WorldWideScience

Sample records for surface emg signal

  1. Identification of contaminant type in surface electromyography (EMG) signals.

    Science.gov (United States)

    McCool, Paul; Fraser, Graham D; Chan, Adrian D C; Petropoulakis, Lykourgos; Soraghan, John J

    2014-07-01

    The ability to recognize various forms of contaminants in surface electromyography (EMG) signals and to ascertain the overall quality of such signals is important in many EMG-enabled rehabilitation systems. In this paper, new methods for the automatic identification of commonly occurring contaminant types in surface EMG signals are presented. Such methods are advantageous because the contaminant type is typically not known in advance. The presented approach uses support vector machines as the main classification system. Both simulated and real EMG signals are used to assess the performance of the methods. The contaminants considered include: 1) electrocardiogram interference; 2) motion artifact; 3) power line interference; 4) amplifier saturation; and 5) additive white Gaussian noise. Results show that the contaminants can readily be distinguished at lower signal to noise ratios, with a growing degree of confusion at higher signal to noise ratios, where their effects on signal quality are less significant.

  2. 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.

  3. Surface Laplacian of scalp electrical signals and independent component analysis resolve EMG contamination of electroencephalogram.

    Science.gov (United States)

    Fitzgibbon, S P; DeLosAngeles, D; Lewis, T W; Powers, D M W; Whitham, E M; Willoughby, J O; Pope, K J

    2015-09-01

    The serious impact of electromyogram (EMG) contamination of electroencephalogram (EEG) is well recognised. The objective of this research is to demonstrate that combining independent component analysis with the surface Laplacian can eliminate EMG contamination of the EEG, and to validate that this processing does not degrade expected neurogenic signals. The method involves sequential application of ICA, using a manual procedure to identify and discard EMG components, followed by the surface Laplacian. The extent of decontamination is quantified by comparing processed EEG with EMG-free data that was recorded during pharmacologically induced neuromuscular paralysis. The combination of the ICA procedure and the surface Laplacian, with a flexible spherical spline, results in a strong suppression of EMG contamination at all scalp sites and frequencies. Furthermore, the ICA and surface Laplacian procedure does not impair the detection of well-known, cerebral responses; alpha activity with eyes-closed; ERP components (N1, P2) in response to an auditory oddball task; and steady state responses to photic and auditory stimulation. Finally, more flexible spherical splines increase the suppression of EMG by the surface Laplacian. We postulate this is due to ICA enabling the removal of local muscle sources of EMG contamination and the Laplacian transform being insensitive to distant (postural) muscle EMG contamination. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. 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.

  5. Discrimination of Combined Motions for Prosthetic Hands Using Surface EMG Signals

    Science.gov (United States)

    Ibe, Ayuko; Gouko, Manabu; Ito, Koji

    The present paper proposes a multiple step discrimination method to determine single and combined movements intended by an amputee from surface electromyogram (EMG) signals. Most previous approaches to the discrimination of movement using EMG signals have been restricted to single joint movements. Our approach enables the amputee's intended movement to be determined from among four single and two combined limb functions using an initial rise zone 125 msec long. Experiments with ten subjects and four electrodes demonstrated that our proposal determines six forearm movements at a discrimination rate exceeding than 90%.

  6. 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

  7. 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.

  8. Muscle Activity Map Reconstruction from High Density Surface EMG Signals With Missing Channels Using Image Inpainting and Surface Reconstruction Methods.

    Science.gov (United States)

    Ghaderi, Parviz; Marateb, Hamid R

    2017-07-01

    The aim of this study was to reconstruct low-quality High-density surface EMG (HDsEMG) signals, recorded with 2-D electrode arrays, using image inpainting and surface reconstruction methods. It is common that some fraction of the electrodes may provide low-quality signals. We used variety of image inpainting methods, based on partial differential equations (PDEs), and surface reconstruction methods to reconstruct the time-averaged or instantaneous muscle activity maps of those outlier channels. Two novel reconstruction algorithms were also proposed. HDsEMG signals were recorded from the biceps femoris and brachial biceps muscles during low-to-moderate-level isometric contractions, and some of the channels (5-25%) were randomly marked as outliers. The root-mean-square error (RMSE) between the original and reconstructed maps was then calculated. Overall, the proposed Poisson and wave PDE outperformed the other methods (average RMSE 8.7 μVrms ± 6.1 μVrms and 7.5 μVrms ± 5.9 μVrms) for the time-averaged single-differential and monopolar map reconstruction, respectively. Biharmonic Spline, the discrete cosine transform, and the Poisson PDE outperformed the other methods for the instantaneous map reconstruction. The running time of the proposed Poisson and wave PDE methods, implemented using a Vectorization package, was 4.6 ± 5.7 ms and 0.6 ± 0.5 ms, respectively, for each signal epoch or time sample in each channel. The proposed reconstruction algorithms could be promising new tools for reconstructing muscle activity maps in real-time applications. Proper reconstruction methods could recover the information of low-quality recorded channels in HDsEMG signals.

  9. 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.

  10. Age Related Differences in the Surface EMG Signals on Adolescent's Muscle during Contraction

    Science.gov (United States)

    Uddin Ahamed, Nizam; Taha, Zahari; Alqahtani, Mahdi; Altwijri, Omar; Rahman, Matiur; Deboucha, Abdelhakim

    2016-02-01

    The aim of this study was to investigate whether there are differences in the amplitude of the EMG signal among five different age groups of adolescent's muscle. Fifteen healthy adolescents participated in this study and they were divided into five age groups (13, 14, 15, 16 and 17 years). Subjects were performed dynamic contraction during lifting a standard weight (3-kg dumbbell) and EMG signals were recorded from their Biceps Brachii (BB) muscle. Two common EMG analysis techniques namely root mean square (RMS) and mean absolute values (MAV) were used to find the differences. The statistical analysis was included: linear regression to examine the relationships between EMG amplitude and age, repeated measures ANOVA to assess differences among the variables, and finally Coefficient of Variation (CoV) for signal steadiness among the groups of subjects during contraction. The result from RMS and MAV analysis shows that the 17-years age groups exhibited higher activity (0.28 and 0.19 mV respectively) compare to other groups (13-Years: 0.26 and 0.17 mV, 14-years: 0.25 and 0.23 mV, 15-Years: 0.23 and 0.16 mV, 16-years: 0.23 and 0.16 mV respectively). Also, this study shows modest correlation between age and signal activities among all age group's muscle. The experiential results can play a pivotal role for developing EMG prosthetic hand controller, neuromuscular system, EMG based rehabilitation aid and movement biomechanics, which may help to separate age groups among the adolescents.

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

    Science.gov (United States)

    Zhang, Qin; Liu, Runfeng; Chen, Wenbin; Xiong, Caihua

    2017-01-01

    In this paper, we present a simultaneous and continuous kinematics estimation method for multiple DoFs across shoulder and elbow joint. Although simultaneous and continuous kinematics estimation from surface electromyography (EMG) is a feasible way to achieve natural and intuitive human-machine interaction, few works investigated multi-DoF estimation across the significant joints of upper limb, shoulder and elbow joints. This paper evaluates the feasibility to estimate 4-DoF kinematics at shoulder and elbow during coordinated arm movements. Considering the potential applications of this method in exoskeleton, prosthetics and other arm rehabilitation techniques, the estimation performance is presented with different muscle activity decomposition and learning strategies. Principle component analysis (PCA) and independent component analysis (ICA) are respectively employed for EMG mode decomposition with artificial neural network (ANN) for learning the electromechanical association. Four joint angles across shoulder and elbow are simultaneously and continuously estimated from EMG in four coordinated arm movements. By using ICA (PCA) and single ANN, the average estimation accuracy 91.12% (90.23%) is obtained in 70-s intra-cross validation and 87.00% (86.30%) is obtained in 2-min inter-cross validation. This result suggests it is feasible and effective to use ICA (PCA) with single ANN for multi-joint kinematics estimation in variant application conditions. PMID:28611573

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

    Directory of Open Access Journals (Sweden)

    Qin Zhang

    2017-05-01

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

  13. 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.

  14. Decoding of individual finger movements from surface EMG signals using vector autoregressive hierarchical hidden Markov models (VARHHMM).

    Science.gov (United States)

    Malesevic, Nebojsa; Markovic, Dimitrije; Kanitz, Gunter; Controzzi, Marco; Cipriani, Christian; Antfolk, Christian

    2017-07-01

    In this paper we present a novel method for predicting individual fingers movements from surface electromyography (EMG). The method is intended for real-time dexterous control of a multifunctional prosthetic hand device. The EMG data was recorded using 16 single-ended channels positioned on the forearm of healthy participants. Synchronously with the EMG recording, the subjects performed consecutive finger movements based on the visual cues. Our algorithm could be described in following steps: extracting mean average value (MAV) of the EMG to be used as the feature for classification, piece-wise linear modeling of EMG feature dynamics, implementation of hierarchical hidden Markov models (HHMM) to capture transitions between linear models, and implementation of Bayesian inference as the classifier. The performance of our classifier was evaluated against commonly used real-time classifiers. The results show that the current algorithm setup classifies EMG data similarly to the best among tested classifiers but with equal or less computational complexity.

  15. 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

  16. 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 < 0.001) 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

  17. Quantification of surface EMG signals to monitor the effect of a Botox treatment in six healthy ponies and two horses with stringhalt: Preliminary study

    NARCIS (Netherlands)

    Wijnberg, I.D.; Schrama, S.E.A.; Elgersma, A.E.; Maree, J.T.M.; Cocq, de P.; Back, W.

    2009-01-01

    REASONS FOR PERFORMING THE STUDY: Therapeutic options for stringhalt in horses are limited, whereas medical experiences with botulinum toxin type A (Botox) have been positive. To evaluate its effectiveness in horses, surface electromyography (sEMG) signals before and after injection need to be

  18. 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

  19. 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....

  20. Quantification of surface EMG signals to monitor the effect of a Botox treatment in six healthy ponies and two horses with stringhalt: preliminary study.

    Science.gov (United States)

    Wijnberg, I D; Schrama, S E A; Elgersma, A E; Maree, J T M; de Cocq, P; Back, W

    2009-03-01

    Therapeutic options for stringhalt in horses are limited, whereas medical experiences with botulinum toxin type A (Botox) have been positive. To evaluate its effectiveness in horses, surface electromyography (sEMG) signals before and after injection need to be quantified. Treatment of healthy ponies and cases with Botox should reduce muscle activity in injected muscles and reduce spastic movements without adverse side effects. Unilaterally, the extensor digitorum longus, extensor digitorum lateralis and lateral vastus muscles of 6 healthy mature Shetland ponies and 2 talented Dutch Warmblood dressage horses with stringhalt were injected (maximum of 400 iu per pony and 700 iu per case; 100 iu in 5 ml NaCl divided into 5 injections) with Botox under needle EMG guidance. Surface EMG data were evaluated using customised software, and in the individuals gait was analysed using Proreflex. Statistical analysis was performed using mixed models and independent sample t test (P signals were quantified using customised software. The area under the curve (integrated EMG) in time was used as variable. It became significantly reduced in injected muscles after injection of Botox in normal ponies (P signals recorded from injected muscle were reduced, which proves this to be a useful tool in statistically evaluating a treatment effect. The positive results of this pilot study encourage further research with a larger group of clinical cases.

  1. Predicting 3D lip shapes using facial surface EMG

    OpenAIRE

    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 their associated motions. Materials and methods With a stereo camera set-up, we recorded 3D lip shapes and simultaneously performed sEMG measurements of the facial muscles, applying principal compon...

  2. Detection of Multiple Innervation Zones from Multi-Channel Surface EMG Recordings with Low Signal-to-Noise Ratio Using Graph-Cut Segmentation.

    Directory of Open Access Journals (Sweden)

    Hamid Reza Marateb

    Full Text Available Knowledge of the location of muscle Innervation Zones (IZs is important in many applications, e.g. for minimizing the quantity of injected botulinum toxin for the treatment of spasticity or for deciding on the type of episiotomy during child delivery. Surface EMG (sEMG can be noninvasively recorded to assess physiological and morphological characteristics of contracting muscles. However, it is not often possible to record signals of high quality. Moreover, muscles could have multiple IZs, which should all be identified. We designed a fully-automatic algorithm based on the enhanced image Graph-Cut segmentation and morphological image processing methods to identify up to five IZs in 60-ms intervals of very-low to moderate quality sEMG signal detected with multi-channel electrodes (20 bipolar channels with Inter Electrode Distance (IED of 5 mm. An anisotropic multilayered cylinder model was used to simulate 750 sEMG signals with signal-to-noise ratio ranging from -5 to 15 dB (using Gaussian noise and in each 60-ms signal frame, 1 to 5 IZs were included. The micro- and macro- averaged performance indices were then reported for the proposed IZ detection algorithm. In the micro-averaging procedure, the number of True Positives, False Positives and False Negatives in each frame were summed up to generate cumulative measures. In the macro-averaging, on the other hand, precision and recall were calculated for each frame and their averages are used to determine F1-score. Overall, the micro (macro-averaged sensitivity, precision and F1-score of the algorithm for IZ channel identification were 82.7% (87.5%, 92.9% (94.0% and 87.5% (90.6%, respectively. For the correctly identified IZ locations, the average bias error was of 0.02±0.10 IED ratio. Also, the average absolute conduction velocity estimation error was 0.41±0.40 m/s for such frames. The sensitivity analysis including increasing IED and reducing interpolation coefficient for time samples was

  3. Emg Signal Analysis of Healthy and Neuropathic Individuals

    Science.gov (United States)

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

    2017-08-01

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

  4. EMG signal classification for myoelectric teleoperating a dexterous robot hand.

    Science.gov (United States)

    Wang, J Z; Wang, R C; Li, F; Jiang, M W; Jin, D W

    2005-01-01

    This paper details a strategy of discriminating finger motions using surface electromyography (EMG) signals, which could be applied to teleoperating a dexterous robot hand or controlling the advanced multi-fingered myoelectric prosthesis for hand amputees. Finger motions discrimination is the key problem in this study. Thus the emphasis is put on myoelectric signal processing approaches in this paper. The EMG signal classification system was established based on the surface EMG signals from the subject's forearm. Four pairs of electrodes were attached on the subjects to acquire the signals during six types of finger motions, i.e. thumb extension, thumb flexion, index finger extension, index finger flexion, middle finger extension, and middle finger flexion. In order to distinguish these finger motions. A combination of autoregressive (AR) model and an Artificial Neural Network (ANN) was used in the system. The discrimination procedure consists of two steps. Firstly, the AR model is used to preprocess the surface EMG signals to reduce the scale of the data. These data will be imported into the myoelectric pattern classifier. Secondly the coefficients of AR model are imported into the ANN to identify the finger motions. The experimental results show that the discrimination system works with satisfaction.

  5. The use of surface EMG in knee extensor moment prediction.

    Science.gov (United States)

    Cheng, C K; Hsiung, H S; Lai, J S

    1994-10-01

    A systematic method of EMG quantification is developed to estimate the isometric muscle moment directly from quantified surface EMG. This method includes the EMG Signals acquired from an acupuncture point Fu-Tu located on the quadriceps muscle group, an EMG smoothing scheme, an electromechanical time lag estimation, and a mathematical model with the polynomial regression function to quantify the EMG. Three subjects were asked to be tested on the CYBEX II dynamometer with a knee joint angle of 90 degree flexion and hip joint angle of also 90 degrees. They were asked to perform "two" trials of maximal voluntary contraction and "three" trials of free voluntary contraction of the isometric exercise. The first two trials were used to build up the quantification model, and the latter three trials served as data for the validation of the method. A Medelec MS92 EMG system with surface EMG electrodes was used to acquire the EMG Signals. In the determination of the regression order of the polynomial equations, the threshold value 0.0001 of the difference of the coefficient of determination values was used. The results of the polynomial regression orders are all 6 for three subjects, which reflects a tendency of nonlinear behavior of the EMG/moment relationship. A validation scheme was proposed to calculate the root mean square difference (RMSD) of the measured knee extensor moments from the CYBEX II dynamometer and estimated moments from the EMG quantification. The mean values of the RMSD of the three subjects were 0.0597, 0.0679 and 0.1080. These results demonstrate that the present approach can estimate the isometric muscle moment exerted by the quadriceps muscle group.

  6. Surface EMG parameters in schizophrenia patients.

    Science.gov (United States)

    Miroshnichenko, German; Kuzmina, Anna; Meigal, Alexander; Burkin, Mark; Rissanen, Saara M; Karjalainen, Pasi A

    2014-01-01

    The aim of the study was to compare a variety of surface EMG (sEMG) parameters in several groups of schizophrenia (SZ, n=69) patients and healthy controls (n=44). We computed spectral, mutual information (MI) based and recurrence quantification analysis (RQA) parameters of sEMG. The major finding is that sEMG of the controls had higher values of the MI-based parameter, mean and median spectrum frequencies, and lower values of most of RQA parameters. It means higher content of recurrent fragments in sEMG of SZ patients. We suggest that the differences might be caused by either denervation/renervation process of single muscle fibers in SZ patients and/or by increased motor unit synchronization induced by antipsychotic therapy.

  7. Assessment of force and fatigue in isometric contractions of the upper trapezius muscle by surface EMG signal and perceived exertion scale.

    Science.gov (United States)

    Troiano, Amedeo; Naddeo, Francesco; Sosso, Erik; Camarota, Gianfranco; Merletti, Roberto; Mesin, Luca

    2008-08-01

    Quantifying muscle force and fatigue is important in designing ergonomic work stations, in planning appropriate work-rest patterns, and in preventing/assessing the progress of disorders. In 14 subjects (seven males, seven females), muscle force and fatigue were estimated by subjective perception (based on Borg scale CR10) and objective indexes extracted from surface electromyogram (EMG). The experimental protocol consisted of an isometric task selective for the upper trapezius muscle at different force levels (10-80% of maximal voluntary contraction--MVC, in steps of 10%MVC) and one fatiguing contraction (constant force level at 50%MVC until exhaustion). Surface EMG signals were detected by a two-dimensional (2D) array of electrodes placed half way between C7 and the acromion. The following variables were calculated from EMG signals: muscle fibre conduction velocity (CV), root mean square value (RMS), mean frequency of the power spectrum (MNF), fractal dimension (FD), and entropy. All detected signals were also used to build topographical maps of RMS. Both subjective and objective indications of force and fatigue can provide information on exerted force and endurance time (ET). In particular, Borg ratings, RMS, and entropy were significantly related to force, and the rate of change of CV, MNF, FD, and Borg ratings were predictive of the endurance time. Moreover, significant differences were found in Borg ratings between males and females. The correlation coefficient of pairs of topographical maps of RMS was high (of the order of 0.8). This reflects a characteristic spatial-temporal recruitment of upper trapezius motor units that is not affected by force levels or fatigue.

  8. Rectification of the EMG Signal Impairs the Identification of Oscillatory Input to the Muscle

    OpenAIRE

    Neto, Osmar Pinto; Christou, Evangelos A.

    2009-01-01

    Rectification of EMG signals is a common processing step used when performing electroencephalographic–electromyographic (EEG–EMG) coherence and EMG–EMG coherence. It is well known, however, that EMG rectification alters the power spectrum of the recorded EMG signal (interference EMG). The purpose of this study was to determine whether rectification of the EMG signal influences the capability of capturing the oscillatory input to a single EMG signal and the common oscillations between two EMG ...

  9. 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.

  10. An Evaluation of Hand-Force Prediction Using Artificial Neural-Network Regression Models of Surface EMG Signals for Handwear Devices

    Directory of Open Access Journals (Sweden)

    Masayuki Yokoyama

    2017-01-01

    Full Text Available Hand-force prediction is an important technology for hand-oriented user interface systems. Specifically, surface electromyography (sEMG is a promising technique for hand-force prediction, which requires a sensor with a small design space and low hardware costs. In this study, we applied several artificial neural-network (ANN regression models with different numbers of neurons and hidden layers and evaluated handgrip forces by using a dynamometer. A handwear with dry electrodes on the dorsal interosseous muscles was used for our evaluation. Eleven healthy subjects participated in our experiments. sEMG signals with six different levels of forces from 0 N to 200 N and maximum voluntary contraction (MVC are measured to train and test our ANN regression models. We evaluated three different methods (intrasession, intrasubject, and intersubject evaluation, and our experimental results show a high correlation (0.840, 0.770, and 0.789 each between the predicted forces and observed forces, which are normalized by the MVC for each subject. Our results also reveal that ANNs with deeper layers of up to four hidden layers show fewer errors in intrasession and intrasubject evaluations.

  11. Robot Control Using Electromyography (EMG Signals of the Wrist

    Directory of Open Access Journals (Sweden)

    C. DaSalla

    2005-01-01

    Full Text Available The aim of this paper is to design a human–interface system, using EMG signals elicited by various wrist movements, to control a robot. EMG signals are normalized and based on joint torque. A three-layer neural network is used to estimate posture of the wrist and forearm from EMG signals. After training the neural network and obtaining appropriate weights, the subject was able to control the robot in real time using wrist and forearm movements.

  12. The extraction of neural strategies from the surface EMG: an update

    Science.gov (United States)

    Merletti, Roberto; Enoka, Roger M.

    2014-01-01

    A surface EMG signal represents the linear transformation of motor neuron discharge times by the compound action potentials of the innervated muscle fibers and is often used as a source of information about neural activation of muscle. However, retrieving the embedded neural code from a surface EMG signal is extremely challenging. Most studies use indirect approaches in which selected features of the signal are interpreted as indicating certain characteristics of the neural code. These indirect associations are constrained by limitations that have been detailed previously (Farina D, Merletti R, Enoka RM. J Appl Physiol 96: 1486–1495, 2004) and are generally difficult to overcome. In an update on these issues, the current review extends the discussion to EMG-based coherence methods for assessing neural connectivity. We focus first on EMG amplitude cancellation, which intrinsically limits the association between EMG amplitude and the intensity of the neural activation and then discuss the limitations of coherence methods (EEG-EMG, EMG-EMG) as a way to assess the strength of the transmission of synaptic inputs into trains of motor unit action potentials. The debated influence of rectification on EMG spectral analysis and coherence measures is also discussed. Alternatively, there have been a number of attempts to identify the neural information directly by decomposing surface EMG signals into the discharge times of motor unit action potentials. The application of this approach is extremely powerful, but validation remains a central issue. PMID:25277737

  13. The extraction of neural strategies from the surface EMG: an update.

    Science.gov (United States)

    Farina, Dario; Merletti, Roberto; Enoka, Roger M

    2014-12-01

    A surface EMG signal represents the linear transformation of motor neuron discharge times by the compound action potentials of the innervated muscle fibers and is often used as a source of information about neural activation of muscle. However, retrieving the embedded neural code from a surface EMG signal is extremely challenging. Most studies use indirect approaches in which selected features of the signal are interpreted as indicating certain characteristics of the neural code. These indirect associations are constrained by limitations that have been detailed previously (Farina D, Merletti R, Enoka RM. J Appl Physiol 96: 1486-1495, 2004) and are generally difficult to overcome. In an update on these issues, the current review extends the discussion to EMG-based coherence methods for assessing neural connectivity. We focus first on EMG amplitude cancellation, which intrinsically limits the association between EMG amplitude and the intensity of the neural activation and then discuss the limitations of coherence methods (EEG-EMG, EMG-EMG) as a way to assess the strength of the transmission of synaptic inputs into trains of motor unit action potentials. The debated influence of rectification on EMG spectral analysis and coherence measures is also discussed. Alternatively, there have been a number of attempts to identify the neural information directly by decomposing surface EMG signals into the discharge times of motor unit action potentials. The application of this approach is extremely powerful, but validation remains a central issue. Copyright © 2014 the American Physiological Society.

  14. A surface EMG test tool to measure proportional prosthetic control.

    Science.gov (United States)

    Sturma, Agnes; Roche, Aidan D; Göbel, Peter; Herceg, Malvina; Ge, Nan; Fialka-Moser, Veronika; Aszmann, Oskar

    2015-06-01

    In upper limb amputees, prosthetic control training is recommended before and after fitting. During rehabilitation, the focus is on selective proportional control signals. For functional monitoring, many different tests are available. None can be used in the early phase of training. However, an early assessment is needed to judge if a patient has the potential to control a certain prosthetic set-up. This early analysis will determine if further training is needed or if other strategies would be more appropriate. Presented here is a tool that is capable of predicting achievable function in voluntary EMG control. This tool is applicable to individual muscle groups to support preparation of training and fitting. In four of five patients, the sEMG test tool accurately predicted the suitability for further myoelectric training based on SHAP outcome measures. (P1: "Poor" function in the sEMG test tool corresponded to 54/100 in the SHAP test; P2: Good: 85; P3: Good: 81; P4: Average: 78). One patient scored well during sEMG testing, but was unmotivated during SHAP testing. (Good: 50) Therefore, the surface EMG test tool may predict achievable control skills to a high extent, validated with the SHAP, but requires further clinical testing to validate this technique.

  15. 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.

  16. Objective models of EMG signals for cyclic processes such as a human gait

    Science.gov (United States)

    Babska, Luiza; Selegrat, Monika; Dusza, Jacek J.

    2016-09-01

    EMG signals are small potentials appearing at the surface of human skin during muscle work. They arise due to changes in the physiological state of cell membranes in the muscle fibers. They are characterized by a relatively low frequency range (500 Hz) and a low amplitude signal (of the order of μV), making it difficult to record. Raw EMG signal is inherently random shape. However we can distinguish certain features related to the activation of the muscles of a deterministic or quasi-deterministic associated with the movement and its parametric description. Objective models of EMG signals were created on the base of actual data obtained from the VICON system installed at the University of Physical Education in Warsaw. The object of research (healthy woman) moved repeatedly after a fixed track. On her body 35 reflective markers to record the gait kinematics and 8 electrodes to record EMG signals were placed. We obtained research data included more than 1,000 EMG signals synchronized with the phases of gait. Test result of the work is an algorithm for obtaining the average EMG signal received from the multiple registration gait cycles carried out in the same reproducible conditions. The method described in the article is essentially a pre-finding measurement data from the two quasi-synchronous signals at different sampling frequencies for further processing. This signal is characterized by a significant reduction of high frequency noise and emphasis on the specific characteristics of individual records found in muscle activity.

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

    Science.gov (United States)

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

    2016-06-13

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

  18. Surface EMG pattern recognition for real-time control of a wrist exoskeleton

    National Research Council Canada - National Science Library

    Khokhar, Zeeshan O; Xiao, Zhen G; Menon, Carlo

    2010-01-01

    Surface electromyography (sEMG) signals have been used in numerous studies for the classification of hand gestures and movements and successfully implemented in the position control of different prosthetic hands for amputees...

