  9. [Hip abduction force measured by a new method and its relation to EMG activity].

    Science.gov (United States)

    Murakami, K

    1989-11-01

    I measured hip abduction force using a new device of my own design and evaluated the correlation between hip abduction force and electromyographic (EMG) activity of the gluteus medius, gluteus maximus, rectus femoris and adductor longus in 20 normal adults. Hip abduction force showed a maximum value on starting and decreased during abduction of the hip joint. Durability, on the other hand, showed an increase. The attenuation curve was approximated to the exponential function A.e-Kt; A and l/k indicating maximum hip abduction force and durability, respectively. Maximum hip abduction force was about 20 kg and durability was about 160 seconds on starting hip abduction. The regression coefficient between hip abduction force and EMG activity of the gluteus medius, gluteus maximus, rectus femoris and adductor longus was 1.5, 06, 0.6 and 0.2 respectively. From these results, I concluded that although the gluteus medius plays the major role in hip abduction, the rectus femoris and gluteus maximus may act as stabilizers for maintaining the position of hip abduction.

  10. 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.

  11. Fuel selection during intense shivering in humans: EMG pattern reflects carbohydrate oxidation

    Science.gov (United States)

    Haman, François; Legault, Stéphane R; Weber, Jean-Michel

    2004-01-01

    The thermogenic response of humans depends critically on the coordination of muscle fibre recruitment and oxidative fuel metabolism. The primary goal of this study was to determine whether the electromyographic (EMG) pattern of muscle recruitment could provide metabolic information on oxidative fuel selection during high-intensity shivering. EMG activity (of 8 large muscles) and fuel metabolism were monitored simultaneously in non-acclimatized adult men during high-intensity shivering. Even though acute cold exposure elicited similar changes in metabolic rate among subjects, lipid and carbohydrate use was very different. Depending on the subject, the cold-induced increase in carbohydrate (CHO) oxidation ranged between 2- and 8-fold, with CHO accounting for 33–78% of total heat production (Ḣprod), and lipids for 14–60% Ḣprod. This high variability in fuel selection was primarily explained by differences in ‘burst shivering’ rate, indicating that the recruitment of type II fibres plays a key role in orchestrating fuel selection. This study is the first to show that the pattern of muscle recruitment can provide quantitative information on energy metabolism. Future work should focus on the study of shivering bursts that may provide essential clues on what limits human survival in the cold. PMID:14742724

  12. 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 peak triceps muscle activity (p = 0.01). However, one-way repeated ANOVA produced no statistical significance in the composite 3-dimensional movement acceleration coordination data (p = 0.12). The present study is a first clinical trial that demonstrated the superior benefits of the EMG biofeedback when 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.

  13. EMG analysis of lumbar paraspinal muscles as a predictor of the risk of low-back pain.

    Science.gov (United States)

    Heydari, Abbas; Nargol, Antoni V F; Jones, Anthony P C; Humphrey, Anthony R; Greenough, Charles G

    2010-07-01

    Studies of EMG power spectra have established associations between low-back pain (LBP) and median frequency (MF). This 2-year prospective study investigates the association of LBP with EMG variables over time. 120 health care workers underwent paraspinal EMG measurements and assessment of back pain disability. The EMG recordings were performed under isometric trunk extension at 2/3 maximum voluntary contraction and acquired from erector spinae muscles at the level of L4/L5. 108 (90%) subjects were reviewed at a minimum 2-year follow up. 16 out of 93 subjects with no history of chronic low-back pain became worse as measured by time off work, disability, reported pain and self-assessment rating. The value of the EMG variable half-width at inception demonstrated significant association with changes in subject's outcome measure and their own assessment of their LBP at follow up (p assessment data, subjects with no history of chronic LBP with half-width of greater than 56 Hz were at threefold greater risk of developing back pain compared with the remainder of the population (p = 0.045). The value of the initial median frequency (IMF) and MF slope at inception were also associated with the subjects' own assessment of LBP at follow up. Subjects with an IMF greater than 49 Hz were at 5.8-fold greater risk of developing back pain compared with the remainder of the population (p = 0.014). EMG variables recorded from lumbar paraspinal muscles can identify a sub group of subjects at increased risk of developing low-back pain in the future.