  19. Research on Lower Limb Motion Recognition Based on Fusion of sEMG and Accelerometer Signals

    Directory of Open Access Journals (Sweden)

    Qingsong Ai

    2017-08-01

    Full Text Available Since surface electromyograghic (sEMG signals are non-invasive and capable of reflecting humans’ motion intention, they have been widely used for the motion recognition of upper limbs. However, limited research has been conducted for lower limbs, because the sEMGs of lower limbs are easily affected by body gravity and muscle jitter. In this paper, sEMG signals and accelerometer signals are acquired and fused to recognize the motion patterns of lower limbs. A curve fitting method based on median filtering is proposed to remove accelerometer noise. As for movement onset detection, an sEMG power spectral correlation coefficient method is used to detect the start and end points of active signals. Then, the time-domain features and wavelet coefficients of sEMG signals are extracted, and a dynamic time warping (DTW distance is used for feature extraction of acceleration signals. At last, five lower limbs’ motions are classified and recognized by using Gaussian kernel-based linear discriminant analysis (LDA and support vector machine (SVM respectively. The results prove that the fused feature-based classification outperforms the classification with only sEMG signals or accelerometer signals, and the fused feature can achieve 95% or higher recognition accuracy, demonstrating the validity of the proposed method.

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

    Science.gov (United States)

    Güler, Nihal Fatma; Hardalaç, Firat

    2002-04-01

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

  1. A study on the effect of age, gender and paralysis on sEMG signals

    CERN Document Server

    Jha, Abhishek

    2015-01-01

    Surface Electromyography (sEMG) is a technology to measure the bio-potentials across the muscles. The true prospective of this technology is yet to be explored. In this paper, a simple and economic construction of a sEMG sensor is proposed. These sensors are used to determine the differences in the Electromyography (EMG) signal patterns of different individuals. Signals of several volunteers from different age groups, gender and individual having paralysis have been obtained. The sEMG data acquisition is done using the soundcard of a computer, hence reducing the need of additional hardware. Finally, the data is used to analyse the relationship between electromyography and factors like age, gender and health condition i.e. paralysis.

  2. 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.

  3. Features extraction of EMG signal using time domain analysis for arm rehabilitation device

    Science.gov (United States)

    Jali, Mohd Hafiz; Ibrahim, Iffah Masturah; Sulaima, Mohamad Fani; Bukhari, W. M.; Izzuddin, Tarmizi Ahmad; Nasir, Mohamad Na'im

    2015-05-01

    Rehabilitation device is used as an exoskeleton for people who had failure of their limb. Arm rehabilitation device may help the rehab program whom suffers from arm disability. The device that is used to facilitate the tasks of the program should improve the electrical activity in the motor unit and minimize the mental effort of the user. Electromyography (EMG) is the techniques to analyze the presence of electrical activity in musculoskeletal systems. The electrical activity in muscles of disable person is failed to contract the muscle for movements. In order to prevent the muscles from paralysis becomes spasticity, the force of movements should minimize the mental efforts. Therefore, the rehabilitation device should analyze the surface EMG signal of normal people that can be implemented to the device. The signal is collected according to procedure of surface electromyography for non-invasive assessment of muscles (SENIAM). The EMG signal is implemented to set the movements' pattern of the arm rehabilitation device. The filtered EMG signal was extracted for features of Standard Deviation (STD), Mean Absolute Value (MAV) and Root Mean Square (RMS) in time-domain. The extraction of EMG data is important to have the reduced vector in the signal features with less of error. In order to determine the best features for any movements, several trials of extraction methods are used by determining the features with less of errors. The accurate features can be use for future works of rehabilitation control in real-time.

  4. Surface EMG Decomposition Based on K-means Clustering and Convolution Kernel Compensation

    Science.gov (United States)

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

    2015-01-01

    A new approach has been developed by combining the K-mean clustering (KMC) method and a modified convolution kernel compensation (CKC) method for multi-channel 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 multi-step 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 −10dB. Over 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 multi-channel 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. PMID:25486655

  5. 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.

  6. 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.

  7. MUAP number estimates in surface EMG: template-matching methods and their performance boundaries.

    Science.gov (United States)

    Zhou, Ping; Rymer, William Z

    2004-07-01

    Estimates of the number of motor unit action potential (MUAP)s appearing in the surface electromyogram (EMG) signal, which offers potentially valuable information about motor unit recruitment and firing rates, are likely to provide a more accurate reflection of the neural command to muscle than are current EMG quantification methods. In this paper, we show that the basic shapes of surface MUAPs recorded from the first dorsal interosseous (FDI) muscle can ideally be represented by a small number of waveforms. On the basis of this, we seek to estimate the number of MUAPs present in standard surface EMG records, using template-matching techniques to identify MUAP occurrences. Our simulation study indicates that the performance of template-matching methods for MUAP number estimation is mainly constrained by the MUAP superposition in the signal, and the maximum number of MUAPs allowed in the signal for a good estimation is determined by the duration of MUAPs. To further explore this from experimental surface EMG signals, we compare the recordings from a selective multiple concentric ring electrode against those derived from a standard differential EMG electrode situated over the same muscle. We conclude that the ring surface electrode only slightly reduces the MUAP duration and the less MUAP superposition rate contained in the signal is mainly achieved by reducing the pick up area of the electrode. Using a template-matching method, although the number of MUAPs can be approximately estimated based on a very selective surface EMG recording at low force levels, the maximum number of MUAPs correctly estimated from the surface EMG is constrained by the MUAP duration.

  8. An EMG-CT method using multiple surface electrodes in the forearm.

    Science.gov (United States)

    Nakajima, Yasuhiro; Keeratihattayakorn, Saran; Yoshinari, Satoshi; Tadano, Shigeru

    2014-12-01

    Electromyography computed tomography (EMG-CT) method is proposed for visualizing the individual muscle activities in the human forearm. An EMG conduction model was formulated for reverse-estimation of muscle activities using EMG signals obtained with multi surface electrodes. The optimization process was calculated using sequential quadratic programming by comparing the estimated EMG values from the model with the measured values. The individual muscle activities in the deep region were estimated and used to produce an EMG tomographic image. For validation of the method, isometric contractions of finger muscles were examined for three subjects, applying a flexion load (4.9, 7.4 and 9.8 N) to the proximal interphalangeal joint of the middle finger. EMG signals in the forearm were recorded during the tasks using multiple surface electrodes, which were bound around the subject's forearm. The EMG-CT method illustrates the distribution of muscle activities within the forearm. The change in amplitude and area of activated muscles can be observed. The normalized muscle activities of all three subjects appear to increase monotonically with increases in the load. Kinesiologically, this method was able to estimate individual muscle activation values and could provide a novel tool for studying hand function and development of an examination for evaluating rehabilitation. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. EMG signal decomposition using motor unit potential train validity.

    Science.gov (United States)

    Parsaei, Hossein; Stashuk, Daniel W

    2013-03-01

    A system to resolve an intramuscular electromyographic (EMG) signal into its component motor unit potential trains (MUPTs) is presented. The system is intended mainly for clinical applications where several physiological parameters of motor units (MUs), such as their motor unit potential (MUP) templates and mean firing rates, are of interest. The system filters an EMG signal, detects MUPs, and clusters and classifies the detected MUPs into MUPTs. Clustering is partially based on the K-means algorithm, and the supervised classification is implemented using a certainty-based algorithm. Both clustering and supervised classification algorithms use MUP shape and MU firing pattern information along with signal dependent assignment criteria to obtain robust performance across a variety of EMG signals. During classification, the validity of extracted MUPTs are determined using several supervised classifiers; invalid trains are corrected and the assignment threshold for each train is adjusted based on the estimated validity (i.e., adaptive classification). Performance of the developed system in terms of accuracy (A(c)), assignment rate (A(r)), correct classification rate (CC(r)) , and the error in estimating the number of MUPTs represented in the set of detected MUPs (E(NMUPTs)) was evaluated using 32 simulated and 30 real EMG signals comprised of 3-11 and 3-15 MUPTs, respectively. The developed system, with average CC(r) of 86.4% for simulated and 96.4% for real data, outperformed a previously developed EMG decomposition system, with average CC(r) of 71.6% and 89.7% for simulated and real data, by 14.7% and 6.7%, respectively. In terms of E(NMUPTs), the new system, with average E(NMUPTs) of 0.3 and 0.2 for simulated and real data respectively, was better able to estimate the number of MUPTs represented in a set of detected MUPs than the previous system, with average E(NMUPTs) of 2.2 and 0.8 for simulated and real data respectively. For both the simulated and real data used

  10. A Novel Framework Based on FastICA for High Density Surface EMG Decomposition

    Science.gov (United States)

    Chen, Maoqi; Zhou, Ping

    2015-01-01

    This study presents a progressive FastICA peel-off (PFP) framework for high density surface electromyogram (EMG) decomposition. The novel framework is based on a shift-invariant model for describing surface EMG. The decomposition process can be viewed as progressively expanding the set of motor unit spike trains, which is primarily based on FastICA. To overcome the local convergence of FastICA, a “peel off” strategy (i.e. removal of the estimated motor unit action potential (MUAP) trains from the previous step) is used to mitigate the effects of the already identified motor units, so more motor units can be extracted. Moreover, a constrained FastICA is applied to assess the extracted spike trains and correct possible erroneous or missed spikes. These procedures work together to improve the decomposition performance. The proposed framework was validated using simulated surface EMG signals with different motor unit numbers (30, 70, 91) and signal to noise ratios (SNRs) (20, 10, 0 dB). The results demonstrated relatively large numbers of extracted motor units and high accuracies (high F1-scores). The framework was also tested with 111 trials of 64-channel electrode array experimental surface EMG signals during the first dorsal interosseous (FDI) muscle contraction at different intensities. On average 14.1 ± 5.0 motor units were identified from each trial of experimental surface EMG signals. PMID:25775496

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

    OpenAIRE

    Kale, S. N.; Dudul, S. V.

    2009-01-01

    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 d...

  12. Novel Methods for Surface EMG Analysis and Exploration Based on Multi-Modal Gaussian Mixture Models

    National Research Council Canada - National Science Library

    Vögele, Anna Magdalena; Zsoldos, Rebeka R; Krüger, Björn; Licka, Theresia

    2016-01-01

    .... It is based on fitting Gaussian mixture models (GMMs) to surface EMG data (sEMG). This approach enables researchers/users to isolate parts of the overall muscle activation within locomotion EMG data...

  13. 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

  14. 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.

  15. 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.

  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. The classification for "equilibrium triad" sensory loss based on sEMG signals of calf muscles.

    Science.gov (United States)

    Hairong Yu; Kairui Guo; Jie Luo; Kai Cao; Nguyen, Hung T; Su, Steven W

    2017-07-01

    Surface Electromyography (sEMG) has been commonly applied for analysing the electrical activities of skeletal muscles. The sensory system of maintaining posture balance includes vision, proprioception and vestibular senses. In this work, an attempt is made to classify whether the body is missing one of the sense during balance control by using sEMG signals. A trial of combination with different features and muscles is also developed. The results demonstrate that the classification accuracy between vision loss and the normal condition is higher than the one between vestibular sense loss and normal condition. When using different features and muscles, the impact on classification results is also different. The outcomes of this study could aid the development of sEMG based classification for the function of sensory systems during human balance movement.

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

    Science.gov (United States)

    Ying, Rex; Wall, Christine E

    2016-12-08

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

  19. Surface EMG pattern recognition for real-time control of a wrist exoskeleton

    Directory of Open Access Journals (Sweden)

    Khokhar Zeeshan O

    2010-08-01

    Full Text Available Abstract Background Surface electromyography (sEMG signals have been used in numerous studies for the classification of hand gestures and movements and successfully implemented in the position control of different prosthetic hands for amputees. sEMG could also potentially be used for controlling wearable devices which could assist persons with reduced muscle mass, such as those suffering from sarcopenia. While using sEMG for position control, estimation of the intended torque of the user could also provide sufficient information for an effective force control of the hand prosthesis or assistive device. This paper presents the use of pattern recognition to estimate the torque applied by a human wrist and its real-time implementation to control a novel two degree of freedom wrist exoskeleton prototype (WEP, which was specifically developed for this work. Methods Both sEMG data from four muscles of the forearm and wrist torque were collected from eight volunteers by using a custom-made testing rig. The features that were extracted from the sEMG signals included root mean square (rms EMG amplitude, autoregressive (AR model coefficients and waveform length. Support Vector Machines (SVM was employed to extract classes of different force intensity from the sEMG signals. After assessing the off-line performance of the used classification technique, the WEP was used to validate in real-time the proposed classification scheme. Results The data gathered from the volunteers were divided into two sets, one with nineteen classes and the second with thirteen classes. Each set of data was further divided into training and testing data. It was observed that the average testing accuracy in the case of nineteen classes was about 88% whereas the average accuracy in the case of thirteen classes reached about 96%. Classification and control algorithm implemented in the WEP was executed in less than 125 ms. Conclusions The results of this study showed that

  20. 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

  1. Clinical applications of high-density surface EMG: a systematic review.

    NARCIS (Netherlands)

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

    2006-01-01

    High density-surface EMG (HD-sEMG) is a non-invasive technique to measure electrical muscle activity with multiple (more than two) closely spaced electrodes overlying a restricted area of the skin. Besides temporal activity HD-sEMG also allows spatial EMG activity to be recorded, thus expanding the

  2. Clinical applications of high-density surface EMG: A systematic review

    NARCIS (Netherlands)

    Drost, G; Stegeman, D.F.; van Engelen, B.G.M.; Smeitink, J.A.M.; Rodenburg, J.A.; Hol, F.A.

    2006-01-01

    High density-surface EMG (HD-sEMG) is a non-invasive technique to measure electrical muscle activity with multiple (more than two) closely spaced electrodes overlying a restricted area of the skin. Besides temporal activity HD-sEMG also allows spatial EMG activity to be recorded, thus expanding the

  3. 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.

  4. Evaluation of surface EMG features for the recognition of American Sign Language gestures.

    Science.gov (United States)

    Kosmidou, Vasiliki E; Hadjileontiadis, Leontios J; Panas, Stavros M

    2006-01-01

    In this work, analysis of the surface electromyogram (sEMG) signal is proposed for the recognition of American sign language (ASL) gestures. To this purpose, sixteen features are extracted from the sEMG signal acquired from the user's forearm, and evaluated by the Mahalanobis distance criterion. Discriminant analysis is used to reduce the number of features used in the classification of the signed ASL gestures. The proposed features are tested against noise resulting in a further reduced set of features, which are evaluated for their discriminant ability. The classification results reveal that 97.7% of the inspected ASL gestures were correctly recognized using sEMG-based features, providing a promising solution to the automatic ASL gesture recognition problem.

  5. 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...

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

    Science.gov (United States)

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

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

  7. 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.

  8. Quantitative surface electromyography (qEMG): applications in anaesthesiology and critical care.

    Science.gov (United States)

    Paloheimo, M

    1990-01-01

    During general anaesthesia and in lowered vigilance states such as after major trauma and during heavy sedation or analgesic medication, patients' ability to communicate with their surroundings is limited. Subjective intuitional interpretation may be the only means to ascertain a patient's emotional state, mood, and pain perception. Electromyographic detection and quantification of minimal and covert facial mimic muscle activity in anaesthesiology and critical care was an interesting concept worth further evaluation. In this study, the behaviour of quantitative surface-detected electromyographic activity (qEMG) was investigated during common anaesthetic events, post-operatively, and in volunteers as well as in experimental animals. A review of the methodology includes the necessary details for reproduction of the studies, including computerized processing of numerical data available in the commercial equipment. Results from the monitoring of 218 patients, seven volunteers and 31 rats are discussed. Conclusions are based on 32 testable null-hypotheses, the earlier documented literature and the author's own experience. The qEMG signal was derived from two electrodes placed on the frontal area and on the mastoid process behind the ipsilateral ear. After amplification, the signal was filtered to obtain a portion containing electrical activity between 60-300 Hz, which was considered to represent electromyographic activity. The signals were thereafter full-wave rectified and averaged with a 1-s time constant. The output of the processing unit consisted of a graphics display and a numeric computer output. A variety of clinical conditions and drug effects were studied in order to evaluate the method's applicability in research and in routine anaesthetic practice. The facial muscles turned out to be less sensitive to the effects of neuromuscular blocking drugs than the hand muscles, the normal monitoring site of neuromuscular transmission. Although muscle relaxants had a

  9. 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

  10. 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.

  11. Supralaryngeal muscle activity during sustained vibrato in four sopranos: surface EMG findings.

    Science.gov (United States)

    Sapir, S; Larson, K K

    1993-09-01

    Four classically trained sopranos, aged 22-41 years, sustained a vibrato at a comfortable loudness level, and at different vowels (/u/, /i/, or /a/) and pitch levels (220, 277, 349, 440, 554, 698, or 880 Hz). Pairs of surface electrodes were placed on each singer's right side over the submandibular region, the thyroid cartilage, mandibular ramus, and upper lip to record electromyographic (EMG) activity from the anterior suprahyoid (ASH), extralaryngeal (ELAR), massetter (MAS), and perioral (PER) muscles, respectively. A headset-mounted miniature microphone transduced the voice, and a Kay Visi-Pitch extracted the voice fundamental frequency (F0). The output of the Visi-Pitch, a voltage analog of the F0 (VF0), and the EMG signals were digitized, the EMG signals rectified and smoothed, and the VF0 and smoothed EMG signals were subjected to Fast Fourier Transform (FFT) analysis. Spectral peaks in the FFT records indicated vibrato-related activity in the ASH and ELAR muscles, with occasional vibrato-related activity in the MAS and PER muscles. The role of supralaryngeal muscles in vibrato is discussed.

  12. Absolute and relative intrasession reliability of surface EMG variables for voluntary precise forearm movements.

    Science.gov (United States)

    Carius, Daniel; Kugler, Patrick; Kuhwald, Hans-Marten; Wollny, Rainer

    2015-12-01

    The reliability of surface electromyography (EMG) derived parameters is of high importance, but there is distinct lack of studies concerning the reliability during dynamic contractions. Especially Amplitude, Fourier and Wavelet parameter in conjunction have not been tested so far. The interpretation of the EMG variables might be difficult because the movement itself introduces additional factors that affect its characteristics. The aim of this study was to determine the relative and absolute intrasession reliability of electromyographic (EMG) variables of selected arm muscles during concurrent precise elbow extension/flexion movements at different force levels and movement speed. Participants (all-male: n = 17, range 20-32 years) were asked to adapt to a gross-motor visuomotor tracking task (elbow extension/flexion movement) using a custom-built lever arm apparatus. After sufficient adaptation surface electromyography was used to record the electrical activity of mm. biceps brachii, brachioradialis and triceps brachii, and the signal amplitude (RMS [μV]) and the mean frequency of the power spectrum (MNF [Hz]) were computed. Additionally Wavelet analysis was used. Relative reproducibility (intraclass correlation) for signal amplitude, mean frequency of the power spectrum and Wavelet intensity during dynamic contractions was fair to good, independent of force level and movement speed (ICC = 0.71-0.98). The amount of absolute intrasession reliability (coefficient of variation) of EMG variables depends on muscle and force level. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Application of EMG signals for controlling exoskeleton robots.

    Science.gov (United States)

    Fleischer, Christian; Wege, Andreas; Kondak, Konstantin; Hommel, Günter

    2006-12-01

    Exoskeleton robots are mechanical constructions attached to human body parts, containing actuators for influencing human motion. One important application area for exoskeletons is human motion support, for example, for disabled people, including rehabilitation training, and for force enhancement in healthy subjects. This paper surveys two exoskeleton systems developed in our laboratory. The first system is a lower-extremity exoskeleton with one actuated degree of freedom in the knee joint. This system was designed for motion support in disabled people. The second system is an exoskeleton for a human hand with 16 actuated joints, four for each finger. This hand exoskeleton will be used in rehabilitation training after hand surgeries. The application of EMG signals for motion control is presented. An overview of the design and control methods, and first experimental results for the leg exoskeleton are reported.

  14. 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.

  15. Sex differences in surface EMG interference pattern power spectrum.

    Science.gov (United States)

    Cioni, R; Giannini, F; Paradiso, C; Battistini, N; Navona, C; Starita, A

    1994-11-01

    Sex differences in the spectral parameters of the surface electromyogram (EMG) power spectrum were studied during voluntary muscle contractions of different strength with rest in between. The influence of two different types of leads (unipolar and bipolar) on the values of the spectral parameters was also investigated under the same experimental conditions. The subjects were 15 healthy female and 15 healthy male volunteers. The relationship between the amplitude (root mean square) of the EMG and the force developed was not linear. The mean values of the median power frequency were lower in women than in men. With both types of lead, the increase in force was accompanied by a progressive increase in median power frequency in male and female subjects. The significant differences in spectral parameters observed in the two sexes are probably correlated with anatomic differences.

  16. 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%.

  17. Estimation of elbow-induced wrist force with EMG signals using fast orthogonal search.

    Science.gov (United States)

    Mobasser, Farid; Eklund, J Mikael; Hashtrudi-Zaad, Keyvan

    2007-04-01

    In many studies and applications that include direct human involvement-such as human-robot interaction, control of prosthetic arms, and human factor studies-hand force is needed for monitoring or control purposes. The use of inexpensive and easily portable active electromyogram (EMG) electrodes and position sensors would be advantageous in these applications compared to the use of force sensors, which are often very expensive and require bulky frames. Multilayer perceptron artificial neural networks (MLPANN) have been used commonly in the literature to model the relationship between surface EMG signals and muscle or limb forces for different anatomies. This paper investigates the use of fast orthogonal search (FOS), a time-domain method for rapid nonlinear system identification, for elbow-induced wrist force estimation. It further compares the forces estimated using FOS with the forces estimated by MLPANN for the same human anatomy under an ensemble of operational conditions. In this paper, the EMG signal readings from upper arm muscles involved in elbow joint movement and sensed elbow angular position and velocity are utilized as inputs. A single degree-of-freedom robotic experimental testbed has been constructed and used for data collection, training and validation.

  18. 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.

  19. Automatic segmentation of surface EMG images: Improving the estimation of neuromuscular activity.

    Science.gov (United States)

    Vieira, Taian M M; Merletti, Roberto; Mesin, Luca

    2010-08-10

    Surface electromyograms (EMGs) recorded with a couple of electrodes are meant to comprise representative information of the whole muscle activation. Nonetheless, regional variations in neuromuscular activity seem to occur in numerous conditions, from standing to passive muscle stretching. In this study, we show how local activation of skeletal muscles can be automatically tracked from EMGs acquired with a bi-dimensional grid of surface electrodes (a grid of 8 rows and 15 columns was used). Grayscale images were created from simulated and experimental EMGs, filtered and segmented into clusters of activity with the watershed algorithm. The number of electrodes on each cluster and the mean level of neuromuscular activity were used to assess the accuracy of the segmentation of simulated signals. Regardless of the noise level, thickness of fat tissue and acquisition configuration (monopolar or single differential), the segmentation accuracy was above 60%. Accuracy values peaked close to 95% when pixels with intensity below approximately 70% of maximal EMG amplitude in each segmented cluster were excluded. When simulating opposite variations in the activity of two adjacent muscles, watershed segmentation produced clusters of activity consistently centered on each simulated portion of active muscle and with mean amplitude close to the simulated value. Finally, the segmentation algorithm was used to track spatial variations in the activity, within and between medial and lateral gastrocnemius muscles, during isometric plantar flexion contraction and in quiet standing position. In both cases, the regionalization of neuromuscular activity occurred and was consistently identified with the segmentation method. Copyright 2010 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Weiwei Yu

    2017-01-01

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

  1. An artificial EMG generation model based on signal-dependent noise and related application to motion classification.

    Science.gov (United States)

    Furui, Akira; Hayashi, Hideaki; Nakamura, Go; Chin, Takaaki; Tsuji, Toshio

    2017-01-01

    This paper proposes an artificial electromyogram (EMG) signal generation model based on signal-dependent noise, which has been ignored in existing methods, by introducing the stochastic construction of the EMG signals. In the proposed model, an EMG signal variance value is first generated from a probability distribution with a shape determined by a commanded muscle force and signal-dependent noise. Artificial EMG signals are then generated from the associated Gaussian distribution with a zero mean and the generated variance. This facilitates representation of artificial EMG signals with signal-dependent noise superimposed according to the muscle activation levels. The frequency characteristics of the EMG signals are also simulated via a shaping filter with parameters determined by an autoregressive model. An estimation method to determine EMG variance distribution using rectified and smoothed EMG signals, thereby allowing model parameter estimation with a small number of samples, is also incorporated in the proposed model. Moreover, the prediction of variance distribution with strong muscle contraction from EMG signals with low muscle contraction and related artificial EMG generation are also described. The results of experiments conducted, in which the reproduction capability of the proposed model was evaluated through comparison with measured EMG signals in terms of amplitude, frequency content, and EMG distribution demonstrate that the proposed model can reproduce the features of measured EMG signals. Further, utilizing the generated EMG signals as training data for a neural network resulted in the classification of upper limb motion with a higher precision than by learning from only measured EMG signals. This indicates that the proposed model is also applicable to motion classification.

  2. An artificial EMG generation model based on signal-dependent noise and related application to motion classification

    Science.gov (United States)

    Hayashi, Hideaki; Nakamura, Go; Chin, Takaaki; Tsuji, Toshio

    2017-01-01

    This paper proposes an artificial electromyogram (EMG) signal generation model based on signal-dependent noise, which has been ignored in existing methods, by introducing the stochastic construction of the EMG signals. In the proposed model, an EMG signal variance value is first generated from a probability distribution with a shape determined by a commanded muscle force and signal-dependent noise. Artificial EMG signals are then generated from the associated Gaussian distribution with a zero mean and the generated variance. This facilitates representation of artificial EMG signals with signal-dependent noise superimposed according to the muscle activation levels. The frequency characteristics of the EMG signals are also simulated via a shaping filter with parameters determined by an autoregressive model. An estimation method to determine EMG variance distribution using rectified and smoothed EMG signals, thereby allowing model parameter estimation with a small number of samples, is also incorporated in the proposed model. Moreover, the prediction of variance distribution with strong muscle contraction from EMG signals with low muscle contraction and related artificial EMG generation are also described. The results of experiments conducted, in which the reproduction capability of the proposed model was evaluated through comparison with measured EMG signals in terms of amplitude, frequency content, and EMG distribution demonstrate that the proposed model can reproduce the features of measured EMG signals. Further, utilizing the generated EMG signals as training data for a neural network resulted in the classification of upper limb motion with a higher precision than by learning from only measured EMG signals. This indicates that the proposed model is also applicable to motion classification. PMID:28640883

  3. Classification of EMG signals using neuro-fuzzy system and diagnosis of neuromuscular diseases.

    Science.gov (United States)

    Koçer, Sabri

    2010-06-01

    This work investigates the performance of neuro-fuzzy system for analyzing and classifying EMG signals recorded from normal, neuropathy, and myopathy subjects. EMG signals were obtained from 177 subjects, 60 of them had suffered from neuropathy disorder, 60 of them had suffered from myopathy disorder, and rest of them had been normal. Coefficients that were obtained from the EMG signals using Autoregressive (AR) analysis was applied to neuro-fuzzy system. The classification performance of the feature sets was investigated for three classes.

  4. 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.

  5. Intra-session and inter-day reliability of forearm surface EMG during varying hand grip forces.

    Science.gov (United States)

    Hashemi Oskouei, Alireza; Paulin, Michael G; Carman, Allan B

    2013-02-01

    Surface electromyography (EMG) is widely used to evaluate forearm muscle function and predict hand grip forces; however, there is a lack of literature on its intra-session and inter-day reliability. The aim of this study was to determine reliability of surface EMG of finger and wrist flexor muscles across varying grip forces. Surface EMG was measured from six forearm flexor muscles of 23 healthy adults. Eleven of these subjects undertook inter-day test-retest. Six repetitions of five randomized isometric grip forces between 0% and 80% of maximum force (MVC) were recorded and normalized to MVC. Intra- and inter-day reliability were calculated through the intraclass correlation coefficient (ICC) and standard error of measurement (SEM). Normalized EMG produced excellent intra-session ICC of 0.90 when repeated measurements were averaged. Intra-session SEM was low at low grip forces, however, corresponding normalized SEM was high (23-45%) due to the small magnitude of EMG signals. This may limit the ability to evaluate finer forearm muscle function and hand grip forces in daily tasks. Combining EMG of functionally related muscles improved intra-session SEM, improving within-subject reliability without taking multiple measurements. Removing and replacing electrodes inter-day produced poor ICC (ICC < 0.50) but did not substantially affect SEM. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. 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...

  7. Teager–Kaiser energy operator signal conditioning improves EMG onset detection

    Science.gov (United States)

    Rider, Patrick; Steinweg, Ken; DeVita, Paul; Hortobágyi, Tibor

    2010-01-01

    Accurate identification of the onset of muscle activity is an important element in the biomechanical analysis of human movement. The purpose of this study was to determine if inclusion of the Teager–Kaiser energy operator (TKEO) in signal conditioning would increase the accuracy of popular electromyography (EMG) onset detection methods. Three methods, visual determination, threshold-based method, and approximated generalized likelihood ratio were used to estimate the onset of EMG burst with and without TKEO conditioning. Reference signals, with known onset times, were constructed from EMG signals collected during isometric contraction of the vastus lateralis (n = 17). Additionally, vastus lateralis EMG signals (n = 255) recorded during gait were used to evaluate a clinical application of the TKEO conditioning. Inclusion of TKEO in signal conditioning significantly reduced mean detection error of all three methods compared with signal conditioning without TKEO, using artificially generated reference data (13 vs. 98 ms, p EMG signals increases the detection accuracy of EMG burst boundaries. PMID:20526612

  8. The increase in surface EMG could be a misleading measure of neural adaptation during the early gains in strength.

    Science.gov (United States)

    Arabadzhiev, Todor I; Dimitrov, Vladimir G; Dimitrov, George V

    2014-08-01

    To test the validity of using the increase in surface EMG as a measure of neural adaptation during the early gains in strength. Simulation of EMG signals detected by surface bipolar electrode with 20-mm inter-pole distance at different radial distances from the muscle and longitudinal distances from the end-plate area. The increases in the root mean square (RMS) of the EMG signal due to possible alteration in the neural drive or elevation of the intracellular negative after-potentials, detected in fast fatigable muscle fibres during post-tetanic potentiation and assumed to accompany post-activation potentiation, were compared. Lengthening of the intracellular action potential (IAP) profile due to elevation of the negative after-potentials could affect amplitude characteristics of surface EMG detected at any axial distance stronger than alteration in the neural drive. This was irrespective of the fact that the elevation of IAP negative after-potential was applied to fast fatigable motor units (MUs) only, while changes in frequency of activation (simulating neural drive changes) were applied to all MUs. In deeper muscles, where the fibre-electrode distance was larger, the peripheral effect was more pronounced. The normalization of EMG amplitude characteristics to an M-wave one could result only in partial elimination of peripheral factor influence The increase in RMS of surface EMG during the early gains in strength should not be directly related to the changes in the neural drive. The relatively small but long-lasting elevated free resting calcium after high-resistance strength training could result in force potentiation and EMG increase.

  9. Dental occlusion and body posture: a surface EMG study.

    Science.gov (United States)

    Bergamini, Maurizio; Pierleoni, Felicita; Gizdulich, Andrea; Bergamini, Carlo

    2008-01-01

    The influence between dental occlusion and body posture has been discussed in the past ten years by several authors with controversial conclusions. The objective of this study was to access, using surface electromyography (EMG), the rest activity of paired sternocleidomastoids, erectors spinae at L4 level, and soleus muscles in a group of 24 volunteer subjects (12 males, 12 females, aged 23-25 yrs) affected by sub-clinical dental malocclusions in different situations of dental occlusion. The subjects' occlusion was balanced (neuromuscularly) (registered on an acrylic wafer). Rest activity was assessed using the sEMG. The measurements were achieved on subjects while standing barefooted, before (Test 1), and 15 minutes after they wore the acrylic wafer (Test 2). The result was a significant reduction of the mean voltage for each muscle. Paired muscles were registered and the balancing rate between right and left muscles showed improvement for all the paired muscles (Wilcoxon test p occlusion with an acrylic wafer on the following paired postural muscles: sternocleidomostoid, erector spinae, and soleus.

  10. Compression of high-density EMG signals for trapezius and gastrocnemius muscles

    Science.gov (United States)

    2014-01-01

    Background New technologies for data transmission and multi-electrode arrays increased the demand for compressing high-density electromyography (HD EMG) signals. This article aims the compression of HD EMG signals recorded by two-dimensional electrode matrices at different muscle-contraction forces. It also shows methodological aspects of compressing HD EMG signals for non-pinnate (upper trapezius) and pinnate (medial gastrocnemius) muscles, using image compression techniques. Methods HD EMG signals were placed in image rows, according to two distinct electrode orders: parallel and perpendicular to the muscle longitudinal axis. For the lossless case, the images obtained from single-differential signals as well as their differences in time were compressed. For the lossy algorithm, the images associated to the recorded monopolar or single-differential signals were compressed for different compression levels. Results Lossless compression provided up to 59.3% file-size reduction (FSR), with lower contraction forces associated to higher FSR. For lossy compression, a 90.8% reduction on the file size was attained, while keeping the signal-to-noise ratio (SNR) at 21.19 dB. For a similar FSR, higher contraction forces corresponded to higher SNR Conclusions The computation of signal differences in time improves the performance of lossless compression while the selection of signals in the transversal order improves the lossy compression of HD EMG, for both pinnate and non-pinnate muscles. PMID:24612604

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

    Science.gov (United States)

    Matsubara, Takamitsu; Morimoto, Jun

    2013-08-01

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

  12. Development of new protocols and analysis procedures for the assessment of LBP by surface EMG techniques.

    Science.gov (United States)

    Oddsson, L I; Giphart, J E; Buijs, R J; Roy, S H; Taylor, H P; De Luca, C J

    1997-10-01

    Spectral parameters of the surface electromyographic (EMG) signal from lumbar back muscles assessed during a fatiguing isometric contraction can be used to classify different categories of low back pain (LBP) subjects and control subjects without LBP. In the test protocol currently used at the NeuroMuscular Research Center at Boston University, subjects contract their back muscles at 80% of their maximal voluntary contraction (MVC) force. This fatigue-based protocol has been successfully applied to persons with subacute or chronic LBP; those in acute pain, however, have not been included because of their inability to perform a maximal exertion. In this paper we will examine the force sensitivity of the currently used EMG parameters and also give an overview of some of our efforts to develop new test procedures. Our goal is to develop force-insensitive surface EMG parameters that can be used for classification purposes in populations of subjects who develop low trunk extension forces. In addition, the development of a model to predict MVC from anthropometrical measurements will be presented.

  13. Multifractal analysis of sEMG signal of the complex muscle activity

    CERN Document Server

    Trybek, Paulina; Nowakowski, Michal; Machura, Lukasz

    2014-01-01

    The neuro--muscular activity while working on laparoscopic trainer is the example of the complex (and complicated) movement. This class of problems are still waiting for the proper theory which will be able to describe the actual properties of the muscle performance. Here we consider the signals obtained from three states of muscle activity: at maximum contraction, during complex movements (at actual work) and in the completely relaxed state. In addition the difference between a professional and an amateur is presented. The Multifractal Detrended Fluctuation Analysis was used in description of the properties the kinesiological surface electromyographic signals (sEMG). We demonstrate the dissimilarity between each state of work for the selected group of muscles as well as between trained and untrained individuals.

  14. A note on the probability distribution function of the surface electromyogram signal.

    Science.gov (United States)

    Nazarpour, Kianoush; Al-Timemy, Ali H; Bugmann, Guido; Jackson, Andrew

    2013-01-01

    The probability density function (PDF) of the surface electromyogram (EMG) signals has been modelled with Gaussian and Laplacian distribution functions. However, a general consensus upon the PDF of the EMG signals is yet to be reached, because not only are there several biological factors that can influence this distribution function, but also different analysis techniques can lead to contradicting results. Here, we recorded the EMG signal at different isometric muscle contraction levels and characterised the probability distribution of the surface EMG signal with two statistical measures: bicoherence and kurtosis. Bicoherence analysis did not help to infer the PDF of measured EMG signals. In contrast, with kurtosis analysis we demonstrated that the EMG PDF at isometric, non-fatiguing, low contraction levels is super-Gaussian. Moreover, kurtosis analysis showed that as the contraction force increases the surface EMG PDF tends to a Gaussian distribution. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. Advanced biofeedback from surface electromyography signals using fuzzy system

    DEFF Research Database (Denmark)

    Samani, Afshin; Holtermann, Andreas; Søgaard, Karen

    2010-01-01

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

  16. Basic reporting and interpretation of surface EMG amplitude and mean power frequency: a reply to Vitgotsky, Ogborn, and Phillips.

    Science.gov (United States)

    Jenkins, Nathaniel D M; Housh, Terry J; Bergstrom, Haley C; Cochrane, Kristen C; Hill, Ethan C; Smith, Cory M; Johnson, Glen O; Schmidt, Richard J; Cramer, Joel T

    2016-03-01

    In this response, we addressed the specific issues raised by Vigotsky et al. and clarified (1) our methods and adherence to electromyographic signal reporting standards, (2) our interpretation of EMG amplitude, and (3) our interpretation of EMG mean power frequency.

  17. 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.

  18. 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…

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

    Directory of Open Access Journals (Sweden)

    Mohammadreza Balouchestani

    2014-12-01

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

  20. Surface EMG-based sketching recognition using two analysis windows and gene expression programming

    Directory of Open Access Journals (Sweden)

    Zhongliang Yang

    2016-10-01

    Full Text Available 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.

  1. EMG (Electromyography) (For Parents)

    Science.gov (United States)

    ... Late for the Flu Vaccine? Eating Disorders Arrhythmias EMG (Electromyogram) KidsHealth > For Parents > EMG (Electromyogram) Print A ... muscular dystrophy and nerve disorders. How Is an EMG Done? Muscles are stimulated by signals from nerve ...

  2. Wrist torque estimation during simultaneous and continuously changing movements: surface vs. untargeted intramuscular EMG.

    Science.gov (United States)

    Kamavuako, Ernest N; Scheme, Erik J; Englehart, Kevin B

    2013-06-01

    In this paper, the predictive capability of surface and untargeted intramuscular electromyography (EMG) was compared with respect to wrist-joint torque to quantify which type of measurement better represents joint torque during multiple degrees-of-freedom (DoF) movements for possible application in prosthetic control. Ten able-bodied subjects participated in the study. Surface and intramuscular EMG was recorded concurrently from the right forearm. The subjects were instructed to track continuous contraction profiles using single and combined DoF in two trials. The association between torque and EMG was assessed using an artificial neural network. Results showed a significant difference between the two types of EMG (P EMG (R(2) = 0.93 ± 0.03; PCC = 0.98 ± 0.01; RMSE = 8.7 ± 2.1%) was found to be superior compared with intramuscular EMG (R(2) = 0.80 ± 0.07; PCC = 0.93 ± 0.03; RMSE = 14.5 ± 2.9%). The higher values of PCC compared with R(2) indicate that both methods are able to track the torque profile well but have some trouble (particularly intramuscular EMG) in estimating the exact amplitude. The possible cause for the difference, thus the low performance of intramuscular EMG, may be attributed to the very high selectivity of the recordings used in this study.

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

    Science.gov (United States)

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

    2014-01-01

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

  4. Prosthetic hand control using motion discrimination from EMG signals.

    Science.gov (United States)

    Kurisu, Naoyuki; Tsujiuchi, Nobutaka; Koizumi, Takayuki

    2009-01-01

    In this report, we improve the motion discrimination method from electromyogram (EMG) for a prosthetic hand and propose prosthetic hand control. In the past, we proved that a motion discrimination method using conic models could discriminate three hand motions without the incorrect discriminations that the elbow motions cause. In this research, to increase discrimination accuracy of motion discrimination using conic models, we propose a feature extraction method using quadratic polynomials. Additionally, because many prosthetic hands using motion discrimination have constant motion speed that can't be controlled, we propose an angular velocity generation method using multiple regression models. We verified these methods by controlling the 3D hand model. In the experiment, the proposed method could discriminate five motions at a rate of above 90 percent without the incorrect discriminations that elbow motions cause. Moreover, the wrist joint angle of the 3D hand model could be controlled by standard variation of 3[deg] or less.

  5. Biomathematical pattern of EMG signal propagation in smooth muscle of the non-pregnant porcine uterus.

    Directory of Open Access Journals (Sweden)

    Malgorzata Domino

    Full Text Available Uterine contractions are generated by myometrial smooth muscle cells (SMCs that comprise most of the myometrial layer of the uterine wall. Aberrant uterine motility (i.e., hypo- or hyper-contractility or asynchronous contractions has been implicated in the pathogenesis of infertility due to the failure of implantation, endometriosis and abnormal estrous cycles. The mechanism whereby the non-pregnant uterus initiates spontaneous contractions remains poorly understood. The aim of the present study was to employ linear synchronization measures for analyzing the pattern of EMG signal propagation (direction and speed in smooth muscles of the non-pregnant porcine uterus in vivo using telemetry recording system. It has been revealed that the EMG signal conduction in the uterine wall of the non-pregnant sow does not occur at random but it rather exhibits specific directions and speed. All detectable EMG signals moved along the uterine horn in both cervico-tubal and tubo-cervical directions. The signal migration speed could be divided into the three main types or categories: i. slow basic migration rhythm (SBMR; ii. rapid basic migration rhythm (RBMR; and iii. rapid accessory migration rhythm (RAMR. In conclusion, the EMG signal propagation in smooth muscles of the porcine uterus in vivo can be assessed using a linear synchronization model. Physiological pattern of the uterine contractile activity determined in this study provides a basis for future investigations of normal and pathologicall myogenic function of the uterus.

  6. Biomathematical pattern of EMG signal propagation in smooth muscle of the non-pregnant porcine uterus.

    Science.gov (United States)

    Domino, Malgorzata; Pawlinski, Bartosz; Gajewski, Zdzislaw

    2017-01-01

    Uterine contractions are generated by myometrial smooth muscle cells (SMCs) that comprise most of the myometrial layer of the uterine wall. Aberrant uterine motility (i.e., hypo- or hyper-contractility or asynchronous contractions) has been implicated in the pathogenesis of infertility due to the failure of implantation, endometriosis and abnormal estrous cycles. The mechanism whereby the non-pregnant uterus initiates spontaneous contractions remains poorly understood. The aim of the present study was to employ linear synchronization measures for analyzing the pattern of EMG signal propagation (direction and speed) in smooth muscles of the non-pregnant porcine uterus in vivo using telemetry recording system. It has been revealed that the EMG signal conduction in the uterine wall of the non-pregnant sow does not occur at random but it rather exhibits specific directions and speed. All detectable EMG signals moved along the uterine horn in both cervico-tubal and tubo-cervical directions. The signal migration speed could be divided into the three main types or categories: i. slow basic migration rhythm (SBMR); ii. rapid basic migration rhythm (RBMR); and iii. rapid accessory migration rhythm (RAMR). In conclusion, the EMG signal propagation in smooth muscles of the porcine uterus in vivo can be assessed using a linear synchronization model. Physiological pattern of the uterine contractile activity determined in this study provides a basis for future investigations of normal and pathologicall myogenic function of the uterus.

  7. An examination of surface EMG for the assessment of muscle tension dysphonia.

    Science.gov (United States)

    Van Houtte, Evelyne; Claeys, Sofie; D'haeseleer, Evelien; Wuyts, Floris; Van Lierde, Kristiane

    2013-03-01

    Muscle tension dysphonia (MTD) is the pathological condition in which an excessive tension of the (para)laryngeal musculature leads to a disturbed voice. Surface electromyography (sEMG) was used to investigate differences in extralaryngeal muscles' tension in patients with MTD compared with normal speakers. sEMG was examined as a diagnostic tool to differentiate between patients with MTD and controls. Eighteen patients with MTD and 44 normal speakers were included in the study. All subjects were evaluated with videostroboscopy, voice assessment protocol, and sEMG. sEMG was performed on three locations of the anterior neck. Measurements were taken during silence, phonation tasks, and while reading, with comparisons made between both study groups. Patients with MTD did not express higher levels of sEMG during rest, phonation, or reading compared with normal speakers. There were no significant differences in sEMG values between males and females in both study groups. sEMG was not able to detect an increase in muscle tension in patients with MTD. The results of this study do not support the use of sEMG as a diagnostic tool for distinguishing patients with and without MTD. Clinical examination with laryngeal palpation, videostroboscopy, and dysphonia severity index remain the key investigations. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

  8. 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...

  9. Use of surface electromyography (EMG) in the diagnosis of childhood hypertonia: a pilot study.

    Science.gov (United States)

    Sanger, Terence D

    2008-06-01

    In children, increased tone in a joint can be caused by spasticity, dystonia, rigidity, or mechanical limitations such as contracture. Determination of the cause of hypertonia is important for selection of appropriate therapy, but distinction between the types of hypertonia is difficult in a clinical setting. We present results of a pilot test of the use of a portable surface electromyography (EMG) device for the evaluation of hypertonia. Seven children 5-17 years of age with hypertonia due to cerebral palsy were each examined by 6 clinicians, both with and without the use of surface EMG. The use of surface EMG resulted in an increase in interrater agreement as well as an increase in the self-reported confidence of the clinicians in their assessment. These results support the importance of further testing of surface EMG as an adjunct to the clinical examination of childhood hypertonia.

  10. 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,

  11. 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.

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

    Science.gov (United States)

    Nazmi, Nurhazimah; Abdul Rahman, Mohd Azizi; Yamamoto, Shin-Ichiroh; Ahmad, Siti Anom; Zamzuri, Hairi; Mazlan, Saiful Amri

    2016-01-01

    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. PMID:27548165

  13. 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

  14. Compression robuste du signal EMG par la transformee avec lec B ...

    African Journals Online (AJOL)

    Compression robuste du signal EMG par la transformee avec lec B-splines. PN Eloundou, P Ele, E Tonye. Abstract. No Abstract. Journal of the Cameroon Academy of Sciences Vol. 6 (3) 2006: pp. 195-206. Full Text: EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT.

  15. The linear synchronization measures of uterine EMG signals: Evidence of synchronized action potentials during propagation.

    Science.gov (United States)

    Domino, Malgorzata; Pawlinski, Bartosz; Gajewski, Zdzislaw

    2016-11-01

    Evaluation of synchronization between myoelectric signals can give new insights into the functioning of the complex system of porcine myometrium. We propose a model of uterine contractions according to the hypothesis of action potentials similarity which is possible to detect during propagation in the uterine wall. We introduce similarity measures based on the concept of synchronization as used in matching linear signals such as electromyographic (EMG) time series data. The aim was to present linear measures to assess synchronization between contractions in different topographic regions of the uterus. We use the cross-correlation function (ƒx,y[l], ƒy,z[l]) and the cross-coherence function (Cxy[ƒ], Cyz[ƒ]) to assess synchronization between three data series of a diestral uterine EMG bundles in porcine reproductive tract. Spontaneous uterine activity was recorded using telemetry method directly by three-channel transmitter and three silver bipolar needle electrodes sutured on different topographic regions of the reproductive tract in the sow. The results show the usefulness of the cross-coherence function in that synchronization between uterine horn and corpus uteri for multiple action potentials (bundles) could be observed. The EMG bundles synchronization may be used to investigate the direction and velocity of EMG signals propagation in porcine reproductive tract. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Differences in Contraction-Induced Hemodynamics and Surface EMG in Duchenne Muscular Dystrophy.

    Science.gov (United States)

    Van Ginderdeuren, Eva; Caicedo, Alexander; Taelmans, Joachim; Goemans, Nathalie; van den Hauwe, Marlen; Naulaers, Gunnar; Van Huffel, Sabine; Buyse, Gunnar

    2016-01-01

    Duchenne muscular dystrophy (DMD) is the most common and devastating type of muscular dystrophy worldwide. In this study we have investigated the potential of the combined use of non-invasive near-infrared spectroscopy (NIRS) and surface electromyography (sEMG) to assess contraction-induced changes in oxygenation and myoelectrical activity, respectively in the biceps brachii of eight DMD patients aged 9-12 years and 11 age-matched healthy controls. Muscle tissue oxygenation index (TOI), oxyhemoglobin (HbO2), and sEMG signals were continuously measured during a sustained submaximal contraction of 60% maximal voluntary isometric contraction, and post-exercise recovery period. Compared to controls, DMD subjects showed significantly smaller changes in TOI during the contraction. In addition, during the reoxygenation phase some dynamic parameters extracted from the HbO2 measurements were significantly different between the two groups, some of which were correlated with functional performances on a 6-min walking test. In conclusion, non-invasive continuous monitoring of skeletal muscle oxygenation by NIRS is feasible in young children, and significant differences in contraction-induced deoxygenation and reoxygenation patterns were observed between healthy controls and DMD children.

  17. Differences between surface EMG in male and female subjects evidenced by automatic analysis.

    Science.gov (United States)

    Cioni, R; Giannini, F; Paradiso, C; Battistini, N; Denoth, F; Navona, C; Starita, A

    1988-10-01

    40 healthy volunteers (20 males and 20 females) have been studied by an automatic analysis of their surface EMG. The power density spectrum (PDS) of the electromyographic signal, derived from the tibialis anterior muscle, was used to evaluate the RMS values of the EMG developed during maximal voluntary (Vc) and evoked (Vm) contractions. The ratios between Vc, calculated over each of 5 frequency bands (5-15, 20-40, 45-70, 75-110, 115-160 Hz), and the total Vc have also been calculated. No significant differences emerge in the Vm values for males and females, whereas the Vc values for female subjects are found to be significantly reduced (P less than 0.001) with respect to the corresponding values for males. Significant differences have also been found concerning the percentage distribution of power in the above mentioned frequency bands for men and women (P less than 0.001). It can thus, be hypothesized that there are two different modalities of motor unit recruitment and that different sociological and cultural traditions may be more important in producing these differences than sexually determined physiological differences.

  18. 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

  19. Design and testing of an under-actuated surface EMG-driven hand exoskeleton.

    Science.gov (United States)

    Lince, A; Celadon, N; Battezzato, A; Favetto, A; Appendino, S; Ariano, P; Paleari, M

    2017-07-01

    Stroke and other neurological pathologies are an increasing cause of hand impairment, involving expensive rehabilitative therapies. In this scenario, robotics applied to hand rehabilitation and assistance appears particularly promising in order to lower therapy costs and boost its efficacy. This work shows a recently conceived hand exoskeleton, from the design and realization to its preliminary evaluation. A control strategy based on surface electromyography (sEMG) signals is integrated: preliminary tests performed on healthy subjects show the validity of this choice. The testing protocol, applied on healthy subjects, demonstrated the robustness of the whole system, both in terms of mimicking a physiological distribution of finger forces across subjects, and of realizing an effective control strategy based on the user's intention.

  20. Power spectral analysis of surface electromyography (EMG) at matched contraction levels of the first dorsal interosseous muscle in stroke survivors.

    Science.gov (United States)

    Li, Xiaoyan; Shin, Henry; Zhou, Ping; Niu, Xun; Liu, Jie; Rymer, William Zev

    2014-05-01

    The objective of this study was to help assess complex neural and muscular changes induced by stroke using power spectral analysis of surface electromyogram (EMG) signals. Fourteen stroke subjects participated in the study. They were instructed to perform isometric voluntary contractions by abducting the index finger. Surface EMG signals were collected from the paretic and contralateral first dorsal interosseous (FDI) muscles with forces ranging from 30% to 70% maximum voluntary contraction (MVC) of the paretic muscle. Power spectral analysis was performed to characterize features of the surface EMG in paretic and contralateral muscles at matched forces. A Linear Mixed Model was applied to identify the spectral changes in the hemiparetic muscle and to examine the relation between spectral parameters and contraction levels. Regression analysis was performed to examine the correlations between spectral characteristics and clinical features. Differences in power spectrum distribution patterns were observed in paretic muscles when compared with their contralateral pairs. Nine subjects showed increased mean power frequency (MPF) in the contralateral side (>15 Hz). No evident spectrum difference was observed in 3 subjects. Only 2 subjects had higher MPF in the paretic muscle than the contralateral muscle. Pooling all subjects' data, there was a significant reduction of MPF in the paretic muscle compared with the contralateral muscle (paretic: 168.7 ± 7.6 Hz, contralateral: 186.1 ± 8.7 Hz, mean ± standard error, F=36.56, pEMG power spectrum did not confirm a significant correlation between the MPF and contraction force in either hand (F=0.7, p>0.5). There was no correlation between spectrum difference and Fugl-Meyer or Chedoke scores, or ratio of paretic and contralateral MVC (p>0.2). There appears to be complex muscular and neural processes at work post stroke that may impact the surface EMG power spectrum. The majority of the tested stroke subjects had lower MPF in

  1. 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.

  2. Does local immersion in thermo-neutral bath influence surface EMG measurements? Results of an experimental trial.

    Science.gov (United States)

    Kalpakcioglu, Banu; Candir, Fatma; Bernateck, Michael; Gutenbrunner, Christoph; Fischer, Michael J

    2009-12-01

    This study investigated the effect of water immersion on surface electromyography (EMG) signals recorded from the brachioradial muscle of 11 healthy subjects, both in a dry environment and a thermo-neutral forearm bath (36 degrees C). EMG measurements were registered in a sitting position, using waterproof electrodes under 3 conditions: relaxed muscle, maximum voluntary isometric contraction (MVC, 1s, grip test) and 70% of the MVC (5 s). In relaxed muscle, mean EMG values were significantly higher under immersion compared to the dry conditions (dry: 5.4+/-3.6 microV; water: 19.5+/-14.9 microV; p=0.014). In maximum voluntary isometric contraction, there was a significant difference, though not in the same direction (dry: 145.9+/-58.9 microV; water: 73.2+/-35.0 microV; p=0.003). Under 70% MVC, there was no difference between wet and dry conditions (dry: 102.4+/-75.0 microV; water: 100.4+/-65.3 microV; p=0.951). Results suggest that dry and underwater conditions influence EMG readings; however, the results are inconsistent. These findings indicate additional influences on resting muscle activity, as well as MVC. Further measurements with other muscle groups and different types of immersion are needed to clarify conflicting observations.

  3. Waterproofing EMG Instrumentation.

    Science.gov (United States)

    Benfield, Rebecca D; Newton, Edward R; Hortobágyi, Tibor

    2007-01-01

    While still experimental, measurement of external uterine electromyographic (EMG) activity is a more sensitive and noninvasive method for measuring uterine contractility in human labor than the methods currently used in clinical practice. Hydrotherapy is purported to improve contractility in labor, yet there have been no reports of abdominal uterine EMG activity measured during immersion. To test telemetric EMG equipment and different waterproofing techniques under dry and immersed conditions, the authors recorded surface EMG activity from the abdominal muscles of 11 healthy, nonpregnant women, 22 to 51 years of age. After attaching one pair of electrodes to the skin on either side of the umbilicus and applying the waterproofing material, the authors tested the signal by asking participants to perform a short series of leg lifts while seated in a chair to evoke abdominal muscle contractions. They were then immersed to the chest in a hydrotherapy tub while performing two to three leg lifts over 60 s every 5 min for 60 min with 20 lb of weight suspended from their ankles to counteract the buoyancy effect of water. EMG activity was continuously recorded. They then repeated the dry-measures sequence. While waterproofing remained intact, EMG signals were essentially unchanged between dry and wet conditions. Of the 11 waterproofing applications tested, 10 failed at some point. In the data from the successful application, EMG signals in both channels exhibited stable baselines throughout and an absence of low-frequency artifact. The development of this technique allows for the recording of external uterine EMG activity during hydrotherapy. The authors have begun using it to investigate the effects of hydrotherapy on uterine contractility during human labor.

  4. EMG Versus Torque Control of Human-Machine Systems: Equalizing Control Signal Variability Does not Equalize Error or Uncertainty.

    Science.gov (United States)

    Johnson, Reva E; Kording, Konrad P; Hargrove, Levi J; Sensinger, Jonathon W

    2017-06-01

    In this paper we asked the question: if we artificially raise the variability of torque control signals to match that of EMG, do subjects make similar errors and have similar uncertainty about their movements? We answered this question using two experiments in which subjects used three different control signals: torque, torque+noise, and EMG. First, we measured error on a simple target-hitting task in which subjects received visual feedback only at the end of their movements. We found that even when the signal-to-noise ratio was equal across EMG and torque+noise control signals, EMG resulted in larger errors. Second, we quantified uncertainty by measuring the just-noticeable difference of a visual perturbation. We found that for equal errors, EMG resulted in higher movement uncertainty than both torque and torque+noise. The differences suggest that performance and confidence are influenced by more than just the noisiness of the control signal, and suggest that other factors, such as the user's ability to incorporate feedback and develop accurate internal models, also have significant impacts on the performance and confidence of a person's actions. We theorize that users have difficulty distinguishing between random and systematic errors for EMG control, and future work should examine in more detail the types of errors made with EMG control.

  5. Acquisition and Analysis of EMG Signals to Recognize Multiple Hand Movements for Prosthetic Applications

    Directory of Open Access Journals (Sweden)

    Giuseppina Gini

    2012-01-01

    Full Text Available One of the main problems in developing active prosthesis is how to control them in a natural way. In order to increase the effectiveness of hand prostheses there is a need in better exploiting electromyography (EMG signals. After an analysis of the movements necessary for grasping, we individuated five movements for the wrist-hand mobility. Then we designed the basic electronics and software for the acquisition and the analysis of the EMG signals. We built a small size electronic device capable of registering them that can be integrated into a hand prosthesis. Among all the numerous muscles that move the fingers, we have chosen the ones in the forearm and positioned only two electrodes. To recognize the operation, we developed a classification system, using a novel integration of Artificial Neural Networks (ANN and wavelet features.

  6. [Data collection of signals in the multi-channel sEMG system of masticatory muscles and development and preliminary clinical application of an analytic system].

    Science.gov (United States)

    Du, Hongliang; Li, Xin; Li, Shan; Zhang, Rui; Song, Rong; Li, Lan; Wang, Wei; Kang, Hong

    2014-02-01

    The aim of this study was to design a simple, economic, with high Common Mode Rejection Ratio (CMRR), preamplifier and multi-channel masticatory muscle surface electromyography (sEMG) signal acquisition system assisting to diagnose temporomandibular disorders (TMD). We used the USB interface technology in the EMG data with the aid of the windows to operate system and graphical interface. Eight patients with TMD and eight controls were analyzed separately using this system. In this system, we analyzed sEMG by an optional combination of time domain, frequency domain, time-frequency, several spectral analysis, wavelets and other special algorithms under multi-parameter. Multi-channel sEMG System of Masticatory Muscles is a simple, economic system. It has high sensitivity and specificity. The sEMG signals were changed in patients with TMD. The system would pave the way for diagnosis TMD and help us to assess the treatment effect. A novel and objective method is provided for diagnosis and treatment of oral-maxillofacial disease and functional reconstruction.

  7. 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.

  8. Noise-assisted multivariate empirical mode decomposition for multichannel EMG signals.

    Science.gov (United States)

    Zhang, Yi; Xu, Peng; Li, Peiyang; Duan, Keyi; Wen, Yuexin; Yang, Qin; Zhang, Tao; Yao, Dezhong

    2017-08-23

    Ensemble Empirical Mode Decomposition (EEMD) has been popularised for single-channel Electromyography (EMG) signal processing as it can effectively extract the temporal information of the EMG time series. However, few papers examine the temporal and spatial characteristics across multiple muscle groups in relation to multichannel EMG signals. The experimental data was obtained from the Center for Machine Learning and Intelligent Systems, University of California Irvine (UCI). The data was donated by the Nueva Granada Military University and the Technopark node Manizales in Colombia. The databases of 11 male subjects from the healthy group were taken into the study. The subjects undergo three exercise programs, leg extension from a sitting position (sitting), flexion of the leg up (standing), and gait (walking), while four electrodes were placed on biceps femoris (BF), vastus medialis (VM), rectus femoris (RF), and semitendinosus (ST). Based on the experimental data, a comparative study is provided by assessing the Empirical Mode Decomposition (EMD)-based approaches, EEMD, Multivariate EMD (MEMD), and Noise-Assisted MEMD (NA-MEMD). The outcomes from these approaches are then quantitatively estimated on the basis of three criterions, the number of Intrinsic Mode Functions (IMFs), mode-alignment and mode-mixing. Both MEMD and NA-MEMD methods (except EEMD) can guarantee equal numbers of IMFs. For mode-alignment and mode-mixing, NA-MEMD is optimal compared with MEMD and EEMD, and MEMD is merely better than EEMD. This study proposes the NA-MEMD approach for multichannel EMG signal processing. This finding implies that NA-MEMD is effective for simultaneously analysing IMFs based frequency bands. It has a vital clinical implication in exploring the neuromuscular patterns that enable the multiple muscle groups to coordinate while performing the functional activities of daily living.

  9. 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.

  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. 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.

  12. 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

  13. The distribution and propagation pattern of motor unit action potentials studied by multi-channel surface EMG.

    Science.gov (United States)

    Yamada, M; Kumagai, K; Uchiyama, A

    1987-11-01

    We developed the multi-channel surface EMG system using a matrix-type of surface electrode and with the aid of digital signal processing. The subjects were 14 normals (4-50 years) and 2 patients with Duchenne muscular dystrophy (7 and 8 years). The biceps brachii and the tibialis anterior muscles were investigated. The location of the motor end-plates and the measurement of muscle fiber conduction velocity were evaluated by the time shift of bipolar EMG arrays along muscle fibers, or by the distribution map of averaged motor unit action potentials (MUAPs). The lateral extension of a motor unit could be also estimated from the changes of averaged MUAP's amplitudes in the distribution map. Moreover in the biceps of 2 patients with Duchenne dystrophy, the mean muscle fiber conduction velocities were reduced compared to normal subjects, and characteristic propagation patterns of action potentials were obtained. In the 2-dimensional or 3-dimensional distribution map of integrated monopolar EMGs, the high density area agreed with the motor end-plate band.

  14. Three-Dimensional Innervation Zone Imaging from Multi-Channel Surface EMG Recordings.

    Science.gov (United States)

    Liu, Yang; Ning, Yong; Li, Sheng; Zhou, Ping; Rymer, William Z; Zhang, Yingchun

    2015-09-01

    There is an unmet need to accurately identify the locations of innervation zones (IZs) of spastic muscles, so as to guide botulinum toxin (BTX) injections for the best clinical outcome. A novel 3D IZ imaging (3DIZI) approach was developed by combining the bioelectrical source imaging and surface electromyogram (EMG) decomposition methods to image the 3D distribution of IZs in the target muscles. Surface IZ locations of motor units (MUs), identified from the bipolar map of their MU action potentials (MUAPs) were employed as a prior knowledge in the 3DIZI approach to improve its imaging accuracy. The performance of the 3DIZI approach was first optimized and evaluated via a series of designed computer simulations, and then validated with the intramuscular EMG data, together with simultaneously recorded 128-channel surface EMG data from the biceps of two subjects. Both simulation and experimental validation results demonstrate the high performance of the 3DIZI approach in accurately reconstructing the distributions of IZs and the dynamic propagation of internal muscle activities in the biceps from high-density surface EMG recordings.

  15. Surface EMG Recording of the Perioral Reflexes: Preliminary Observations on Stutterers and Nonstutterers.

    Science.gov (United States)

    McClean, Michael D.

    1987-01-01

    Surface electrodes were used to describe the perioral reflexes in seven stutterers and five nonstutterers and electromyographic (EMG) recordings were obtained at electrode sites associated with the orbicularis oris inferior muscle and the depressor labia inferior muscle. A difference was noted in the pattern of reflex response between the two…

  16. 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.

  17. 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.

  18. SURFACE ELECTROMYOGRAPHY IN BIOMECHANICS: APPLICATIONS AND SIGNAL ANALYSIS ASPECTS

    Directory of Open Access Journals (Sweden)

    DEAK GRAłIELA-FLAVIA

    2009-12-01

    Full Text Available Surface electromyography (SEMG is a technique for detecting and recording the electrical activity of the muscles using surface electrodes. The EMG signal is used in biomechanics mainly as an indicator of the initiation of muscle activation, as an indicator of the force produced by a contracting muscle, and as an index ofthe fatigue occurring within a muscle. EMG, used as a method of investigation, can tell us if the muscle is active or not, if the muscle is more or less active, when it is on or off, how much active is it, and finally, if it fatigues.The purpose of this article is to discuss some specific EMG signal analysis aspects with emphasis on comparison type analysis and frequency fatigue analysis.

  19. 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.

  20. Surface EMG activity during REM sleep in Parkinson's disease correlates with disease severity.

    Science.gov (United States)

    Chahine, Lama M; Kauta, Shilpa R; Daley, Joseph T; Cantor, Charles R; Dahodwala, Nabila

    2014-07-01

    Over 40% of individuals with Parkinson's disease (PD) have rapid eye movement sleep behavior disorder (RBD). This is associated with excessive sustained (tonic) or intermittent (phasic) muscle activity instead of the muscle atonia normally seen during REM sleep. We examined characteristics of manually-quantitated surface EMG activity in PD to ascertain whether the extent of muscle activity during REM sleep is associated with specific clinical features and measures of disease severity. In a convenience sample of outpatients with idiopathic PD, REM sleep behavior disorder was diagnosed based on clinical history and polysomnogram, and severity was measured using the RBD sleep questionnaire. Surface EMG activity in the mentalis, extensor muscle group of the forearms, and anterior tibialis was manually quantitated. Percentage of REM time with excessive tonic or phasic muscle activity was calculated and compared across PD and RBD characteristics. Among 65 patients, 31 had confirmed RBD. In univariate analyses, higher amounts of surface EMG activity were associated with longer PD disease duration (srho = 0.34; p = 0.006) and greater disease severity (p REM sleep was associated with severity of both PD and RBD. This measure may be useful as a PD biomarker and, if confirmed, may aid in determining which PD patients warrant treatment for their dream enactment to reduce risk of injury. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2017-08-01

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

  2. Discrimination of Parkinsonian Tremor From Essential Tremor by Voting Between Different EMG Signal Processing Techniques

    Directory of Open Access Journals (Sweden)

    A Hossen

    2014-06-01

    Full Text Available Parkinson's disease (PD and essential tremor (ET are the two most common disorders that cause involuntary muscle shaking movements, or what is called "tremor”. PD is a neurodegenerative disease caused by the loss of dopamine receptors which control and adjust the movement of the body. On the other hand, ET is a neurological movement disorder which also causes tremors and shaking, but it is not related to dopamine receptor loss; it is simply a tremor. The differential diagnosis between these two disorders is sometimes difficult to make clinically because of the similarities of their symptoms; additionally, the available tests are complex and expensive. Thus, the objective of this paper is to discriminate between these two disorders with simpler, cheaper and easier ways by using electromyography (EMG signal processing techniques. EMG and accelerometer records of 39 patients with PD and 41 with ET were acquired from the Hospital of Kiel University in Germany and divided into a trial group and a test group. Three main techniques were applied: the wavelet-based soft-decision technique, statistical signal characterization (SSC of the spectrum of the signal, and SSC of the amplitude variation of the Hilbert transform. The first technique resulted in a discrimination efficiency of 80% on the trial set and 85% on the test set. The second technique resulted in an efficiency of 90% on the trial set and 82.5% on the test set. The third technique resulted in an 87.5% efficiency on the trial set and 65.5% efficiency on the test set. Lastly, a final vote was done to finalize the discrimination using these three techniques, and as a result of the vote, accuracies of 92.5%, 85.0% and 88.75% were obtained on the trial data, test data and total data, respectively.

  3. EMG responses to maintain stance during multidirectional surface translations

    Science.gov (United States)

    Henry, S. M.; Fung, J.; Horak, F. B.; Peterson, B. W. (Principal Investigator)

    1998-01-01

    To characterize muscle synergy organization underlying multidirectional control of stance posture, electromyographic activity was recorded from 11 lower limb and trunk muscles of 7 healthy subjects while they were subjected to horizontal surface translations in 12 different, randomly presented directions. The latency and amplitude of muscle responses were quantified for each perturbation direction. Tuning curves for each muscle were examined to relate the amplitude of the muscle response to the direction of surface translation. The latencies of responses for the shank and thigh muscles were constant, regardless of perturbation direction. In contrast, the latencies for another thigh [tensor fascia latae (TFL)] and two trunk muscles [rectus abdominis (RAB) and erector spinae (ESP)] were either early or late, depending on the perturbation direction. These three muscles with direction-specific latencies may play different roles in postural control as prime movers or as stabilizers for different translation directions, depending on the timing of recruitment. Most muscle tuning curves were within one quadrant, having one direction of maximal activity, generally in response to diagonal surface translations. Two trunk muscles (RAB and ESP) and two lower limb muscles (semimembranosus and peroneus longus) had bipolar tuning curves, with two different directions of maximal activity, suggesting that these muscle can play different roles as part of different synergies, depending on translation direction. Muscle tuning curves tended to group into one of three regions in response to 12 different directions of perturbations. Two muscles [rectus femoris (RFM) and TFL] were maximally active in response to lateral surface translations. The remaining muscles clustered into one of two diagonal regions. The diagonal regions corresponded to the two primary directions of active horizontal force vector responses. Two muscles (RFM and adductor longus) were maximally active orthogonal to

  4. 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.

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

    Science.gov (United States)

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

    2017-01-01

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

  6. 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.

  7. 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.

  8. 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

  9. Test-retest reliability of muscle fiber conduction velocity and fractal dimension of surface EMG during isometric contractions.

    Science.gov (United States)

    Beretta-Piccoli, Matteo; D'Antona, Giuseppe; Zampella, Cristian; Barbero, Marco; Clijsen, Ron; Cescon, Corrado

    2017-04-01

    The aim of this study was to determine the test-retest reliability of muscle fiber conduction velocity (CV) and fractal dimension (FD) obtained from multichannel surface electromyographic (sEMG) recordings. Forty healthy recreationally active subjects (20 men and 20 women) performed two elbow flexions on two trials with a 1 week interval. The first was a 20% maximal voluntary contraction (MVC) of 120 s, and the second at 60% MVC held until exhaustion. sEMG signals were detected from the biceps brachii, using bi-dimensional arrays. Initial values and slope of CV and FD were used for the reliability analysis. The intraclass correlation coefficient (ICC) values for the isometric contraction at 20% MVC were (-0.09) and 0.67 for CV and FD respectively; whereas the ICC values at 60% MVC were 0.78 and 0.82 for CV and FD respectively. The Bland Altman plots for the two isometric contractions showed a mean difference close to zero, with no evident outliers between the repeated measurements: at 20% MVC 0.001 53 for FD and  -0.0277 for CV, and at 60% MVC 0.006 66 for FD and 0.009 07 for CV. Overall, our findings suggest that during isometric fatiguing contractions, CV and FD slopes are reliable variables, with potential application in clinical populations.

  10. Complexity analysis of EMG signals for patients after stroke during robot-aided rehabilitation training using fuzzy approximate entropy.

    Science.gov (United States)

    Sun, Rui; Song, Rong; Tong, Kai-yu

    2014-09-01

    The paper presents a novel viewpoint to monitor the motor function improvement during a robot-aided rehabilitation training. Eight chronic poststroke subjects were recruited to attend the 20-session training, and in each session, subjects were asked to perform voluntary movements of elbow flexion and extension together with the robotic system. The robotic system was continuously controlled by the electromyographic (EMG) signal from the affected triceps. Fuzzy approximate entropy (fApEn) was applied to investigate the complexity of the EMG segment, and maximum voluntary contraction (MVC) during elbow flexion and extension was applied to reflect force generating capacity of the affected muscles. The results showed that the group mean fApEn of EMG signals from triceps and biceps increased significantly after the robot-aided rehabilitation training . There was also significant increase in maximum voluntary flexion and extension torques after the robot-aided rehabilitation training . There was significant correlation between fApEn of agonist and MVC , which implied that the increase of motorneuron number is one of factors that may explain the increase in muscle strength. These findings based on fApEn of the EMG signals expand the existing interpretation of training-induced function improvement in patients after stroke, and help us to understand the neurological change induced by the robot-aided rehabilitation training.

  11. 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

  12. Signal features of surface electromyography in advanced Parkinson's disease during different settings of deep brain stimulation.

    Science.gov (United States)

    Rissanen, Saara M; Ruonala, Verneri; Pekkonen, Eero; Kankaanpää, Markku; Airaksinen, Olavi; Karjalainen, Pasi A

    2015-12-01

    Electromyography (EMG) and acceleration (ACC) measurements are potential methods for quantifying efficacy of deep brain stimulation (DBS) treatment in Parkinson's disease (PD). The treatment efficacy depends on the settings of DBS parameters (pulse amplitude, frequency and width). This study quantified, if EMG and ACC signal features differ between different DBS settings and if DBS effect is unequal between different muscles. EMGs were measured from biceps brachii (BB) and tibialis anterior (TA) muscles of 13 PD patients. ACCs were measured from wrists. Measurements were performed during seven different settings of DBS and analyzed using methods based on spectral analysis, signal morphology and nonlinear dynamics. The results showed significant within-subject differences in the EMG signal kurtosis, correlation dimension, recurrence rate and EMG-ACC coherence between different DBS settings for BB but not for TA muscles. Correlations between EMG feature values and clinical rest tremor and rigidity scores were weak but significant. Surface EMG features differed between different DBS settings and DBS effect was unequal between upper and lower limb muscles. EMG changes pointed to previously defined optimal settings in most of patients, which should be quantified even more deeply in the upcoming studies. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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

    Science.gov (United States)

    Mesin, Luca

    2015-02-01

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

  14. 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

  15. 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.

  16. Spatial correlation of high density EMG signals provides features robust to electrode number and shift in pattern recognition for myocontrol.

    Science.gov (United States)

    Stango, Antonietta; Negro, Francesco; Farina, Dario

    2015-03-01

    Research on pattern recognition for myoelectric control has usually focused on a small number of electromyography (EMG) channels because of better clinical acceptability and low computational load with respect to multi-channel EMG. However, recently, high density (HD) EMG technology has substantially improved, also in practical usability, and can thus be applied in myocontrol. HD EMG provides several closely spaced recordings in multiple locations over the skin surface. This study considered the use of HD EMG for controlling upper limb prostheses, based on pattern recognition. In general, robustness and reliability of classical pattern recognition systems are influenced by electrode shift in dons and doff, and by the presence of malfunctioning channels. The aim of this study is to propose a new approach to attenuate these issues. The HD EMG grid of electrodes is an ensemble of sensors that records data spatially correlated. The experimental variogram, which is a measure of the degree of spatial correlation, was used as feature for classification, contrary to previous approaches that are based on temporal or frequency features. The classification based on the variogram was tested on seven able-bodied subjects and one subject with amputation, for the classification of nine and seven classes, respectively. The performance of the proposed approach was comparable with the classic methods based on time-domain and autoregressive features (average classification accuracy over all methods ∼ 95% for nine classes). However, the new spatial features demonstrated lower sensitivity to electrode shift ( ± 1 cm) with respect to the classic features . When even just one channel was noisy, the classification accuracy dropped by ∼ 10% for all methods. However, the new method could be applied without any retraining to a subset of high-quality channels whereas the classic methods require retraining when some channels are omitted. In conclusion, the new spatial feature space

  17. 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.

  18. Electromyography (EMG)

    Science.gov (United States)

    Tests and Procedures Electromyography (EMG) By Mayo Clinic Staff Electromyography (EMG) is a diagnostic procedure to assess the health of ... Woodward Lips Patient Education Center. About your electromyography (EMG) examination. Rochester, Minn.: Mayo Foundation for Medical Education ... . Mayo ...

  19. Seizure Onset Detection based on one sEMG channel

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sandor; Hoppe, Karsten

    2011-01-01

    We present a new method to detect seizure onsets of tonic-clonic epileptic seizures based on surface electromyography (sEMG) data. The proposed method is generic and based on a single channel making it ideal for a small detection or monitoring device. The sEMG signal is high-pass filtered with a ...

  20. A novel hidden Markov model-based pattern discrimination method with the anomaly detection for EMG signals.

    Science.gov (United States)

    Mukaeda, Takayuki; Shima, Keisuke

    2017-07-01

    This paper proposes a novel sequential pattern recognition method enabling calculation of a posteriori probability for learned and unlearned classes. In this approach, probability density functions of unlearned classes are incorporated in a hiddenMarkov model to classify undefined classes via model parameter estimation using given learning samples. The technique can be applied to various pattern recognition problems such as motion classification with electromyogram (EMG) signals and in support for disease diagnosis. In the experiments conducted, motion classification from EMG signals was implemented with three subjects for eight learned/unlearned forearm motions. The proposed method produced higher levels of classification performance (learned motions: 90.13%; unlearned motions: 91.25%) than previous approaches. The results demonstrated the effectiveness of the technique.

  1. Prediction of Above-elbow Motions in Amputees, based on Electromyographic(EMG Signals, Using Nonlinear Autoregressive Exogenous (NARX Model

    Directory of Open Access Journals (Sweden)

    Ali Akbar Akbari

    2014-08-01

    Full Text Available Introduction In order to improve the quality of life of amputees, biomechatronic researchers and biomedical engineers have been trying to use a combination of various techniques to provide suitable rehabilitation systems. Diverse biomedical signals, acquired from a specialized organ or cell system, e.g., the nervous system, are the driving force for the whole system. Electromyography(EMG, as an experimental technique,is concerned with the development, recording, and analysis of myoelectric signals. EMG-based research is making progress in the development of simple, robust, user-friendly, and efficient interface devices for the amputees. Materials and Methods Prediction of muscular activity and motion patterns is a common, practical problem in prosthetic organs. Recurrent neural network (RNN models are not only applicable for the prediction of time series, but are also commonly used for the control of dynamical systems. The prediction can be assimilated to identification of a dynamic process. An architectural approach of RNN with embedded memory is Nonlinear Autoregressive Exogenous (NARX model, which seems to be suitable for dynamic system applications. Results Performance of NARX model is verified for several chaotic time series, which are applied as input for the neural network. The results showed that NARX has the potential to capture the model of nonlinear dynamic systems. The R-value and MSE are  and  , respectively. Conclusion  EMG signals of deltoid and pectoralis major muscles are the inputs of the NARX  network. It is possible to obtain EMG signals of muscles in other arm motions to predict the lost functions of the absent arm in above-elbow amputees, using NARX model.

  2. 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.

  3. Evaluation of Applied Kinesiology meridian techniques by means of surface electromyography (sEMG: demonstration of the regulatory influence of antique acupuncture points

    Directory of Open Access Journals (Sweden)

    Moncayo Helga

    2009-05-01

    Full Text Available Abstract Background The use of Applied Kinesiology techniques based on manual muscle tests relies on the relationship between muscles and acupuncture meridians. Applied Kinesiology detects body dysfunctions based on changes in muscle tone. Muscle tonification or inhibition within the test setting can be achieved with selected acupoints. These acupoints belong to either the same meridian or related meridians. The aim of this study is to analyze muscle sedation and tonification by means of surface electromyography. Methods Manual muscle tests were carried out using standard Applied Kinesiology (AK techniques. The investigation included basic AK procedures such as sedation and tonification with specific acupoints. The sedation and tonification acupoints were selected from related meridians according to the Five Elements. The tonification effect of these acupoints was also tested while interfering effects were induced by manual stimulation of scars. The effects of selective neural therapy, i.e. individually tested and selected anesthetic agent, for the treatment of scars were also studied. The characteristics of muscle action were documented by surface electromyographys (sEMG. Results The sEMG data showed a diminution of signal intensity when sedation was used. Graded sedation resulted in a graded diminution of signal amplitude. Graded increase in signal amplitude was observed when antique acupuncture points were used for tonification. The tactile stretch stimulus of scars localized in meridian-independent places produced diminution of signal intensity on a reference muscle, similar to sedation. These changes, however, were not corrected by tonification acupoints. Correction of these interferences was achieved by lesion specific neural therapy with local anesthetics. Conclusion We demonstrated the central working principles, i.e. sedation and tonification, of Applied Kinesiology through the use of specific acupoints that have an influence on manual

  4. Evaluation of Applied Kinesiology meridian techniques by means of surface electromyography (sEMG): demonstration of the regulatory influence of antique acupuncture points.

    Science.gov (United States)

    Moncayo, Roy; Moncayo, Helga

    2009-05-29

    The use of Applied Kinesiology techniques based on manual muscle tests relies on the relationship between muscles and acupuncture meridians. Applied Kinesiology detects body dysfunctions based on changes in muscle tone. Muscle tonification or inhibition within the test setting can be achieved with selected acupoints. These acupoints belong to either the same meridian or related meridians. The aim of this study is to analyze muscle sedation and tonification by means of surface electromyography. Manual muscle tests were carried out using standard Applied Kinesiology (AK) techniques. The investigation included basic AK procedures such as sedation and tonification with specific acupoints. The sedation and tonification acupoints were selected from related meridians according to the Five Elements. The tonification effect of these acupoints was also tested while interfering effects were induced by manual stimulation of scars. The effects of selective neural therapy, i.e. individually tested and selected anesthetic agent, for the treatment of scars were also studied. The characteristics of muscle action were documented by surface electromyographys (sEMG). The sEMG data showed a diminution of signal intensity when sedation was used. Graded sedation resulted in a graded diminution of signal amplitude. Graded increase in signal amplitude was observed when antique acupuncture points were used for tonification. The tactile stretch stimulus of scars localized in meridian-independent places produced diminution of signal intensity on a reference muscle, similar to sedation. These changes, however, were not corrected by tonification acupoints. Correction of these interferences was achieved by lesion specific neural therapy with local anesthetics. We demonstrated the central working principles, i.e. sedation and tonification, of Applied Kinesiology through the use of specific acupoints that have an influence on manual muscle tests. Sedation decreases RMS signal in sEMG, whereas

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

    NARCIS (Netherlands)

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

    2009-01-01

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

  6. A new EMG frequency-based fatigue threshold test.

    Science.gov (United States)

    Hendrix, C Russell; Housh, Terry J; Johnson, Glen O; Mielke, Michelle; Camic, Clayton L; Zuniga, Jorge M; Schmidt, Richard J

    2009-06-30

    Theoretically, the critical torque (CT) and electromyographic mean power frequency fatigue threshold (EMG MPF(FT)) describe the maximal non-fatiguing isometric torque level. The purposes of this study were two-fold: (1) to determine if the mathematical model for estimating the EMG fatigue threshold (EMG(FT)) from the amplitude of the EMG signal was applicable to the frequency domain of the EMG signal to estimate a new fatigue threshold called the EMG MPF(FT); and (2) to compare the torque level derived from the CT test to that of the EMG MPF(FT) test for the vastus lateralis (VL) muscle during isometric muscle actions of the leg extensors. Nine adults (4 men and 5 women; mean+/-SD age=21.6+/-1.2 yr) performed three or four continuous, fatiguing, isometric muscle actions of the leg extensors at 30, 45, 60, and 75% of maximum voluntary isometric contraction (MVIC) to determine the time to exhaustion (T(lim)) values. The slope coefficient of the linear relationship between total isometric "work" (W(lim) in Nms=TorquexT(lim)) and T(lim) was defined as the CT. Surface EMG signals were recorded from the vastus lateralis (VL) muscle during each fatiguing isometric muscle action. The EMG MPF(FT) was defined as the y-intercept of the isometric torque versus slope coefficient (EMG MPF versus time) plot. There were no significant differences between CT (19.7+/-5.8%MVIC) and EMG MPF(FT) (21.4+/-8.7%MVIC). These findings provided indirect validation of the EMG MPF(FT) test.

  7. 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.

  8. Modeling of surface myoelectric signals--Part II: Model-based signal interpretation.

    Science.gov (United States)

    Merletti, R; Roy, S H; Kupa, E; Roatta, S; Granata, A

    1999-07-01

    Experimental electromyogram (EMG) data from the human biceps brachii were simulated using the model described in [10] of this work. A multichannel linear electrode array, spanning the length of the biceps, was used to detect monopolar and bipolar signals, from which double differential signals were computed, during either voluntary or electrically elicited isometric contractions. For relatively low-level voluntary contractions (10%-30% of maximum force) individual firings of three to four-different motor units were identified and their waveforms were closely approximated by the model. Motor unit parameters such as depth, size, fiber orientation and length, location of innervation and tendonous zones, propagation velocity, and source width were estimated using the model. Two applications of the model are described. The first analyzes the effects of electrode rotation with respect to the muscle fiber direction and shows the possibility of conduction velocity (CV) over- and under-estimation. The second focuses on the myoelectric manifestations of fatigue during a sustained electrically elicited contraction and the interrelationship between muscle fiber CV, spectral and amplitude variables, and the length of the depolarization zone. It is concluded that a) surface EMG detection using an electrode array, when combined with a model of signal propagation, provides a useful method for understanding the physiological and anatomical determinants of EMG waveform characteristics and b) the model provides a way for the interpretation of fatigue plots.

  9. An EMG Decomposition System Aimed at Detailed Analysis of Motor Unit Activity

    DEFF Research Database (Denmark)

    Nikolic, Mile; Krarup, Christian; Dahl, Kristian

    1997-01-01

    Decomposition of EMG signals by segmentation oftime signals, clustering and resolving of compoundsegments.......Decomposition of EMG signals by segmentation oftime signals, clustering and resolving of compoundsegments....

  10. Validation of surface EMG as a measure of intravaginal and intra-abdominal activity: implications for biofeedback-assisted Kegel exercises.

    Science.gov (United States)

    Workman, D E; Cassisi, J E; Dougherty, M C

    1993-01-01

    This study validates surface EMG as a measure of pelvic muscle and abdominal activity by showing its high correlation to internal pressure data. Using standardized scores, between-subjects correlation of perineal EMG and intravaginal pressure was r = .75, and the correlation of abdominal EMG and intra-abdominal pressure was r = .72. Discriminant validity was also demonstrated by showing low correlation between standardized abdominal and perineal EMG measurements (r = .10). A repeated measures multivariate analysis of variance demonstrated that visual and auditory biofeedback of EMG during pelvic floor contractions increases intravaginal pressure when compared with trials without biofeedback. Potential benefits of fabric electrodes include reduced invasiveness and risk and the ease with which patients can utilize this technology for home practice.

  11. 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.

  12. 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.

  13. Normalization of the trapezius sEMG signal - a reliability study on women with and without neck-shoulder pain.

    Science.gov (United States)

    Cid, Marina Machado; Januario, Leticia Bergamin; Zanca, Gisele Garcia; Mattiello, Stela Marcia; Oliveira, Ana Beatriz

    2017-09-29

    To evaluate within- and between-days reliability of two normalization methods of surface electromyography (sEMG) recordings of the trapezius muscle. Nineteen women were allocated into 2 groups (healthy and with neck-shoulder pain). The sEMG was recorded in two sessions with 7 days in between sessions. The four portions of the trapezius muscle (the clavicular and acromial fibers of the upper trapezius, the middle and the lower trapezius) were evaluated during maximal and submaximal isometric voluntary contractions. The within- and between-days reliability of both maximal and submaximal contractions were assessed through Intraclass Correlation Coefficient (ICC(2,1) was used for within-day analyses of both maximal and submaximal contractions, and for between-days analyses of maximal contractions while ICC(2,3) was used for between-days analyses of submaximal contractions), Coefficient of Variation, Standard Error of Measurement, and Bland-Altman analysis. In general, submaximal contractions presented higher within-day reliability, with higher ICC values (e.g., middle trapezius - mean of 0.97), smaller Coefficient of Variation and Standard Error of Measurement ranges compared to maximal contractions (ICC values, e.g. for middle trapezius - mean of 0.94) in both groups. The same pattern was observed for between-days analyses, with submaximal contractions presenting higher ICC values (e.g., middle trapezius - mean of 0.84), smaller Coefficient of Variation and Standard Error of Measurement ranges than maximal contractions (ICC values, e.g. for middle trapezius - mean of 0.73) in both groups. Submaximal contractions are recommended for normalization procedures of trapezius sEMG, in both subjects with neck-shoulder pain and healthy individuals. Copyright © 2017 Associação Brasileira de Pesquisa e Pós-Graduação em Fisioterapia. Publicado por Elsevier Editora Ltda. All rights reserved.

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

    OpenAIRE

    Changcheng Wu; Hong Zeng; Aiguo Song; Baoguo Xu

    2017-01-01

    The estimation of the grip force and the 3D push-pull force (push and pull force in the three dimension space) from the electromyogram (EMG) signal is of great importance in the dexterous control of the EMG prosthetic hand. In this paper, an action force estimation method which is based on the eight channels of the surface EMG (sEMG) and the Generalized Regression Neural Network (GRNN) is proposed to meet the requirements of the force control of the intelligent EMG prosthetic hand. Firstly, t...

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

    Science.gov (United States)

    Li, Yanran; Zhang, Xu; Gong, Yanan; Cheng, Ying; Gao, Xiaoping; Chen, Xiang

    2017-03-13

    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.

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

    Science.gov (United States)

    Ji, Yi; Sun, Shanlin; Xie, Hong-Bo

    2017-06-01

    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.

  17. 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.

  18. Robust Features Of Surface Electromyography Signal

    Science.gov (United States)

    Sabri, M. I.; Miskon, M. F.; Yaacob, M. R.

    2013-12-01

    Nowadays, application of robotics in human life has been explored widely. Robotics exoskeleton system are one of drastically areas in recent robotic research that shows mimic impact in human life. These system have been developed significantly to be used for human power augmentation, robotics rehabilitation, human power assist, and haptic interaction in virtual reality. This paper focus on solving challenges in problem using neural signals and extracting human intent. Commonly, surface electromyography signal (sEMG) are used in order to control human intent for application exoskeleton robot. But the problem lies on difficulty of pattern recognition of the sEMG features due to high noises which are electrode and cable motion artifact, electrode noise, dermic noise, alternating current power line interface, and other noise came from electronic instrument. The main objective in this paper is to study the best features of electromyography in term of time domain (statistical analysis) and frequency domain (Fast Fourier Transform).The secondary objectives is to map the relationship between torque and best features of muscle unit activation potential (MaxPS and RMS) of biceps brachii. This project scope use primary data of 2 male sample subject which using same dominant hand (right handed), age between 20-27 years old, muscle diameter 32cm to 35cm and using single channel muscle (biceps brachii muscle). The experiment conduct 2 times repeated task of contraction and relaxation of biceps brachii when lifting different load from no load to 3kg with ascending 1kg The result shows that Fast Fourier Transform maximum power spectrum (MaxPS) has less error than mean value of reading compare to root mean square (RMS) value. Thus, Fast Fourier Transform maximum power spectrum (MaxPS) show the linear relationship against torque experience by elbow joint to lift different load. As the conclusion, the best features is MaxPS because it has the lowest error than other features and show

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

    Directory of Open Access Journals (Sweden)

    Paulo Feodrippe

    2012-06-01

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

  20. Feature extraction of the first difference of EMG time series for EMG pattern recognition.

    Science.gov (United States)

    Phinyomark, Angkoon; Quaine, Franck; Charbonnier, Sylvie; Serviere, Christine; Tarpin-Bernard, Franck; Laurillau, Yann

    2014-11-01

    This paper demonstrates the utility of a differencing technique to transform surface EMG signals measured during both static and dynamic contractions such that they become more stationary. The technique was evaluated by three stationarity tests consisting of the variation of two statistical properties, i.e., mean and standard deviation, and the reverse arrangements test. As a result of the proposed technique, the first difference of EMG time series became more stationary compared to the original measured signal. Based on this finding, the performance of time-domain features extracted from raw and transformed EMG was investigated via an EMG classification problem (i.e., eight dynamic motions and four EMG channels) on data from 18 subjects. The results show that the classification accuracies of all features extracted from the transformed signals were higher than features extracted from the original signals for six different classifiers including quadratic discriminant analysis. On average, the proposed differencing technique improved classification accuracies by 2-8%. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. Reliability of EMG normalisation methods for upper-limb muscles.

    Science.gov (United States)

    Rota, Samuel; Rogowski, Isabelle; Champely, Stéphane; Hautier, Christophe

    2013-01-01

    The study investigated different electromyographic (EMG) normalisation methods for upper-limb muscles. This assessment aimed at comparing the EMG amplitude and the reliability of EMG values obtained with each method. Eighteen male tennis players completed isometric maximal voluntary contractions and dynamic strength exercises (push-ups and chin-ups) on three separate test sessions over at least 7 days. Surface EMG activity of nine upper body muscles was recorded. For each muscle, an analysis of variance for repeated measures was used to compare maximal EMG amplitudes between test conditions. The intra-class correlation coefficient, the coefficient of variation and the standard error of measurement were calculated to determine the EMG reliability of each condition. On the basis of a compromise between maximal EMG amplitude and high reliability, the chin-ups appeared to be the optimal normalisation method for M. latissimus dorsi, M. posterior deltoid, M. biceps brachii, M. flexor carpi radialis and M. extensor carpi radialis. The push-ups seemed relevant to normalise M. anterior deltoid and M. triceps brachii activity, while isometric maximal voluntary contraction remained the most appropriate method for M. pectoralis major and M. middle deltoid. Thus, original methods are proposed to normalise EMG signal of upper-limb muscles.

  2. Elbow joint angle and elbow movement velocity estimation using NARX-multiple layer perceptron neural network model with surface EMG time domain parameters.

    Science.gov (United States)

    Raj, Retheep; Sivanandan, K S

    2017-01-01

    Estimation of elbow dynamics has been the object of numerous investigations. In this work a solution is proposed for estimating elbow movement velocity and elbow joint angle from Surface Electromyography (SEMG) signals. Here the Surface Electromyography signals are acquired from the biceps brachii muscle of human hand. Two time-domain parameters, Integrated EMG (IEMG) and Zero Crossing (ZC), are extracted from the Surface Electromyography signal. The relationship between the time domain parameters, IEMG and ZC with elbow angular displacement and elbow angular velocity during extension and flexion of the elbow are studied. A multiple input-multiple output model is derived for identifying the kinematics of elbow. A Nonlinear Auto Regressive with eXogenous inputs (NARX) structure based multiple layer perceptron neural network (MLPNN) model is proposed for the estimation of elbow joint angle and elbow angular velocity. The proposed NARX MLPNN model is trained using Levenberg-marquardt based algorithm. The proposed model is estimating the elbow joint angle and elbow movement angular velocity with appreciable accuracy. The model is validated using regression coefficient value (R). The average regression coefficient value (R) obtained for elbow angular displacement prediction is 0.9641 and for the elbow anglular velocity prediction is 0.9347. The Nonlinear Auto Regressive with eXogenous inputs (NARX) structure based multiple layer perceptron neural networks (MLPNN) model can be used for the estimation of angular displacement and movement angular velocity of the elbow with good accuracy.

  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

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

  4. EMG-force relation in the first dorsal interosseous muscle of patients with amyotrophic lateral sclerosis.

    Science.gov (United States)

    Jahanmiri-Nezhad, Faezeh; Hu, Xiaogang; Suresh, Nina L; Rymer, William Z; Zhou, Ping

    2014-01-01

    The relationship between surface electromyography (EMG) and muscle force is essential to assess muscle function and its deficits. However, few studies have explored the EMG-force relation in patients with amyotrophic lateral sclerosis (ALS). The purpose of this study was to examine the EMG-force relation in ALS subjects and its alteration in comparison with healthy control subjects. Surface EMG and force signals were recorded while 10 ALS and 10 age-matched healthy control subjects produced isometric voluntary contractions in the first dorsal interosseous (FDI) muscle over the full range of activation. A linear fit of the EMG-force relation was evaluated through the normalized root mean square error (RMSE) between the experimental and predicted EMG amplitudes. The EMG-force relation was compared between the ALS and the healthy control subjects. With a linear fit, the normalized RMSE between the experimental and predicted EMG amplitudes was 9.6 ± 3.6% for the healthy control subjects and 12.3 ± 8.0% for the ALS subjects. The slope of the linear fit was 2.9 ± 2.2 μVN-1 for the ALS subjects and was significantly shallower (p 0.05). A linear fit can be used to well describe the EMG-force relation for the FDI muscle of both ALS and healthy control subjects. A variety of processes may work together in ALS that can adversely affect the EMG-force relation.

  5. Measurement of distal EMG signals using a wearable device for reading facial expressions.

    Science.gov (United States)

    Gruebler, Anna; Suzuki, Kenji

    2010-01-01

    In this paper we present a quantitative analysis of electrode positions on the side of the face for facial expression recognition using facial bioelectrical signals. We show that distal electrode locations on areas of low facial mobility have a strong amplitude and are correlated to signals captured in the traditional positions on top of the facial muscles. We report on electrode position choice as well successful facial expression identification using computational methods. We also propose a wearable interface device that can detect facial bioelectrical signals distally in a continuous manner while being unobtrusive to the user. The proposed device can be worn on the side of the face and capture signals that are considered to be a mixture of facial electromyographic signals and other bioelectrical signals. Finally we show the design of an interface that can be comfortably worn by the user and makes facial expression recognition possible.

  6. Real-time processing of EMG signals for bionic arm purposes

    Science.gov (United States)

    Olid Dominguez, Ferran; Wawrzyniak, Zbigniew M.

    2016-09-01

    This paper is connected with the problem of prostheses, that have always been a necessity for the human being. Bio-physiological signals from muscles, electromyographic signals have been collected, analyzed and processed in order to implement a real-time algorithm which is capable of differentiation of two different states of a bionic hand: open and closed. An algorithm for real-time electromyographic signal processing with almost no false positives is presented and it is explained that in bio-physiological experiments proper signal processing is of great importance.

  7. Selection of Phase Space Reconstruction Parameters for EMG Signals of the Uterus

    Directory of Open Access Journals (Sweden)

    Brzozowska Ewelina

    2016-12-01

    Full Text Available Biological time series have a finite number of samples with noise included in them. Because of this fact, it is not possible to reconstruct phase space in an ideal manner. One kind of biomedical signals are electrohisterographical (EHG datasets, which represent uterine muscle contractile activity. In the process of phase space reconstruction, the most important thing is suitable choice of the method for calculating the time delay τ and embedding dimension d, which will reliably reconstruct the original signal. The parameters used in digital signal processing are key to arranging adequate parameters of the analysed attractor embedded in the phase space. The aim of this paper is to present a method employed for phase space reconstruction for EHG signals that will make it possible for their further analysis to be carried out.

  8. Reliability of the diaphragmatic compound muscle action potential evoked by cervical magnetic stimulation and recorded via chest wall surface EMG.

    Science.gov (United States)

    Welch, Joseph F; Mildren, Robyn L; Zaback, Martin; Archiza, Bruno; Allen, Grayson P; Sheel, A William

    2017-09-01

    Stimulation of the phrenic nerve via cervical magnetic stimulation (CMS) elicits a compound muscle action potential (CMAP) that allows for assessment of diaphragm activation. The reliability of CMS to evoke the CMAP recorded by chest wall surface EMG has yet to be comprehensively examined. CMS was performed on healthy young males (n=10) and females (n=10). Surface EMG electrodes were placed on the right and left hemi-diaphragm between the 6-8th intercostal spaces. CMAPs were analysed for: latency, duration, peak-to-peak amplitude, and area. Reliability within and between experimental sessions was assessed using intraclass correlation coefficients (ICC). Bilateral (right-left) and sex-based (male-female) comparisons were also made (independent samples t-test). All CMAP characteristics demonstrated high reproducibility within (ICCs>0.96) and between (ICCs>0.89) experimental sessions. No statistically significant bilateral or sex-based differences were found (p>0.05). CMS is a reliable and non-invasive method to evaluate phrenic nerve conduction. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Zhou Ping

    2012-10-01

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

  10. Man-machine interface system for neuromuscular training and evaluation based on EMG and MMG signals.

    Science.gov (United States)

    de la Rosa, Ramon; Alonso, Alonso; Carrera, Albano; Durán, Ramon; Fernández, Patricia

    2010-01-01

    This paper presents the UVa-NTS (University of Valladolid Neuromuscular Training System), a multifunction and portable Neuromuscular Training System. The UVa-NTS is designed to analyze the voluntary control of severe neuromotor handicapped patients, their interactive response, and their adaptation to neuromuscular interface systems, such as neural prostheses or domotic applications. Thus, it is an excellent tool to evaluate the residual muscle capabilities in the handicapped. The UVa-NTS is composed of a custom signal conditioning front-end and a computer. The front-end electronics is described thoroughly as well as the overall features of the custom software implementation. The software system is composed of a set of graphical training tools and a processing core. The UVa-NTS works with two classes of neuromuscular signals: the classic myoelectric signals (MES) and, as a novelty, the myomechanic signals (MMS). In order to evaluate the performance of the processing core, a complete analysis has been done to classify its efficiency and to check that it fulfils with the real-time constraints. Tests were performed both with healthy and selected impaired subjects. The adaptation was achieved rapidly, applying a predefined protocol for the UVa-NTS set of training tools. Fine voluntary control was demonstrated to be reached with the myoelectric signals. And the UVa-NTS demonstrated to provide a satisfactory voluntary control when applying the myomechanic signals.

  11. Man-Machine Interface System for Neuromuscular Training and Evaluation Based on EMG and MMG Signals

    Directory of Open Access Journals (Sweden)

    Patricia Fernández

    2010-12-01

    Full Text Available This paper presents the UVa-NTS (University of Valladolid Neuromuscular Training System, a multifunction and portable Neuromuscular Training System. The UVa-NTS is designed to analyze the voluntary control of severe neuromotor handicapped patients, their interactive response, and their adaptation to neuromuscular interface systems, such as neural prostheses or domotic applications. Thus, it is an excellent tool to evaluate the residual muscle capabilities in the handicapped. The UVa-NTS is composed of a custom signal conditioning front-end and a computer. The front-end electronics is described thoroughly as well as the overall features of the custom software implementation. The software system is composed of a set of graphical training tools and a processing core. The UVa-NTS works with two classes of neuromuscular signals: the classic myoelectric signals (MES and, as a novelty, the myomechanic signals (MMS. In order to evaluate the performance of the processing core, a complete analysis has been done to classify its efficiency and to check that it fulfils with the real-time constraints. Tests were performed both with healthy and selected impaired subjects. The adaptation was achieved rapidly, applying a predefined protocol for the UVa-NTS set of training tools. Fine voluntary control was demonstrated to be reached with the myoelectric signals. And the UVa-NTS demonstrated to provide a satisfactory voluntary control when applying the myomechanic signals.

  12. High-pass filtering to remove electrocardiographic interference from torso EMG recordings.

    Science.gov (United States)

    Redfern, M; Hughes, R; Chaffin, D

    1993-01-01

    Removal of electrocardiographic (ECG) contamination of electromyographic (EMG) signals from torso muscles is often attempted by high-pass filtering. This study investigated the effects of the cut-off frequency used in this high-pass filtering technique on the resulting EMG signal. Surface EMGs were recorded on five subjects from the rectus abdominis, external oblique, and erector spinae muscles. These signals were then digitally high-pass filtered at cut-off frequencies of 10, 30, and 60 Hz. Integration and power analyses of the filtered EMGs were subsequently performed. It was found that an increase in the cut-off frequency affects the integrated EMG signal by (1) reducing the ECG contamination, (2) decreasing the amplitude, and (3) smoothing the signal. It was concluded that the use of a high-pass filter is effective in reducing ECG interference in integrated EMG recordings, and a cut-off frequency of approximately 30 Hz was optimal. Electromyographic recordings of torso muscles are often used in the development of low-back biomechanical models. Unfortunately, these recordings are usually contaminated by electrocardiographic interference. High-pass filtering methods are sometimes used to diminish the influence of ECG from surface EMGs; however, the effects of these filters on the recorded and processed EMG have not been reported. The findings show that high-pass filtering is effective in reducing ECG contamination and motion artefact from integrated EMGs when the appropriate cut-off frequency is used. Inappropriate cut-off frequencies lead to either incomplete ECG removal or excess filtering of the EMG signal. Copyright © 1993. Published by Elsevier Ltd.

  13. Surface EMG during the Push-up plus Exercise on a Stable Support or Swiss Ball: Scapular Stabilizer Muscle Exercise.

    Science.gov (United States)

    Seo, Sung-Hwa; Jeon, In-Ho; Cho, Yong-Ho; Lee, Hyun-Gi; Hwang, Yoon-Tae; Jang, Jee-Hun

    2013-07-01

    [Purpose] Scapular stabilizer strengthening exercise is crucial for shoulder rehabilitation. The purpose of this study was to compare two types of push-up plus exercises, on a stable and unstable bases of support, using surface electromyography (EMG), to suggest an effective shoulder rehabilitation program. [Subjects and Methods] Ten healthy men volunteered for this study. All volunteers performed two sets of push-up plus exercise (standard push up and knee push up) on stable and unstable bases of support. The muscle activities of five important scapular stabilizer muscles (upper trapezius, middle trapezius, lower trapezius, serratus anterior, latissimus dorsi) were recorded during the exercise. [Results] The upper trapezius showed greater mean electric activation amplitude in the scapular retraction posture than in the scapular protraction posture, and the serratus anterior showed greater mean electric activation amplitude in the scapular protraction posture than in the scapular retraction posture. The root-mean-square normalized EMG values of the muscles were greater during the exercise performed on the unstable support than those on the stable support. [Conclusion] The standard push-up plus exercise on an unstable base of support helps to increase muscle activity, especially those of the upper/middle trapezius and serratus anterior.

  14. Analysis of maximal isometric force and EMG signal in lower limb exercise. 10.5007/1980-0037.2011v13n6p429

    OpenAIRE

    Cleiton Silva Correa; Bruna Gonçalves Cordeiro da Silva; Cristine Lima Alberton; Eurico Nestor Wilhelm Neto; Antonio Carlos de Moraes; Claudia Silveira Lima; Ronei Silveira Pinto

    2011-01-01

    The aim of this study was to compare maximal isometric force (MIF) and the electrical activity of the vastus medialis, vastus lateralis, rectus femoris, gluteus maximus and biceps femoris long head muscles between maximal voluntary contractions (MVC) performed at different joint angles, and to identify the most suitable positions to normalize the electromyography (EMG) signals from each of these muscles when they are activated under dynamic conditions. Ten men ranging in age from 20 to 30 yea...

  15. Power spectrum of the rectified EMG: when and why is rectification beneficial for identifying neural connectivity?

    Science.gov (United States)

    Negro, Francesco; Keenan, Kevin; Farina, Dario

    2015-06-01

    Objective. The identification of common oscillatory inputs to motor neurons in the electromyographic (EMG) signal power spectrum is often preceded by EMG rectification for enhancing the low-frequency oscillatory components. However, rectification is a nonlinear operator and its influence on the EMG signal spectrum is not fully understood. In this study, we aim at determining when EMG rectification is beneficial in the study of oscillatory inputs to motor neurons. Approach. We provide a full mathematical description of the power spectrum of the rectified EMG signal and the influence of the average shape of the motor unit action potentials on it. We also provide a validation of these theoretical results with both simulated and experimental EMG signals. Main results. Simulations using an advanced computational model and experimental results demonstrated the accuracy of the theoretical derivations on the effect of rectification on the EMG spectrum. These derivations proved that rectification is beneficial when assessing the strength of low-frequency (delta and alpha bands) common synaptic inputs to the motor neurons, when the duration of the action potentials is short, and when the level of cancellation is relatively low. On the other hand, rectification may distort the estimation of common synaptic inputs when studying higher frequencies (beta and gamma), in a way dependent on the duration of the action potentials, and may introduce peaks in the coherence function that do not correspond to physiological shared inputs. Significance. This study clarifies the conditions when rectifying the surface EMG is appropriate for studying neural connectivity.

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

    Science.gov (United States)

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

    2013-01-01

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

  17. 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.

  18. 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.

  19. 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

    2014-01-01

    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 (r2=0.62, P0.05) and upper part of the muscle belly (r2=0.29, PEMG 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.

  20. Kinematical and EMG-classifications of a fencing attack.

    Science.gov (United States)

    Frère, J; Göpfert, B; Nüesch, C; Huber, C; Fischer, M; Wirz, D; Friederich, N F

    2011-01-01

    8 expert fencers were studied with a 3-dimensional motion analysis system. Each subject performed 10 flèche attacks toward a standardized target. Surface electromyography signals (EMG) were recorded of the deltoid pars clavicularis, infraspinatus and triceps brachii caput laterale muscles of the weapon arm. The recorded EMGs were averaged using EMG wavelet-transformation software. 4 phases were defined based on the arm kinematics and used to classify fencers into 2 groups. A first group of 4 fencers showed an early maximal elbow extension (Early MEE) whereas the second group presented a late maximal elbow extension (Late MEE). 2 EMG-classifications were based on this kinematical classification, one in the time-domain and the other in the frequency-domain by using the spherical classification. The time-domain EMG-classification showed a significantly ( P=0.03) higher normalized deltoid intensity for the Early MEE group (91 ± 18%) than the Late MEE group (36 ± 13%) in the attack phase. The spherical classification revealed that the activity of all the muscles was significantly classified (recognition rate 75%, P=0.04) between the 2 groups. This study of EMG and kinematics of the weapon upper limb in fencing proposes several classifications, which implies a relationship between kinematic strategies, muscular activations and fencing success. © Georg Thieme Verlag KG Stuttgart · New York.

  1. Independence Between Two Channels of Surface Electromyogram Signal to Measure the Loss of Motor Units

    Directory of Open Access Journals (Sweden)

    Arjunan Sridhar P.

    2015-06-01

    Full Text Available This study has investigated the relationship in the connectivity of motor units in surface electromyogram (sEMG of biceps brachii muscle. It is hypothesized that with ageing, there is reduction/loss in number of motor units, leading to reduction in the independence between the channels of the recorded muscle activity. Two channels of sEMG were recorded during three levels of isometric muscle contraction: 50 %, 75 % and 100 % maximal voluntary contraction (MVC. 73 subjects (age range 20-70 participated in the experiments. The independence in channel index (ICI between the two sEMG recording locations was computed using the independent components and Frobenius norm. ANOVA Statistical analysis was performed to test the effect of age (loss of motor units and level of contraction on ICI. The results show that the ICI among the older cohort was significantly lower compared with the younger adults. This research study has shown that the reduction in number of motor units is reflected by the reduction in the ICI of the sEMG signal.

  2. 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.

  3. Specificity of surface-EMG on the intrinsic lumbar back muscles

    NARCIS (Netherlands)

    Vink, P.; Daanen, H. A M; Verbout, A.J.

    1989-01-01

    The cross-correlation coefficient functions (CCCFs) between twelve bipolar surface electrodes, placed symmetrically on the intrinsic lumbar back muscles (ILBM) were computed in order to estimate the amount of cross-talk. It was found that the CCCF values were mainly influenced by the distance

  4. 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.

  5. On the usability of intramuscular EMG for prosthetic control: a Fitts' Law approach.

    Science.gov (United States)

    Kamavuako, Ernest N; Scheme, Erik J; Englehart, Kevin B

    2014-10-01

    Previous studies on intramuscular EMG based control used offline data analysis. The current study investigates the usability of intramuscular EMG in two degree-of-freedom using a Fitts' Law approach by combining classification and proportional control to perform a task, with real time feedback of user performance. Nine able-bodied subjects participated in the study. Intramuscular and surface EMG signals were recorded concurrently from the right forearm. Five performance metrics (Throughput,Path efficiency, Average Speed, Overshoot and Completion Rate) were used for quantification of usability. Intramuscular EMG based control performed significantly better than surface EMG for Path Efficiency (80.5±2.4% vs. 71.5±3.8%, P=0.004) and Overshoot (22.0±3.0% vs. 45.1±6.6%, P=0.01). No difference was found between Throughput and Completion Rate. However the Average Speed was significantly higher for surface (51.8±5.5%) than for intramuscular EMG (35.7±2.7%). The results obtained in this study imply that intramuscular EMG has great potential as control source for advanced myoelectric prosthetic devices. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Analysis of Muscle Fatigue Progression using Cyclostationary Property of Surface Electromyography Signals.

    Science.gov (United States)

    Karthick, P A; Venugopal, G; Ramakrishnan, S

    2016-01-01

    Analysis of neuromuscular fatigue finds various applications ranging from clinical studies to biomechanics. Surface electromyography (sEMG) signals are widely used for these studies due to its non-invasiveness. During cyclic dynamic contractions, these signals are nonstationary and cyclostationary. In recent years, several nonstationary methods have been employed for the muscle fatigue analysis. However, cyclostationary based approach is not well established for the assessment of muscle fatigue. In this work, cyclostationarity associated with the biceps brachii muscle fatigue progression is analyzed using sEMG signals and Spectral Correlation Density (SCD) functions. Signals are recorded from fifty healthy adult volunteers during dynamic contractions under a prescribed protocol. These signals are preprocessed and are divided into three segments, namely, non-fatigue, first muscle discomfort and fatigue zones. Then SCD is estimated using fast Fourier transform accumulation method. Further, Cyclic Frequency Spectral Density (CFSD) is calculated from the SCD spectrum. Two features, namely, cyclic frequency spectral area (CFSA) and cyclic frequency spectral entropy (CFSE) are proposed to study the progression of muscle fatigue. Additionally, degree of cyclostationarity (DCS) is computed to quantify the amount of cyclostationarity present in the signals. Results show that there is a progressive increase in cyclostationary during the progression of muscle fatigue. CFSA shows an increasing trend in muscle fatiguing contraction. However, CFSE shows a decreasing trend. It is observed that when the muscle progresses from non-fatigue to fatigue condition, the mean DCS of fifty subjects increases from 0.016 to 0.99. All the extracted features found to be distinct and statistically significant in the three zones of muscle contraction (p < 0.05). It appears that these SCD features could be useful in the automated analysis of sEMG signals for different neuromuscular conditions.

  7. Analysis of maximal isometric force and EMG signal in lower limb exercise. 10.5007/1980-0037.2011v13n6p429

    Directory of Open Access Journals (Sweden)

    Cleiton Silva Correa

    2011-11-01

    Full Text Available The aim of this study was to compare maximal isometric force (MIF and the electrical activity of the vastus medialis, vastus lateralis, rectus femoris, gluteus maximus and biceps femoris long head muscles between maximal voluntary contractions (MVC performed at different joint angles, and to identify the most suitable positions to normalize the electromyography (EMG signals from each of these muscles when they are activated under dynamic conditions. Ten men ranging in age from 20 to 30 years, who were familiar with strength training exercise, were studied. MVC at different joint angles of the knee extensors and flexors (0°, 60°, 90° and hip extensors (-30°, 0°, 60° and flexors (90°, 120° were tested. The MIF values differed significantly between the 60° knee flexion and 60° and 90° knee extension positions (p0.05. Significantly higher EMG values were only observed for the rectus femoris muscle at 90° knee extension (p0.05. These results suggest that the 60° knee joint flexion position is the most suitable for assessment of knee extension and flexion MIF, and that all positions tested in this study are suitable for the assessment of hip flexion and extension.

  8. Factors governing the form of the relation between muscle force and the EMG: a simulation study.

    Science.gov (United States)

    Zhou, Ping; Rymer, William Zev

    2004-11-01

    The dependence of the form of the EMG-force relation on key motoneuron and muscle properties was explored using a simulation approach. Surface EMG signals and isometric forces were simulated using existing motoneuron pool, muscle force, and surface EMG models, based primarily on reported properties of the first dorsal interosseous (FDI) muscle in humans. Our simulation results indicate that the relation between electrical and mechanical properties of the individual motor unit level plays the dominant role in determining the overall EMG amplitude-force relation of the muscle, while the underlying motor unit firing rate strategy appears to be a less important factor. However, different motor unit firing rate strategies result in substantially different relations between counts of the numbers of motoneuron discharges and the isometric force. Our simulation results also show that EMG amplitude (estimated as the average rectified value) increases as a result of synchronous discharges of different motor units within the pool, but the magnitude of this increase is determined primarily by the action potential duration of the synchronized motor units. Furthermore, when the EMG effects are normalized to their maximum levels, motor unit synchrony does not exert significant effects on the form of the EMG-force relation, provided that the synchrony level is held similar at different excitation levels.

  9. 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.

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

    Science.gov (United States)

    Ishii, Tomohiro; Narita, Noriyuki; Endo, Hiroshi

    2016-06-01

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

  11. A real-time, practical sensor fault-tolerant module for robust EMG pattern recognition.

    Science.gov (United States)

    Zhang, Xiaorong; Huang, He

    2015-02-19

    Unreliability of surface EMG recordings over time is a challenge for applying the EMG pattern recognition (PR)-controlled prostheses in clinical practice. Our previous study proposed a sensor fault-tolerant module (SFTM) by utilizing redundant information in multiple EMG signals. The SFTM consists of multiple sensor fault detectors and a self-recovery mechanism that can identify anomaly in EMG signals and remove the recordings of the disturbed signals from the input of the pattern classifier to recover the PR performance. While the proposed SFTM has shown great promise, the previous design is impractical. A practical SFTM has to be fast enough, lightweight, automatic, and robust under different conditions with or without disturbances. This paper presented a real-time, practical SFTM towards robust EMG PR. A novel fast LDA retraining algorithm and a fully automatic sensor fault detector based on outlier detection were developed, which allowed the SFTM to promptly detect disturbances and recover the PR performance immediately. These components of SFTM were then integrated with the EMG PR module and tested on five able-bodied subjects and a transradial amputee in real-time for classifying multiple hand and wrist motions under different conditions with different disturbance types and levels. The proposed fast LDA retraining algorithm significantly shortened the retraining time from nearly 1 s to less than 4 ms when tested on the embedded system prototype, which demonstrated the feasibility of a nearly "zero-delay" SFTM that is imperceptible to the users. The results of the real-time tests suggested that the SFTM was able to handle different types of disturbances investigated in this study and significantly improve the classification performance when one or multiple EMG signals were disturbed. In addition, the SFTM could also maintain the system's classification performance when there was no disturbance. This paper presented a real-time, lightweight, and automatic

  12. Generating Control Commands From Gestures Sensed by EMG

    Science.gov (United States)

    Wheeler, Kevin R.; Jorgensen, Charles

    2006-01-01

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

  13. 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.

  14. EMG-force relations during isometric contractions of the first dorsal interosseous muscle after stroke.

    Science.gov (United States)

    Zhou, Ping; Li, Xiaoyan; Rymer, William Zev

    2013-01-01

    This study examines the electromyogram (EMG)-force relations observed in the first dorsal interosseous (FDI) muscle of hemiparetic stroke survivors. Fourteen stroke subjects were instructed to perform different levels of index finger abduction using their paretic and contralateral hands, respectively. Surface EMG and force signals were recorded from the FDI muscle. The EMG-force relation was constructed using linear regression of the EMG amplitude and force measurements. We found that there were diverse changes in the slope of the EMG-force relations in paretic muscles compared with contralateral muscles, with significant increases and decreases being observed relative to the contralateral side. Regression analysis did not verify strong correlations between the ratio of paretic and contralateral muscle EMG-force slopes and any clinical parameters. These findings suggest that there appear to be different types of processes (eg, motor unit control property changes, muscle fiber atrophy, spinal motoneuron degeneration, muscle fiber reinnervation, etc) at work post stroke that may impact the EMG-force relations and that may be present in varying degree in any given stroke survivor.

  15. Neural adaptations in isometric contractions with EMG and force biofeedback

    OpenAIRE

    Francisco Locks; Heleodório Honorato dos Santos; Luis Carlos Carvalho; Lígia Raquel Ortiz Gomes Stolt; José Jamacy de Almeida Ferreira

    2015-01-01

    This study aimed to evaluate the quadriceps femoris neural adaptations during isometric contractions using force and electromyogram (EMG) signals as visual biofeedback. Forty-two participants were randomly assigned to three groups: EMG group, tested with EMG biofeedback; Force group, tested with force biofeedback; and Control group, tested without biofeedback. Evaluations were performed pre (baseline) and post-tests to determine the maximum force and EMG amplitude during maximal voluntary iso...

  16. 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.

  17. Perineal Surface Electromyography Does Not Typically Demonstrate Expected Relaxation During Normal Voiding

    Science.gov (United States)

    Kirby, Anna C.; Nager, Charles W.; Litman, Heather J.; FitzGerald, Mary P.; Kraus, Stephen; Norton, Peggy; Sirls, Larry; Rickey, Leslie; Wilson, Tracey; Dandreo, Kimberly J.; Shepherd, Jonathan; Zimmern, Philippe

    2015-01-01

    Aims To describe perineal surface patch electromyography (EMG) activity during urodynamics (UDS) and compare activity between filling and voiding phases and to assess for a relationship between preoperative EMG activity and postoperative voiding symptoms. Methods 655 women underwent standardized preoperative UDS that included perineal surface EMG prior to undergoing surgery for stress urinary incontinence. Pressure-flow studies were evaluated for abdominal straining and interrupted flow. Quantitative EMG values were extracted from 10 predetermined time-points and compared between fill and void. Qualitative EMG activity was assessed for the percent of time EMG was active during fill and void and for the average amplitude of EMG during fill compared to void. Postoperative voiding dysfunction was defined as surgical revision or catheterization more than 6 weeks after surgery. Fisher’s exact test with a 5% two-sided significance level was used to assess differences in EMG activity and postoperative voiding dysfunction. Results 321 UDS had interpretable EMG studies, of which 131 (41%) had EMG values at all 10 predetermined and annotated time-points. Quantitative and qualitative EMG signals during flow were usually greater than during fill. The prevalence of postoperative voiding dysfunction in subjects with higher preoperative EMG activity during void was not significantly different. Results were similar in the 42 subjects who had neither abdominal straining during void nor interrupted flow. Conclusions Perineal surface patch EMG did not measure expected pelvic floor and urethral sphincter relaxation during voiding. Preoperative EMG did not predict patients at risk for postoperative voiding dysfunction. PMID:21560157

  18. EOG-sEMG Human Interface for Communication

    Directory of Open Access Journals (Sweden)

    Hiroki Tamura

    2016-01-01

    Full Text Available 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%.

  19. 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%.

  20. 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

    2014-01-01

    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. PMID:24844608

  1. 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.

  2. 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.

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

    NARCIS (Netherlands)

    Lobo Prat, J.; Janssen, Mariska M.H.P.; Koopman, Bart F.J.M.; Stienen, Arno H.A.; De Groot, Imelda J.M.

    2017-01-01

    Background: Robotic arm supports aim at improving the quality of life for adults with Duchenne muscular dystrophy (DMD) by augmenting their residual functional abilities. A critical component of robotic arm supports is the control interface, as is it responsible for the human-machine interaction.

  4. 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.

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

    Science.gov (United States)

    Supuk, Tamara Grujic; Skelin, Ana Kuzmanic; Cic, Maja

    2014-01-01

    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. PMID:24811078

  6. Towards optimal multi-channel EMG electrode configurations in muscle force estimation: a high density EMG study.

    NARCIS (Netherlands)

    Staudenmann, D.; Kingma, I.; Stegeman, D.F.; Dieen, J.H. van

    2005-01-01

    Surface EMG is an important tool in biomechanics, kinesiology and neurophysiology. In neurophysiology the concept of high-density EMG (HD-EMG), using two dimensional electrode grids, was developed for the measurement of spatiotemporal activation patterns of the underlying muscle and its motor units

  7. Low-cost assistive device for hand gesture recognition using sEMG

    Science.gov (United States)

    Kainz, Ondrej; Cymbalák, Dávid; Kardoš, Slavomír.; Fecil'ak, Peter; Jakab, František

    2016-07-01

    In this paper a low-cost solution for surface EMG (sEMG) signal retrieval is presented. The principal goal is to enable reading the temporal parameters of muscles activity by a computer device, with its further processing. Paper integrates design and deployment of surface electrodes and amplifier following the prior researches. Bearing in mind the goal of creating low-cost solution, the Arduino micro-controller was utilized for analog-to-digital conversion and communication. The software part of the system employs support vector machine (SVM) to classify the EMG signal, as acquired from sensors. Accuracy of the proposed solution achieves over 90 percent for six hand movements. Proposed solution is to be tested as an assistive device for several cases, involving people with motor disabilities and amputees.

  8. The detection of long-range correlations of operation force and sEMG with multifractal detrended fluctuation analysis.

    Science.gov (United States)

    Li, Fan; Li, Dongxu; Wang, Chunhui; Chen, Shanguang; Lv, Ming; Wang, Miao

    2015-01-01

    This paper explores the application of multifractal detrended fluctuation analysis (MF-DFA) on the nonlinear characteristics of correlation between operation force and surface electromyography (sEMG), which is an applied frontier of human neuromuscular system activity. We established cross-correlation functions between the signal of force and four typical sEMG time-frequency domain index sequences (force-sEMG cross-correlation sequences), and dealt with the sequences with MF-DFA. In addition, we demonstrated that the force-sEMG cross-correlation sequences have strong statistical self-similarity and the fractal characteristic of the signal spectrum is similar to 1/f noise or fractional Brownian motion.

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

    Science.gov (United States)

    Zhou, Ping; Zev Rymer, William

    2004-12-01

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

  10. 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.

  11. 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.

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

    NARCIS (Netherlands)

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

    2007-01-01

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

  13. Neural adaptations in isometric contractions with EMG and force biofeedback

    Directory of Open Access Journals (Sweden)

    Francisco Locks

    2015-03-01

    Full Text Available This study aimed to evaluate the quadriceps femoris neural adaptations during isometric contractions using force and electromyogram (EMG signals as visual biofeedback. Forty-two participants were randomly assigned to three groups: EMG group, tested with EMG biofeedback; Force group, tested with force biofeedback; and Control group, tested without biofeedback. Evaluations were performed pre (baseline and post-tests to determine the maximum force and EMG amplitude during maximal voluntary isometric contraction (MVIC. The tests consisted of series of MVICs in which the participants were encouraged to surpass the force or EMG thresholds determined at baseline. The vastus lateralis EMG amplitude and knee extensor force increased significantly in all groups when compared the baseline and post-test evaluations values (p < .05. EMG percentage gain was significantly different between Force and Control groups (p < .01, while force percentage gain was not different between groups. Force biofeedback was more effective in producing neural adaptations.

  14. 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.

  15. Nicotine and elevated body temperature reduce the complexity of the genioglossus and diaphragm EMG signals in rats during early maturation

    Science.gov (United States)

    Akkurt, David; Akay, Yasemin M.; Akay, Metin

    2009-10-01

    In this paper, we examined the effect of nicotine exposure and increased body temperature on the complexity (dynamics) of the genioglossus muscle (EMGg) and the diaphragm muscle (EMGdia) to explore the effects of nicotine and hyperthermia. Nonlinear dynamical analysis of the EMGdia and EMGg signals was performed using the approximate entropy method on 15 (7 saline- and 8 nicotine-treated) juvenile rats (P25-P35) and 19 (11 saline- and 8 nicotine-treated) young adult rats (P36-P44). The mean complexity values were calculated over the ten consecutive breaths using the approximate entropy method during mild elevated body temperature (38 °C) and severe elevated body temperature (39-40 °C) in two groups. In the first (nicotine) group, rats were treated with single injections of nicotine enough to produce brain levels of nicotine similar to those achieved in human smokers (2.5 (mg kg-1)/day) until the recording day. In the second (control) group, rats were treated with injections of saline, beginning at postnatal 5 days until the recording day. Our results show that warming the rat by 2-3 °C and nicotine exposure significantly decreased the complexity of the EMGdia and EMGg for the juvenile age group. This reduction in the complexity of the EMGdia and EMGg for the nicotine group was much greater than the normal during elevated body temperatures. We speculate that the generalized depressive effects of nicotine exposure and elevated body temperature on the respiratory neural firing rate and the behavior of the central respiratory network could be responsible for the drastic decrease in the complexity of the EMGdia and EMGg signals, the outputs of the respiratory neural network during early maturation.

  16. Signal Integrity Applications of an EBG Surface

    Directory of Open Access Journals (Sweden)

    MATEKOVITS, L.

    2015-05-01

    Full Text Available Electromagnetic band-gap (EBG surfaces have found applications in mitigation of parallel-plate noise that occurs in high speed circuits. A 2D periodic structure previously introduced by the same authors is dimensioned here for adjusting EBG parameters in view of meeting applications requirements by decreasing the phase velocity of the propagating waves. This adjustment corresponds to decreasing the lower bound of the EBG spectra. The positions of the EBGs' in frequency are determined through full-wave simulation, by solving the corresponding eigenmode equation and by imposing the appropriate boundary conditions on all faces of the unit cell. The operation of a device relying on a finite surface is also demonstrated. Obtained results show that the proposed structure fits for the signal integrity related applications as verified also by comparing the transmission along a finite structure of an ideal signal line and one with an induced discontinuity.

  17. Enhanced Propagating Surface Plasmon Signal Detection

    Energy Technology Data Exchange (ETDEWEB)

    Gong, Yu; Joly, Alan G.; El-Khoury, Patrick Z.; Hess, Wayne P.

    2016-12-21

    Overcoming the dissipative nature of propagating surface plasmons (PSPs) is pre-requisite to realizing functional plasmonic circuitry, in which large bandwidth signals can be manipulated over length scales far-below the diffraction limit of light. To this end, we report on a novel PSP enhanced signal detection technique achieved in an all-metallic substrate. We take advantage of two strategically spatio-temporally separated phase-locked femtosecond laser pulses, incident onto lithographically patterned PSP coupling structures. We follow PSP propagation with joint femtosecond temporal and nanometer spatial resolution in a time-resolved non-linear photoemission electron microscopy scheme. Initially, a PSP signal wave packet is launched from a hole etched into the silver surface from where it propagates through an open trench structure and is decoded through the use of a timed probe pulse. FDTD calculations demonstrate that PSP signal waves may traverse open trenches in excess of 10 microns in diameter, thereby allowing remote detection even through vacuum regions. This arrangement results in a 10X enhancement in photoemission relative to readout from the bare metal surface. The enhancement is attributed to an all-optical homodyne detection technique that mixes signal and reference PSP waves in a non-linear scheme. Larger readout trenches achieve higher readout levels, however reduced transmission through the trench limits the trench size to 6 microns for maximum readout levels. However, the use of an array of trenches increases the maximum enhancement to near 30X. The attainable enhancement factor may be harnessed to achieve extended coherent PSP propagation in ultrafast plasmonic circuitry.

  18. The Location of Peak Upper Trapezius Muscle Activity During Submaximal Contractions is not Associated With the Location of Myofascial Trigger Points: New Insights Revealed by High-density Surface EMG.

    Science.gov (United States)

    Barbero, Marco; Falla, Deborah; Mafodda, Luca; Cescon, Corrado; Gatti, Roberto

    2016-12-01

    To apply topographical mapping of the electromyography (EMG) amplitude recorded from the upper trapezius muscle to evaluate the distribution of activity and the location of peak activity during a shoulder elevation task in participants with and without myofascial pain and myofascial trigger points (MTrP) and compare this location with the site of the MTrP. Thirteen participants with myofascial pain and MTrP in the upper trapezius muscle and 12 asymptomatic individuals participated. High-density surface EMG was recorded from the upper trapezius muscle using a matrix of 64 surface electrodes aligned with an anatomic landmark system (ALS). Each participant performed a shoulder elevation task consisting of a series of 30 s ramped contractions to 15% or 60% of their maximal voluntary contraction (MVC) force. Topographical maps of the EMG average rectified value were computed and the peak EMG amplitude during the ramped contractions was identified and its location determined with respect to the ALS. The location of the MTrP was also determined relative to the ALS and Spearman correlation coefficients were used to examine the relationship between MTrP and peak EMG amplitude location. The location of the peak EMG amplitude was significantly (PEMG amplitude during the ramped contractions at either force level (15%: rs=0.039, P=0.9; 60%: rs=-0.087, P=0.778). People with myofascial pain and MTrP displayed a caudal shift of the distribution of upper trapezius muscle activity compared with asymptomatic individuals during a submaximal shoulder elevation task. For the first time, we show that the location of peak muscle activity is not associated with the location of the MTrP.

  19. 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.

  20. 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.

  1. 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...

  2. Wideband EMG telemetry system

    Science.gov (United States)

    Rosatino, S. A.; Westbrook, R. M.

    1979-01-01

    Miniature, individual crystal-controlled RF transmitters located in EMG pressure sensors simplifies multichannel EMG telemetry for electronic gait monitoring. Transmitters which are assigned operating frequencies within 174 - 216 MHz band have linear frequency response from 20 - 2000 Hz and operate over range of 15 m.

  3. EMG-based speech recognition using hidden markov models with global control variables.

    Science.gov (United States)

    Lee, Ki-Seung

    2008-03-01

    It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model.

  4. Electromyostimulation and EMG real time device with muscle fatigue estimation

    OpenAIRE

    Yochum, Maxime; Bakir, Toufik; Binczak, Stéphane; Lepers, Romuald

    2012-01-01

    International audience; This study presents a system composed of an electromyostimulation (ES) and an electromyograph (EMG) modules which analyze in real time EMG during ES and proposes a new method based on wavelet decomposition to analyze changes in M wave. It leads to introduce a new muscular fatigue index. Different methods to filter the EMG noise are then compared. The results show that this new index gives reliable and robust results even when noise corrupts significantly the signal.

  5. 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.

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

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sandor; Wolf, Peter

    2012-01-01

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

  7. Evaluation of sonomyography (SMG) for control compared with electromyography (EMG) in a discrete target tracking task.

    Science.gov (United States)

    Guo, Jing-Yi; Zheng, Yong-Ping; Kenney, Laurence P; Xie, Hong-Bo

    2009-01-01

    Most of the commercial upper-limb externally powered prosthetic devices are controlled by electromyography (EMG) signals. We previously proposed using the real-time change of muscle thickness detected using ultrasound, namely sonomyography (SMG), for the control of prostheses. In this study, we compared the performance of subjects using 1-D SMG signal and surface EMG signal, using a discrete target tracking protocol involving a series of letter cancellation tasks. Each task involved using grip force, EMG or SMG from a wrist extensor muscle to move a cursor to one of 5 locations on a computer screen, at the first four of which were located a letter and last of which was a word of "NEXT". The target was defined by the location showing the letter "E" and, once the subject reached this target, they were instructed to "cancel" the E from the screen, using a button operated by the contralateral hand. A paired t-test revealed that the percentage of letters correctly cancelled with force/angle and SMG signal in isometric force control, and with SMG in wrist extension were significantly higher than with EMG (PEMG for prosthetic control.

  8. Evaluation of Head Orientation and Neck Muscle EMG Signals as Command Inputs to a Human-Computer Interface for Individuals with High Tetraplegia

    Science.gov (United States)

    Williams, Matthew R.; Kirsch, Robert F.

    2013-01-01

    We investigated the performance of three user interfaces for restoration of cursor control in individuals with tetraplegia: head orientation, EMG from face and neck muscles, and a standard computer mouse (for comparison). Subjects engaged in a 2D, center-out, Fitts’ Law style task and performance was evaluated using several measures. Overall, head orientation commanded motion resembled mouse commanded cursor motion (smooth, accurate movements to all targets), although with somewhat lower performance. EMG commanded movements exhibited a higher average speed, but other performance measures were lower, particularly for diagonal targets. Compared to head orientation, EMG as a cursor command source was less accurate, was more affected by target direction and was more prone to overshoot the target. In particular, EMG commands for diagonal targets were more sequential, moving first in one direction and then the other rather than moving simultaneous in the two directions. While the relative performance of each user interface differs, each has specific advantages depending on the application. PMID:18990652

  9. 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...

  10. 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 < 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 assisting subjects in

  11. 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

  12. 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...

  13. Gesture Based Control and EMG Decomposition

    Science.gov (United States)

    Wheeler, Kevin R.; Chang, Mindy H.; Knuth, Kevin H.

    2005-01-01

    This paper presents two probabilistic developments for use with Electromyograms (EMG). First described is a new-electric interface for virtual device control based on gesture recognition. The second development is a Bayesian method for decomposing EMG into individual motor unit action potentials. This more complex technique will then allow for higher resolution in separating muscle groups for gesture recognition. All examples presented rely upon sampling EMG data from a subject's forearm. The gesture based recognition uses pattern recognition software that has been trained to identify gestures from among a given set of gestures. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time from moving averages of EMG. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard. Moving averages of EMG do not provide easy distinction between fine muscle groups. To better distinguish between different fine motor skill muscle groups we present a Bayesian algorithm to separate surface EMG into representative motor unit action potentials. The algorithm is based upon differential Variable Component Analysis (dVCA) [l], [2] which was originally developed for Electroencephalograms. The algorithm uses a simple forward model representing a mixture of motor unit action potentials as seen across multiple channels. The parameters of this model are iteratively optimized for each component. Results are presented on both synthetic and experimental EMG data. The synthetic case has additive white noise and is compared with known components. The experimental EMG data was obtained using a custom linear electrode array designed for this study.

  14. EMG evaluation of hip adduction exercises for soccer players

    DEFF Research Database (Denmark)

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

    2014-01-01

    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...

  15. Fitts' Law Evaluation of a Passive Rotation Paradigm for Two-Dimensional Cursor Control with a Single sEMG Signal

    OpenAIRE

    Skavhaug, Ida-Maria; Lyons, Kenneth R.; Muroff, Shira D.; Chen, Huanchun; Barry, Lauran; Korte, Bryce; Joshi, Sanjay S.

    2016-01-01

    Human-computer interfaces aim to restore some lost independence for individuals with disabilities by allowing them to act on the environment through alternative means. Here, we report performance by four able-bodied pilot subjects on a human-computer interface, which is based on a single surface electromyography signal recorded from the temporalis muscle on the head. The experimental task was 'Center Out' model, where a cursor was directed from the center of a screen to targets of varying siz...

  16. 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.

  17. 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. PMID:28220058

  18. Can muscle coordination be precisely studied by surface electromyography?

    Science.gov (United States)

    Hug, François

    2011-02-01

    Despite the many reviews and research papers on the limitations of surface electromyography (EMG), there are relatively few that address this issue by considering dynamic contractions and specifically from the point of view of muscle coordination. Nevertheless, whether muscle coordination can be precisely studied using surface EMG signals is still a matter of discussion in the scientific community. In other words, it is uncertain whether neural control strategies of movement can be inferred from EMG. This review article discusses the appropriateness of using EMG recordings for studying muscle coordination. First, the main uses of surface EMG for studying muscle coordination are depicted. Then, the main intrinsic drawbacks of the EMG technique (i.e., amplitude cancellation, crosstalk and spatial variability of muscle activity) and of EMG processing (i.e., smoothing of the linear envelope, normalization of the time scale and the amplitude and timing of muscle activation) are described and discussed. Finally, three other factors (i.e., variability, electromechanical delay and neuromuscular fatigue), which can affect the interpretation of EMG and have received little attention in the literature, are presented and discussed. All of this information is crucial to the proper interpretation of muscle coordination from EMG signals. Copyright © 2010 Elsevier Ltd. All rights reserved.

  19. 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.

  20. An EMG Keyboard for Forearm Amputees

    Directory of Open Access Journals (Sweden)

    Wenwei Yu

    2003-01-01

    Full Text Available A high-efficiency, easy-to-use input device is not only important for data entry but also for human-computer interaction. To date, there has been little research on input devices with many degrees of freedom (DOF that can be used by the handicapped. This paper presents the development of an electromyography (EMG-based input device for forearm amputees. To overcome the difficulties in analysing EMG and realising high DOF from biosignals, the following were integrated: (1 an online learning method to cope with nonlinearity and the individual difference of EMG signals; (2 a smoothing algorithm to deal with noisy recognition results and transition states; and (3 a modified Huffman coding algorithm to generate the optimal code, taking expected error and input efficiency into consideration. Experiments showed the validity of the system and the possibility for development of a quiet, free-posture (no postural restriction input device with many DOF for users, including forearm amputees.

  1. 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.

  2. Characterizing EMG data using machine-learning tools.

    Science.gov (United States)

    Yousefi, Jamileh; Hamilton-Wright, Andrew

    2014-08-01

    Effective electromyographic (EMG) signal characterization is critical in the diagnosis of neuromuscular disorders. Machine-learning based pattern classification algorithms are commonly used to produce such characterizations. Several classifiers have been investigated to develop accurate and computationally efficient strategies for EMG signal characterization. This paper provides a critical review of some of the classification methodologies used in EMG characterization, and presents the state-of-the-art accomplishments in this field, emphasizing neuromuscular pathology. The techniques studied are grouped by their methodology, and a summary of the salient findings associated with each method is presented. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. 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.

  4. Quantification of dynamic EMG patterns during gait in children with cerebral palsy.

    Science.gov (United States)

    Bojanic, Dubravka M; Petrovacki-Balj, Bojana D; Jorgovanovic, Nikola D; Ilic, Vojin R

    2011-06-15

    Our goal was to simplify the representation and interpretation of surface electromyographic (EMG) activity during gait to develop a clinical method for evaluating gait disabilities in children with cerebral palsy (CP). EMG was recorded from four muscles of a lower extremity. Gait cycles were tracked from one force-sensing resistor signal that was recorded synchronously with EMG. The method is based on the comparison of a patient's dynamic EMG envelope shapes and the normative gait-related patterns (norms). Developed norms were based on EMG data obtained in 10 healthy children. Due to newly introduced techniques for time and amplitude normalization, norms were developed regardless of differences in subject age, gender, basic gait parameters and the EMG measurement process. The proposed gait metric quantifies the similarity between a patient's gait-related patterns and norms by a single global value suitable for gait analysis in general, including a detailed analysis using the 10 partial values. The gait metric was experimentally validated with a control group of healthy children and a group of children with CP with different degrees of motor deficits. Gait metric values obtained in children from the control group are high for all muscles, which means that gait-related patterns are close to norms, whereas in children with CP the higher the degree of motor deficit, the lower the gait metric values. The method could be a very useful clinical tool for the recognition and tracking of motor disorders of the lower extremities in children with CP as well as many other neuromotor pathologies. Copyright © 2011 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2015-03-01

    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 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. Key pointsThe spikes observed in the sEMG spectrum during WBV exercises contain motion artifacts and possibly reflex activityThe motion artifacts are more pronounced in the first spike than the following spikes in the sEMG spectrumReflex activity during WBV exercises is enhanced with an additional load of approximately 50% of the body mass.

  6. Multi-stream HMM for EMG-based speech recognition.

    Science.gov (United States)

    Manabe, H; Zhang, Z

    2004-01-01

    A technique for improving the recognition accuracy of EMG-based speech recognition by applying existing speech recognition technologies is proposed. The authors have proposed an EMG-based speech recognition system that requires only mouth movements, voice need not be generated. A multi-stream HMM (hidden Markov model) and feature extraction technique are applied to EMG-based speech recognition. 3 channel facial EMG signals are collected from ten subjects when uttering 10 Japanese isolated digits. One channel corresponds to one stream. By examining various features, we found that the delta component of the static parameter leads to higher accuracy. Compared to equal stream weighting, the individual optimization of stream weights increased recognition accuracy by 4.0% which corresponds to a 12.8% reduction in error rate. This result shows that multistream HMM is effective for the classification of EMG.

  7. 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.

  8. 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.

  9. 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

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

    Science.gov (United States)

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

    2016-02-01

    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. 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. 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. Compared with pulse-width modulation stimulation strategies that are based on sEMG detection, the MNDC strategy is more effective for both voluntary muscle force reproduction and muscle fatigue reduction.

  11. Interpreting Signal Amplitudes in Surface Electromyography Studies in Sport and Rehabilitation Sciences.

    Science.gov (United States)

    Vigotsky, Andrew D; Halperin, Israel; Lehman, Gregory J; Trajano, Gabriel S; Vieira, Taian M

    2017-01-01

    Surface electromyography (sEMG) is a popular research tool in sport and rehabilitation sciences. Common study designs include the comparison of sEMG amplitudes collected from different muscles as participants perform various exercises and techniques under different loads. Based on such comparisons, researchers attempt to draw conclusions concerning the neuro- and electrophysiological underpinning of force production and hypothesize about possible longitudinal adaptations, such as strength and hypertrophy. However, such conclusions are frequently unsubstantiated and unwarranted. Hence, the goal of this review is to discuss what can and cannot be inferred from comparative research designs as it pertains to both the acute and longitudinal outcomes. General methodological recommendations are made, gaps in the literature are identified, and lines for future research to help improve the applicability of sEMG are suggested.

  12. Interpreting Signal Amplitudes in Surface Electromyography Studies in Sport and Rehabilitation Sciences

    Science.gov (United States)

    Vigotsky, Andrew D.; Halperin, Israel; Lehman, Gregory J.; Trajano, Gabriel S.; Vieira, Taian M.

    2018-01-01

    Surface electromyography (sEMG) is a popular research tool in sport and rehabilitation sciences. Common study designs include the comparison of sEMG amplitudes collected from different muscles as participants perform various exercises and techniques under different loads. Based on such comparisons, researchers attempt to draw conclusions concerning the neuro- and electrophysiological underpinning of force production and hypothesize about possible longitudinal adaptations, such as strength and hypertrophy. However, such conclusions are frequently unsubstantiated and unwarranted. Hence, the goal of this review is to discuss what can and cannot be inferred from comparative research designs as it pertains to both the acute and longitudinal outcomes. General methodological recommendations are made, gaps in the literature are identified, and lines for future research to help improve the applicability of sEMG are suggested. PMID:29354060

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. Detection of and Compensation for EMG Disturbances for Powered Lower Limb Prosthesis Control.

    Science.gov (United States)

    Spanias, John A; Perreault, Eric J; Hargrove, Levi J

    2016-02-01

    Myoelectric pattern recognition algorithms have been proposed for the control of powered lower limb prostheses, but electromyography (EMG) signal disturbances remain an obstacle to clinical implementation. To address this problem, we used a log-likelihood metric to detect simulated EMG disturbances and real disturbances acquired from EMG containing electrode shift. We found that features extracted from disturbed EMG have much lower log likelihoods than those from undisturbed signals and can be detected using a single threshold acquired from the training data. We designed a linear discriminant analysis (LDA) classifier that uses the log likelihood to decide between using a combination of EMG and mechanical sensors and using mechanical sensors only, to predict locomotion modes. When EMG contained disturbances, our classifier detected those disturbances and disregarded EMG data. Our classifier had significantly lower errors than a standard LDA classifier in the presence of EMG disturbances. The log-likelihood classifier had a low false positive threshold, and thus did not perform significantly differently from the standard LDA classifier when EMG did not contain disturbances. The log-likelihood threshold could also be applied to individual EMG channels, enabling specific channels containing EMG disturbances to be appropriately ignored when making locomotion mode predictions.

  19. Accuracy assessment of a surface electromyogram decomposition system in human first dorsal interosseus muscle

    Science.gov (United States)

    Hu, Xiaogang; Rymer, William Z.; Suresh, Nina L.

    2014-04-01

    Objective. The aim of this study is to assess the accuracy of a surface electromyogram (sEMG) motor unit (MU) decomposition algorithm during low levels of muscle contraction. Approach. A two-source method was used to verify the accuracy of the sEMG decomposition system, by utilizing simultaneous intramuscular and surface EMG recordings from the human first dorsal interosseous muscle recorded during isometric trapezoidal force contractions. Spike trains from each recording type were decomposed independently utilizing two different algorithms, EMGlab and dEMG decomposition algorithms. The degree of agreement of the decomposed spike timings was assessed for three different segments of the EMG signals, corresponding to specified regions in the force task. A regression analysis was performed to examine whether certain properties of the sEMG and force signal can predict the decomposition accuracy. Main results. The average accuracy of successful decomposition among the 119 MUs that were common to both intramuscular and surface records was approximately 95%, and the accuracy was comparable between the different segments of the sEMG signals (i.e., force ramp-up versus steady state force versus combined). The regression function between the accuracy and properties of sEMG and force signals revealed that the signal-to-noise ratio of the action potential and stability in the action potential records were significant predictors of the surface decomposition accuracy. Significance. The outcomes of our study confirm the accuracy of the sEMG decomposition algorithm during low muscle contraction levels and provide confidence in the overall validity of the surface dEMG decomposition algorithm.

  20. Adaptive neuron-to-EMG decoder training for FES neuroprostheses

    Science.gov (United States)

    Ethier, Christian; Acuna, Daniel; Solla, Sara A.; Miller, Lee E.

    2016-08-01

    Objective. We have previously demonstrated a brain-machine interface neuroprosthetic system that provided continuous control of functional electrical stimulation (FES) and restoration of grasp in a primate model of spinal cord injury (SCI). Predicting intended EMG directly from cortical recordings provides a flexible high-dimensional control signal for FES. However, no peripheral signal such as force or EMG is available for training EMG decoders in paralyzed individuals. Approach. Here we present a method for training an EMG decoder in the absence of muscle activity recordings; the decoder relies on mapping behaviorally relevant cortical activity to the inferred EMG activity underlying an intended action. Monkeys were trained at a 2D isometric wrist force task to control a computer cursor by applying force in the flexion, extension, ulnar, and radial directions and execute a center-out task. We used a generic muscle force-to-endpoint force model based on muscle pulling directions to relate each target force to an optimal EMG pattern that attained the target force while minimizing overall muscle activity. We trained EMG decoders during the target hold periods using a gradient descent algorithm that compared EMG predictions to optimal EMG patterns. Main results. We tested this method both offline and online. We quantified both the accuracy of offline force predictions and the ability of a monkey to use these real-time force predictions for closed-loop cursor control. We compared both offline and online results to those obtained with several other direct force decoders, including an optimal decoder computed from concurrently measured neural and force signals. Significance. This novel approach to training an adaptive EMG decoder could make a brain-control FES neuroprosthesis an effective tool to restore the hand function of paralyzed individuals. Clinical implementation would make use of individualized EMG-to-force models. Broad generalization could be achieved by

  1. EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis.

    Science.gov (United States)

    Dosen, Strahinja; Markovic, Marko; Somer, Kelef; Graimann, Bernhard; Farina, Dario

    2015-06-19

    Active hand prostheses controlled using electromyography (EMG) signals have been used for decades to restore the grasping function, lost after an amputation. Although myocontrol is a simple and intuitive interface, it is also imprecise due to the stochastic nature of the EMG recorded using surface electrodes. Furthermore, the sensory feedback from the prosthesis to the user is still missing. In this study, we present a novel concept to close the loop in myoelectric prostheses. In addition to conveying the grasping force (system output), we provided to the user the online information about the system input (EMG biofeedback). As a proof-of-concept, the EMG biofeedback was transmitted in the current study using a visual interface (ideal condition). Ten able-bodied subjects and two amputees controlled a state-of-the-art myoelectric prosthesis in routine grasping and force steering tasks using EMG and force feedback (novel approach) and force feedback only (classic approach). The outcome measures were the variability of the generated forces and absolute deviation from the target levels in the routine grasping task, and the root mean square tracking error and the number of sudden drops in the force steering task. During the routine grasping, the novel method when used by able-bodied subjects decreased twofold the force dispersion as well as absolute deviations from the target force levels, and also resulted in a more accurate and stable tracking of the reference force profiles during the force steering. Furthermore, the force variability during routine grasping did not increase for the higher target forces with EMG biofeedback. The trend was similar in the two amputees. The study demonstrated that the subjects, including the two experienced users of a myoelectric prosthesis, were able to exploit the online EMG biofeedback to observe and modulate the myoelectric signals, generating thereby more consistent commands. This allowed them to control the force predictively

  2. SEA SURFACE ALTIMETRY BASED ON AIRBORNE GNSS SIGNAL MEASUREMENTS

    Directory of Open Access Journals (Sweden)

    K. Yu

    2012-07-01

    Full Text Available In this study the focus is on ocean surface altimetry using the signals transmitted from GNSS (Global Navigation Satellite System satellites. A low-altitude airborne experiment was recently conducted off the coast of Sydney. Both a LiDAR experiment and a GNSS reflectometry (GNSS-R experiment were carried out in the same aircraft, at the same time, in the presence of strong wind and rather high wave height. The sea surface characteristics, including the surface height, were derived from processing the LiDAR data. A two-loop iterative method is proposed to calculate sea surface height using the relative delay between the direct and the reflected GNSS signals. The preliminary results indicate that the results obtained from the GNSS-based surface altimetry deviate from the LiDAR-based results significantly. Identification of the error sources and mitigation of the errors are needed to achieve better surface height estimation performance using GNSS signals.

  3. Knowledge of electromyography (EMG) in patients undergoing EMG examinations.

    Science.gov (United States)

    Mondelli, Mauro; Aretini, Alessandro; Greco, Giuseppe

    2014-01-01

    The aim of this study was to evaluate knowledge of electromyography (EMG) in patients undergoing the procedure. In one year, 1,586 consecutive patients (mean age 56 years; 58.8% women) were admitted to two EMG labs to undergo EMG for the first time. The patients found to be "informed" about the how an EMG examination is performed and about the purpose of EMG numbered 448 (28.2%), while those found to be "informed" only about the manner of its execution or only about its purpose numbered 161 (10.2%) and 151 (9.5%), respectively. The remaining 826 (52.1%) patients had either no information, or the information they had was very poor or incorrect (this was particularly true if they had been consulting websites). Being "informed" was associated with level of education (high), type of referring physician (specialist) and with an appropriate referral diagnosis specified in the EMG request. The quality of patient information on EMG was found to be very poor and could be improved. Physicians referring patients for EMG examinations, especially general practitioners, should assume primary responsibility for patient education and counseling in this field.

  4. Knowledge of electromyography (EMG) in patients undergoing EMG examinations

    Science.gov (United States)

    Mondelli, Mauro; Aretini, Alessandro; Greco, Giuseppe

    2014-01-01

    Summary The aim of this study was to evaluate knowledge of electromyography (EMG) in patients undergoing the procedure. In one year, 1,586 consecutive patients (mean age 56 years; 58.8% women) were admitted to two EMG labs to undergo EMG for the first time. The patients found to be “informed” about the how an EMG examination is performed and about the purpose of EMG numbered 448 (28.2%), while those found to be “informed” only about the manner of its execution or only about its purpose numbered 161 (10.2%) and 151 (9.5%), respectively. The remaining 826 (52.1%) patients had either no information, or the information they had was very poor or incorrect (this was particularly true if they had been consulting websites). Being “informed” was associated with level of education (high), type of referring physician (specialist) and with an appropriate referral diagnosis specified in the EMG request. The quality of patient information on EMG was found to be very poor and could be improved. Physicians referring patients for EMG examinations, especially general practitioners, should assume primary responsibility for patient education and counseling in this field. PMID:25473740

  5. Surface electromyography recording of spontaneous eyeblinks: applications in neuroprosthetics.

    Science.gov (United States)

    Frigerio, Alice; Brenna, Stefano; Cavallari, Paolo

    2013-02-01

    We are designing an implantable neuroprosthesis for the treatment of unilateral facial paralysis. The envisioned biomimetic device paces artificial blinks in the paretic eyelid when activity in the healthy orbicularis oculi (orbicularis) muscle is detected. The present article focuses on electromyography (EMG)-based eyeblink detection. A pilot clinical study was performed in healthy volunteers who were intended to represent individuals with facial paralysis. Spontaneous eyeblinks were detected by a surface EMG recording. Blink detection accuracy was tested at rest and during voluntary smiling and chewing. Fifteen participants were asked to wear surface recording electrodes on the left side of their face, detecting the orbicularis oculi, the masseter, and the zygomatic muscle EMG activity. Participants were asked to look ahead, voluntarily smile, and chew according to an experimental protocol. Custom software was designed with the purpose of selectively filtering the multichannel EMG recordings and triggering a digital output. The software filter allowed elimination of spurious artificial eyeblinks and thus increased the accuracy of the EMG recording apparatus for the spontaneous blinking. Orbicularis oculi EMG recording worked as a real-time eyeblink-detecting system. Moreover, the multichannel EMG recording coupled to a proper digital signal processing was very effective in specifically detecting the spontaneous blinking during other facial muscle activities. With regard to closed-loop biomimetic devices for the pacing of the eyeblink, the EMG signal represents a valid option for the recording side.

  6. Functional Neuromuscular Stimulation Controlled by Surface Electromyographic Signals Produced by Volitional Activation of the Same Muscle

    DEFF Research Database (Denmark)

    Sennels, Søren; Biering-Sørensen, Fin; Andersen, Ole Trier

    1997-01-01

    In order to use the volitional electromyography (EMG) as a control signal for the stimulation of the same muscle, it is necessary to eliminate the stimulation artifacts and the muscle responses caused by the stimulation. The stimulation artifacts, caused by the electric field in skin and tissue...... generated by the stimulation current, are relatively easy to eliminate by shutting down the EMG-amplifier at the onset of the stimulation pulses. The muscle response is a nonstationary signal, therefore, an adaptive linear prediction filter is proposed. The filter is implemented and for three filter lengths...... tested on both simulated and real data. The filter performance is compared with a conventional fixed comb filter. The simulations indicate that the adaptive filter is relatively insensitive to variations in amplitude of the muscle responses, and for all filter lengths produces a good filtering...

  7. Specialized Nerve Tests: EMG, NCV and SSEP

    Science.gov (United States)

    ... BLOG FIND A SPECIALIST Treatments Specialized Nerve Tests: EMG, NCV and SSEP Ajay Jawahar MD Ajay Jawahar ... these techniques in the following sections. What is EMG? EMG, or Electromyography is a technique for evaluating ...

  8. 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.

  9. Classification of ankle joint movements based on surface electromyography signals for rehabilitation robot applications.

    Science.gov (United States)

    Al-Quraishi, Maged S; Ishak, Asnor J; Ahmad, Siti A; Hasan, Mohd K; Al-Qurishi, Muhammad; Ghapanchizadeh, Hossein; Alamri, Atif

    2017-05-01

    Electromyography (EMG)-based control is the core of prostheses, orthoses, and other rehabilitation devices in recent research. Nonetheless, EMG is difficult to use as a control signal given the complex nature of the signal. To overcome this problem, the researchers employed a pattern recognition technique. EMG pattern recognition mainly involves four stages: signal detection, preprocessing feature extraction, dimensionality reduction, and classification. In particular, the success of any pattern recognition technique depends on the feature extraction stage. In this study, a modified time-domain features set and logarithmic transferred time-domain features (LTD) were evaluated and compared with other traditional time-domain features set (TTD). Three classifiers were employed to assess the two feature sets, namely linear discriminant analysis (LDA), k nearest neighborhood, and Naïve Bayes. Results indicated the superiority of the new time-domain feature set LTD, on conventional time-domain features TTD with the average classification accuracy of 97.23 %. In addition, the LDA classifier outperformed the other two classifiers considered in this study.

  10. Generalization of EMG biofeedback training.

    Science.gov (United States)

    Poppen, R; Hanson, H B; Ip, S M

    1988-09-01

    Five young adults received audio biofeedback training to reduce trapezius EMG levels while they engaged in reading in an office, seated at a table. A multiple-baseline-across subjects design was employed in two separate studies. After training, all subjects demonstrated reduced EMG levels while reading in a home or library setting. The first study suggested that subjects reduced EMG levels by minimizing movements and altering their postures; the second study systematically demonstrated changes in such behavior, which was correlated with EMG levels. The data provide evidence that EMG biofeedback resulted in response generalization across several motoric classes, and in stimulus generalization from the training setting to the natural environment. The importance of assessing generalization is discussed.

  11. Ultra Fast Optical Sectioning: Signal preserving filtering and surface reconstruction

    DEFF Research Database (Denmark)

    Jensen, Rasmus Ramsbøl; Poel, Mike van der; Larsen, Rasmus

    2011-01-01

    In 3D surface scanning it is desirable to lter away bad data without altering the quality of the remaining good data. Filtering of raw scanner data before surface reconstruction can minimize the induced er- ror and improve on the probability of reconstructing the true surface. If outliers consist...... a signal preserving ltering of the data set is done. The remaining data are used for a smooth surface re- construction creating very plausible surfaces. The data used in our work comes from a newly developed hand held 3D scanner. The scanner is an Ultra Fast Optical Sectioning scanner, which is able...

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

    OpenAIRE

    Lersviriyanantakul Chaiwat; Booranawong Apidet; Sengchuai Kiattisak; Phukpattaranont Pornchai; Wongkittisuksa Booncharoen; Jindapetch Nattha

    2016-01-01

    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 pa...

  13. 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.

  14. ERRORS IN FREQUENCY PARAMETERS OF EMG POWER SPECTRA

    NARCIS (Netherlands)

    HOF, AL

    1991-01-01

    Frequency shifts in random signals, e.g., EMG or Doppler ultrasound, can be followed by monitoring one or more parameters of the power spectrum. When such a frequency parameter is determined over a finite length of the signal, a random error and sometimes a systematic error or bias are introduced.

  15. 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.

  16. Spectral properties of electromyographic and mechanomyographic signals during isometric ramp and step contractions in biceps brachii.

    Science.gov (United States)

    Qi, Liping; Wakeling, James M; Green, Adam; Lambrecht, Kirstin; Ferguson-Pell, Martin

    2011-02-01

    The purposes of this study were: (1) to apply wavelet and principal component analysis to quantify the spectral properties of the surface EMG and MMG signals from biceps brachii during isometric ramp and step muscle contractions when the motor units are recruited in an orderly manner, and (2) to compare the recruitment patterns of motor unit during isometric ramp and step muscle contractions. Twenty healthy participants (age = 34 ± 10.7 years) performed step and ramped isometric contractions. Surface EMG and MMG were recorded from biceps brachii. The EMGs and MMGs were decomposed into their intensities in time-frequency space using a wavelet technique. The EMG and MMG spectra were then compared using principal component analysis (PCA) and ANCOVA. Wavelet combined PCA offers a quantitative measure of the contribution of high and low frequency content within the EMG and MMG. The ANCOVA indicated that there was no significant difference in EMG total intensity, EMG(MPF), first and second principal component loading scores (PCI and PCII) between ramp and step contractions, whereas the MMG(MPF) and MMG PCI loading scores were significantly higher during ramp contractions than during step contractions. These findings suggested that EMG and MMG may offer complimentary information regarding the interactions between motor unit recruitment and firing rate that control muscle force production. In addition, our results support the hypothesis that different motor unit recruitment strategy was used by the muscle when contracting under different conditions. Copyright © 2010 Elsevier Ltd. All rights reserved.

  17. A multichannel sEMG method for myoelectric control of a forearm prosthesis

    NARCIS (Netherlands)

    van Baal, D.W.; van Baal, D.W.; Muijzer-Witteveen, Heintje Johanna Berendina; Kallenberg, L.A.C.; Hermens, Hermanus J.; Rietman, Johan Swanik; Veltink, P.H.; Eberle, W.

    2009-01-01

    A large number of amputee patients doesn't use their myoelectric prosthesis, mainly due to the limited functionality of the prosthesis. The aim of this study was to investigate if it is possible to distinguish 8 different contractions by using multi-electrode sEMG. We analysed sEMG signals of a grid

  18. EMG and cardiovascular responses to emotionally provocative photographs and text.

    Science.gov (United States)

    Livesay, J R; Porter, T

    1994-08-01

    Previous studies on the psychophysiology of human emotion have repeatedly shown general and occasionally specific facial EMG (mu v) and covert cardiovascular response relationships to emotionally provocative photographs. Less clear are the relationships between psychophysiological response indices measured during the silent reading of emotionally charged versus emotionally neutral text. In this study, 12 adult subjects were presented two emotionally loaded color and black-and-white photographs and two brief newspaper articles, one emotionally charged and the other emotionally neutral in content. Each independent stimulus was presented for 1 min., preceded by a rest according to a multiple baseline-reversal design. Subjects evaluated each pictorial and textual stimulus condition according to adjective dimensions on 7-point rating scales. Mean values for corrugator supercilii EMG (mu v), upper trapezius EMG (mu v), surface temperature (degrees F), and heart rate (bpm) measured by finger photoplethysmography were measured during each rest and test period. Significant increases in the subjects' mean corrugator supercilii EMG (mu v) measures were observed during all color and black-and-white photograph presentations for both emotional and neutral content. As predicted, the subjects' mean corrugator supercilii EMG (mu v) measures increased significantly while silently reading text with an obvious unpleasant emotional tone. A significant positive relationship was observed between the subjects' mean ratings and mean corrugator EMG (mu v) difference values for the emotionally loaded color photographs.

  19. 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 EMG activation was highest in Hips 0 or Hips 45 for adductor 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 test type was a significant factor (p 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.

  20. Are external knee load and EMG measures accurate indicators of internal knee contact forces during gait?

    Science.gov (United States)

    Meyer, Andrew J; D'Lima, Darryl D; Besier, Thor F; Lloyd, David G; Colwell, Clifford W; Fregly, Benjamin J

    2013-06-01

    Mechanical loading is believed to be a critical factor in the development and treatment of knee osteoarthritis. However, the contact forces to which the knee articular surfaces are subjected during daily activities cannot be measured clinically. Thus, the ability to predict internal knee contact forces accurately using external measures (i.e., external knee loads and muscle electromyographic [EMG] signals) would be clinically valuable. We quantified how well external knee load and EMG measures predict internal knee contact forces during gait. A single subject with a force-measuring tibial prosthesis and post-operative valgus alignment performed four gait patterns (normal, medial thrust, walking pole, and trunk sway) to induce a wide range of external and internal knee joint loads. Linear regression analyses were performed to assess how much of the variability in internal contact forces was accounted for by variability in the external measures. Though the different gait patterns successfully induced significant changes in the external and internal quantities, changes in external measures were generally weak indicators of changes in total, medial, and lateral contact force. Our results suggest that when total contact force may be changing, caution should be exercised when inferring changes in knee contact forces based on observed changes in external knee load and EMG measures. Advances in musculoskeletal modeling methods may be needed for accurate estimation of in vivo knee contact forces. Copyright © 2012 Orthopaedic Research Society.

  1. The effects of scapular taping on the surface electromyographic signal amplitude of shoulder girdle muscles during upper extremity elevation in individuals with suspected shoulder impingement syndrome.

    Science.gov (United States)

    Selkowitz, David M; Chaney, Casey; Stuckey, Sandra J; Vlad, Georgeanne

    2007-11-01

    Multifactorial, repeated-measures, within-subjects design. To investigate the immediate effects of scapular taping on surface electromyographic (EMG) signal amplitude of shoulder girdle muscles during upper extremity elevation in individuals with suspected shoulder impingement syndrome. Individuals with shoulder impingement syndrome may present with increased activity of the upper trapezius and inhibition of other shoulder muscles active during upper extremity elevation. Scapular taping is theorized to normalize shoulder girdle function during scapular upward rotation by decreasing upper trapezius activity and increasing the activity of the lower trapezius and other muscles. assessed for each muscle. Upper trapezius activity was significantly lower with tape during shelf task elevation (P = .002), especially above 90 degrees (Pshoulder abduction in the scapular plane, the main effect for upper trapezius showed a significant decrease of EMG signal amplitude (P = .047) for tape versus no tape, but no significant interactions were found among components of this activity, or for other muscles. Scapular taping decreased upper trapezius and increased lower trapezius activity in people with suspected shoulder impingement during a functional overhead-reaching task, and decreased upper trapezius activity during shoulder abduction in the scapular plane. Taping did not affect the other muscles under the loads tested, but it is possible that the activity of these muscles was not deficient at the time of testing.

  2. Surface sensing and signaling networks in plant pathogenic fungi.

    Science.gov (United States)

    Kou, Yanjun; Naqvi, Naweed I

    2016-09-01

    Pathogenic fungi have evolved highly varied and remarkable strategies to invade and infect their plant hosts. Typically, such fungal pathogens utilize highly specialized infection structures, morphologies or cell types produced from conidia or ascospores on the cognate host surfaces to gain entry therein. Such diverse infection strategies require intricate coordination in cell signaling and differentiation in phytopathogenic fungi. Here, we present an overview of our current understanding of cell signaling and infection-associated development that primes host penetration in the top ten plant pathogenic fungi, which utilize specific receptors to sense and respond to different surface cues, such as topographic features, hydrophobicity, hardness, plant lipids, phytohormones, and/or secreted enzymes. Subsequently, diverse signaling components such as G proteins, cyclic AMP/Protein Kinase A and MAP kinases are activated to enable the differentiation of infection structures. Recent studies have also provided fascinating insights into the spatio-temporal dynamics and specialized sequestration and trafficking of signaling moieties required for proper development of infection structures in phytopathogenic fungi. Molecular insight in such infection-related morphogenesis and cell signaling holds promise for identifying novel strategies for intervention of fungal diseases in plants. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. 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.

  4. Investigating the resetting of OSL signals in rock surfaces

    DEFF Research Database (Denmark)

    Sohbati, Reza; Murray, Andrew S.; Jain, Mayank

    2011-01-01

    There are many examples of buried rock surfaces whose age is of interest to geologists and archaeologists. Luminescence dating is a potential method which can be applied to dating such surfaces; as part of a research project which aims to develop such an approach, the degree of resetting of OSL...... signals in grains and slices from five different cobbles/boulders collected from a modern beach is investigated. All the rock surfaces are presumed to have been exposed to daylight for a prolonged period of time (weeks to years). Feldspar was identified as the preferred dosimeter because quartz extracts...... were insensitive. Dose recovery tests using solar simulator and IR diodes on both K-feldspar grains and solid slices taken from the inner parts of the rocks are discussed. Preheat plateau results using surface grains and slices show that significant thermal transfer in naturally bleached samples can...

  5. 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

  6. Normalizing shoulder EMG: An optimal set of maximum isometric voluntary contraction tests considering reproducibility.

    Science.gov (United States)

    Schwartz, Cédric; Tubez, François; Wang, François-Charles; Croisier, Jean-Louis; Brüls, Olivier; Denoël, Vincent; Forthomme, Bénédicte

    2017-08-18

    Normalization of the electromyography (EMG) signal is often performed relatively to maximal voluntary activations (MVA) obtained during maximum isometric voluntary contraction (MVIC). The first aim was to provide an inter-session reproducible protocol to normalize the signal of eight shoulder muscles. The protocol should also lead to a level of activation >90% of MVA for >90% of the volunteers. The second aim was to evaluate the influence of the method used to extract the MVA from the EMG envelope on the normalized EMG signal. Thirteen volunteers performed 12 MVICs twice (one week interval). Several time constants (100ms to 2s) were compared when extracting the MVA from the EMG envelope. The EMG activity was also acquired during an arm elevation. Our results show that a combination of nine MVIC tests was required to meet our requirements including reproducibility. Both the number of MVIC tests and the size of the time constant influence the normalized EMG signal during the dynamic activity (variations up to 15%). A time constant of 1s was a good compromise to extract the MVA. These findings are valuable to improve the reproducibility of EMG signal normalization. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Cesqui, Benedetta; Tropea, Peppino; Micera, Silvestro; Krebs, Hermano Igo

    2013-07-15

    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. 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). 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. 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 abnormal muscle patterns and provide

  8. The effects of whole body vibration on EMG activity of the upper extremity muscles in static modified push up position.

    Science.gov (United States)

    Ashnagar, Zinat; Shadmehr, Azadeh; Hadian, Mohammadreza; Talebian, Saeed; Jalaei, Shohreh

    2016-08-10

    Whole Body Vibration (WBV) has been reported to change neuromuscular activity which indirectly assessed by electromyography (EMG). Although researches regarding the influence of WBV on EMG activity of the upper extremity muscles are in their infancy, contradictory findings have been reported as a result of dissimilar protocols. The purpose of this study was to investigate the effects of WBV on electromyography (EMG) activity of upper extremity muscles in static modified push up position. Forty recreationally active females were randomly assigned in WBV and control groups. Participants in WBV group received 5 sets of 30 seconds vibration at 5 mm (peak to peak) and 30 Hz by using vibratory platform. No vibration stimulus was used in the control group. Surface EMG was recorded from Upper Trapezius (UT), Serratus Anterior (SA), Biceps Brachii (BB) and Triceps Brachii (TB) muscles before, during and after the vibration protocol while the subjects maintained the static modified push up position. EMG signals were expressed as root mean square (EMGrms) and normalized by maximum voluntary exertion (MVE). EMGrms activity of the studied muscles increased significantly during the vibration protocol in the WBV group comparing to the control group (P ≤ 0.05). The results indicated that vibration stimulus transmitting via hands increased muscle activity of UT, SA, BB and TB muscles by an average of 206%, 60%, 106% and 120%, respectively, comparing to pre vibration values. These findings suggest that short exposure to the WBV could increase the EMGrms activity of the upper extremity muscles in the static modified push-up position. However, more sessions of WBV application require for a proper judgment.

  9. Evaluation of muscle force classification using shape analysis of the sEMG probability density function: a simulation study.

    Science.gov (United States)

    Ayachi, F S; Boudaoud, S; Marque, C

    2014-08-01

    In this work, we propose to classify, by simulation, the shape variability (or non-Gaussianity) of the surface electromyogram (sEMG) amplitude probability density function (PDF), according to contraction level, using high-order statistics (HOS) and a recent functional formalism, the core shape modeling (CSM). According to recent studies, based on simulated and/or experimental conditions, the sEMG PDF shape seems to be modified by many factors as: contraction level, fatigue state, muscle anatomy, used instrumentation, and also motor control parameters. For sensitivity evaluation against these several sources (physiological, instrumental, and neural control) of variability, a large-scale simulation (25 muscle anatomies, ten parameter configurations, three electrode arrangements) is performed, by using a recent sEMG-force model and parallel computing, to classify sEMG data from three contraction levels (20, 50, and 80% MVC). A shape clustering algorithm is then launched using five combinations of HOS parameters, the CSM method and compared to amplitude clustering with classical indicators [average rectified value (ARV) and root mean square (RMS)]. From the results screening, it appears that the CSM method obtains, using Laplacian electrode arrangement, the highest classification scores, after ARV and RMS approaches, and followed by one HOS combination. However, when some critical confounding parameters are changed, these scores decrease. These simulation results demonstrate that the shape screening of the sEMG amplitude PDF is a complex task which needs both efficient shape analysis methods and specific signal recording protocol to be properly used for tracking neural drive and muscle activation strategies with varying force contraction in complement to classical amplitude estimators.

  10. 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.

  11. 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.

  12. Early corticospinal tract damage in prodromal SCA2 revealed by EEG-EMG and EMG-EMG coherence.

    Science.gov (United States)

    Velázquez-Pérez, Luis; Tünnerhoff, Johannes; Rodríguez-Labrada, Roberto; Torres-Vega, Reidenis; Ruiz-Gonzalez, Yusely; Belardinelli, Paolo; Medrano-Montero, Jacqueline; Canales-Ochoa, Nalia; González-Zaldivar, Yanetza; Vazquez-Mojena, Yaimeé; Auburger, Georg; Ziemann, Ulf

    2017-12-01

    Clinical data suggest early involvement of the corticospinal tract (CST) in spinocerebellar ataxia type 2 (SCA2). Here we tested if early CST degeneration can be detected in prodromal SCA2 mutation carriers by electrophysiological markers of CST integrity. CST integrity was tested in 15 prodromal SCA2 mutation carriers, 19 SCA2 patients and 25 age-matched healthy controls, using corticomuscular (EEG-EMG) and intermuscular (EMG-EMG) coherence measures in upper and lower limb muscles. Significant reductions of EEG-EMG and EMG-EMG coherences were observed in the SCA2 patients, and to a similar extent in the prodromal SCA2 mutation carriers. In prodromal SCA2, EEG-EMG and EMG-EMG coherences correlated with the predicted time to ataxia onset. Findings indicate early CST neurodegeneration in SCA2. EEG-EMG and EMG-EMG coherence may serve as biomarkers of early CST neurodegeneration in prodromal SCA2 mutation carriers. Findings are important for developing preclinical disease markers in the context of currently emerging disease-modifying therapies of neurodegenerative disorders. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

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

    CERN Document Server

    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 scales (center frequencies) with non-constant relative bandwidth. Some aspects of the method may seem a bit ad hoc and we have therefore undertaken a closer mathematical investigation, showing the connection with the conventional wavelet analysis and giving a somewhat simplified formulation of the method using Morlet wavelets. It is pointed out that the "intensity analysis" method is related to the concept of an equalizer. In order to illustrate the method we apply it to nonstationary EMG-signals of a dynamic leg-extensio...

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

    Science.gov (United States)

    Guo, Shuxiang; Pang, Muye; Gao, Baofeng; Hirata, Hideyuki; Ishihara, Hidenori

    2015-04-16

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

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

    Directory of Open Access Journals (Sweden)

    Shuxiang Guo

    2015-04-01

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

  16. 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

  17. 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.

  18. 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.

  19. Robust Bio-Signal Based Control of an Intelligent Wheelchair

    Directory of Open Access Journals (Sweden)

    Dongyi Chen

    2013-09-01

    Full Text Available In this paper, an adaptive human-machine interaction (HMI method that is based on surface electromyography (sEMG signals is proposed for the hands-free control of an intelligent wheelchair. sEMG signals generated by the facial movements are obtained by a convenient dry electrodes sensing device. After the signals features are extracted from the autoregressive model, control data samples are updated and trained by an incremental online learning algorithm in real-time. Experimental results show that the proposed method can significantly improve the classification accuracy and training speed. Moreover, this method can effectively reduce the influence of muscle fatigue during a long time operation of sEMG-based HMI.

  20. 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.

  1. 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.

  2. EMG activity of the muscles of the neck and forelimbs during different forms of locomotion.

    Science.gov (United States)

    Tokuriki, M; Ohtsuki, R; Kai, M; Hiraga, A; Oki, H; Miyahara, Y; Aoki, O

    1999-07-01

    We recorded the electromyographic (EMG) activity of 7 skeletal muscles in the forequarters and 1 in the hindquarters of 6 Thoroughbred horses during overground walking, swimming in a circular pool, and walking and trotting in a water treadmill. Bipolar fine wire electrodes were inserted into the muscles and the EMG signals were recorded using a telemetric system. The splenius exhibited tonic EMG activity during swimming. The brachiocephalicus showed its highest intensity during swimming followed by the walk and trot in the water treadmill and then walking overground. The triceps brachii caput longum had a similar activity pattern to the brachiocephalicus. The brachialis showed only weak EMG activity in all 3 types of locomotion. The extensor digitorum communis had higher intensity of EMG activity in the walk in the water treadmill than in other kinds of locomotion. The flexor digitorum profundus exhibited the most intense EMG activity during swimming. These results indicated that swimming evoked strong EMG activity in the antigravity muscles in spite of reduced gravitational force. Walking in the water treadmill may require more intensified EMG activity of the forelimb than the trot in the same treadmill.

  3. Functional Neuromuscular Stimulation Controlled by Surface Electromyographic Signals Produced by the Volitional Activation of the Same Muscle:

    DEFF Research Database (Denmark)

    Sennels, Søren; Fin, Biering-Sørensen; Andersen, Ole Trier

    1997-01-01

    Using the voluntary EMG as a control signal for the stimulation of the same muscle necessitates elimination of stimulus artifacts and the muscle response caused by the stimulation. The stimulus artifacts are easily eliminated by shutting down the amplifier during stimulation. The muscle response...... is a non-stationary signal, therefore an adaptive linear prediction filter is proposed. The filter is derived and tested for three filter lengths on both simulated and real data. The performance is compared with a conventional fixed comb filter. The simulations indicate that the adaptive filter...... comparable with the background noise. It is thus possible to extract the voluntary EMG from a partly paralysed muscle and use it for controlling the stimulation of the same muscle....

  4. Inter-Gender sEMG Evaluation of Central and Peripheral Fatigue in Biceps Brachii of Young Healthy Subjects.

    Directory of Open Access Journals (Sweden)

    Federico Meduri

    Full Text Available The purpose of the present study was to evaluate inter-arm and inter-gender differences in fractal dimension (FD and conduction velocity (CV obtained from multichannel surface electromyographic (sEMG recordings during sustained fatiguing contractions of the biceps brachii.A total of 20 recreationally active males (24±6 years and 18 recreationally active females (22±9 years performed two isometric contractions at 120 degrees elbow joint angle: (1 at 20% maximal voluntary contraction (MVC for 90 s, and (2 at 60% MVC until exhaustion the time to perform the task has been measured. Signals from sEMG were detected from the biceps brachii using bidimensional arrays of 64 electrodes and initial values and rate of change of CV and FD of the sEMG signal were calculated.No difference between left and right sides and no statistically significant interaction effect of sides with gender were found for all parameters measured. A significant inter-gender difference was found for MVC (p0.05. During the sustained 60% MVC no statistical correlation was found between MVC and CV or FD initial estimates nor between MVC and CV or FD slopes both in males and females whereas. A significant positive correlation between CV and FD slopes was found in both genders (males: r = 0,61; females: r = 0,55.Fatigue determines changes in FD and CV values in biceps brachii during sustained contractions at 60% MVC. In particular males show greater increase in the rate of change of CV and FD than females whereas no difference in percentage change of these sEMG descriptors of fatigue was found. A significant correlation between FD and CV slopes found in both genders highlights that central and peripheral myoelectric components of fatigue may interact during submaximal isometric contractions.

  5. 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

  6. High-density surface electromyography improves the identification of oscillatory synaptic inputs to motoneurons.

    Science.gov (United States)

    Steeg, Chiel van de; Daffertshofer, Andreas; Stegeman, Dick F; Boonstra, Tjeerd W

    2014-05-15

    Many studies have addressed corticomuscular coherence (CMC), but broad applications are limited by low coherence values and the variability across subjects and recordings. Here, we investigated how the use of high-density surface electromyography (HDsEMG) can improve the detection of CMC. Sixteen healthy subjects performed isometric contractions at six low-force levels using a pinch-grip, while HDsEMG of the adductor pollicis transversus and flexor and abductor pollicis brevis and whole-head magnetoencephalography were recorded. Different configurations were constructed from the HDsEMG grid, such as a bipolar and Laplacian montage, as well as a montage based on principal component analysis (PCA). CMC was estimated for each configuration, and the strength of coherence was compared across configurations. As expected, performance of the precision-grip task resulted in significant CMC in the β-frequency band (16-26 Hz). Compared with a bipolar EMG montage, all multichannel configurations obtained from the HDsEMG grid revealed a significant increase in CMC. The configuration, based on PCA, showed the largest (37%) increase. HDsEMG did not reduce the between-subject variability; rather, many configurations showed an increased coefficient of variation. Increased CMC presumably reflects the ability of HDsEMG to counteract inherent EMG signal factors-such as amplitude cancellation-which impact the detection of oscillatory inputs. In contrast, the between-subject variability of CMC most likely has a cortical origin. Copyright © 2014 the American Physiological Society.

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

    Directory of Open Access Journals (Sweden)

    S. Sethana

    2014-10-01

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

  8. 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.

  9. Sudden changes in walking surface compliance evoke contralateral EMG in a hemiparetic walker: a case study of inter-leg coordination after neurological injury.

    Science.gov (United States)

    Skidmore, Jeffrey; Artemiadis, Panagiotis

    2016-08-01

    Gait impairment due to neurological disorders is a significant problem around the world. Despite the growing interest in using robotic devices for gait rehabilitation, their widespread use remains limited as there is no clear evidence that robot-assisted gait therapy is superior to traditional treadmill-based therapy. This work is a case study that focuses on investigating the existence of mechanisms of inter-leg coordination after neurological injury, and based on that, proposing novel methods for gait rehabilitation. Using a novel robotic device, the Variable Stiffness Treadmill (VST), we apply perturbations to the compliance of the walking surface underneath the non-paretic leg, and analyze the response of the contralateral (paretic) leg. We show that muscle activity is evoked in the gastrocnemius of the paretic leg. From a clinical prospective, the results of this study can be disruptive because our methods provide a safe and targeted way to provide gait rehabilitation in hemiparesis since direct manipulation of the paretic side is not required. This work provides evidence for the first time that muscle activity can be evoked in the paretic leg of a hemiplegic walker in response to unilateral perturbations to the compliance of the walking surface, providing direction for targeted robot-assisted gait rehabilitation.

  10. 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

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Mejić Luka

    2017-01-01

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

  13. EMG activity and neuronal activity in the internal globus pallidus (GPi) and their interaction are different between hemiballismus and apomorphine induced dyskinesias of Parkinson's disease (AID).

    Science.gov (United States)

    Zhao, L; Verhagen-Metman, L; Kim, J H; Liu, C C; Lenz, F A

    2015-04-07

    The nature of electromyogram (EMG) activity and its relationship to neuronal activity in the internal globus pallidus (GPi) have not previously been studied in hyperkinetic movement disorders. We now test the hypothesis that GPi spike trains are cross-correlated with EMG activity during apomorphine-induced dyskinesias of Parkinson's disease (AID), and Hemiballism. We have recorded these two signals during awake stereotactic pallidal surgeries and analyzed them by cross-correlation of the raw signals and of peaks of activity occurring in those signals. EMG signals in Hemiballism usually consist of 'sharp' activity characterized by peaks of activity with low levels of activity between peaks, and by co-contraction between antagonistic muscles. Less commonly, EMG in Hemiballism shows 'non-sharp' EMG activity with substantial EMG activity between peaks; 'non-sharp' EMG activity is more common in AID. Therefore, these hyperkinetic disorders show substantial differences in peripheral (EMG) activity, although both kinds of activity can occur in both disorders. Since GPi spike×EMG spectral and time domain functions demonstrated inconsistent cross-correlation in both disorders, we studied peaks of activity in GPi neuronal and in EMG signals. The peaks of GPi activity commonly show prolonged cross-correlation with peaks of EMG activity, which suggests that GPi peaks are related to the occurrence of EMG peaks, perhaps by transmission of GPi activity to the periphery. In Hemiballism, the presence of direct GPi peak×EMG peak cross-correlations at the site where lesions relieve these disorders is evidence that gradual changes in peak GPi neuronal activity are directly involved in Hemiballism. Copyright © 2015. Published by Elsevier B.V.

  14. The eWrist - A wearable wrist exoskeleton with sEMG-based force control for stroke rehabilitation.

    Science.gov (United States)

    Lambelet, Charles; Lyu, Mingxing; Woolley, Daniel; Gassert, Roger; Wenderoth, Nicole

    2017-07-01

    Chronic wrist impairment is frequent following stroke and negatively impacts everyday life. Rehabilitation of the dysfunctional limb is possible but requires extensive training and motivation. Wearable training devices might offer new opportunities for rehabilitation. However, few devices are available to train wrist extension even though this movement is highly relevant for many upper limb activities of daily living. As a proof of concept, we developed the eWrist, a wearable one degree-of-freedom powered exoskeleton which supports wrist extension training. Conceptually one might think of an electric bike which provides mechanical support only when the rider moves the pedals, i.e. it enhances motor activity but does not replace it. Stroke patients may not have the ability to produce overt movements, but they might still be able to produce weak muscle activation that can be measured via surface electromyography (sEMG). By combining force and sEMG-based control in an assist-as-needed support strategy, we aim at providing a training device which enhances activity of the wrist extensor muscles in the context of daily life activities, thereby, driving cortical reorganization and recovery. Preliminary results show that the integration of sEMG signals in the control strategy allow for adjustable assistance with respect to a proxy measurement of corticomotor drive.

  15. 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.

  16. Zebrafish needle EMG: a new tool for high-throughput drug screens.

    Science.gov (United States)

    Cho, Sung-Joon; Nam, Tai-Seung; Byun, Donghak; Choi, Seok-Yong; Kim, Myeong-Kyu; Kim, Sohee

    2015-09-01

    Zebrafish models have recently been highlighted as a valuable tool in studying the molecular basis of neuromuscular diseases and developing new pharmacological treatments. Needle electromyography (EMG) is needed not only for validating transgenic zebrafish models with muscular dystrophies (MD), but also for assessing the efficacy of therapeutics. However, performing needle EMG on larval zebrafish has not been feasible due to the lack of proper EMG sensors and systems for such small animals. We introduce a new type of EMG needle electrode to measure intramuscular activities of larval zebrafish, together with a method to hold the animal in position during EMG, without anesthetization. The silicon-based needle electrode was found to be sufficiently strong and sharp to penetrate the skin and muscles of zebrafish larvae, and its shape and performance did not change after multiple insertions. With the use of the proposed needle electrode and measurement system, EMG was successfully performed on zebrafish at 30 days postfertilization (dpf) and at 5 dpf. Burst patterns and spike morphology of the recorded EMG signals were analyzed. The measured single spikes were triphasic with an initial positive deflection, which is typical for motor unit action potentials, with durations of ∼10 ms, whereas the muscle activity was silent during the anesthetized condition. These findings confirmed the capability of this system of detecting EMG signals from very small animals such as 5 dpf zebrafish. The developed EMG sensor and system are expected to become a helpful tool in validating zebrafish MD models and further developing therapeutics. Copyright © 2015 the American Physiological Society.

  17. 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.

  18. What is the best surface EMG measure of lumbar flexion-relaxation for distinguishing chronic low back pain patients from pain-free controls?

    Science.gov (United States)

    Neblett, Randy; Brede, Emily; Mayer, Tom G; Gatchel, Robert J

    2013-04-01

    Lumbar flexion-relaxation (FR) is a well-known phenomenon that can reliably be seen in normal subjects but not in most chronic low back pain (CLBP) patients. The purpose of this study was to determine which surface electromyographic (SEMG) measures of FR best distinguish CLBP patients from pain-free control subjects. Standing SEMG and lumbar flexion range of motion (ROM) were also evaluated. A cohort of 218 CLBP patients, who were admitted to a functional restoration program, received a standardized SEMG and ROM assessment during standing trunk flexion and reextension. An asymptomatic control group of 30 nonpatients received an identical assessment. Both groups were compared on 8 separate SEMG and 3 flexion ROM measures. A receiver operating characteristic curve analysis was used to determine how well each measure distinguished between the CLBP patients and the pain-free control subjects. All SEMG measures of FR performed acceptably. Between 79% and 82% of patients, and 83% and 100% of controls were correctly classified. Standing SEMG performed less well. Gross flexion ROM was the best single classification measure tested, correctly classifying 88% of patients and 83% of controls. A series of discriminant analyses found that certain combinations of SEMG and ROM performed slightly better than gross ROM alone for correctly classifying the 2 subjects groups. Because all SEMG measures of FR performed acceptably, the determination of which SEMG measure of FR is "best" is largely dependent on one's specific purpose. In addition, ROM measures were found to be important components of the FR assessment.

  19. 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...

  20. 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.

  1. EMG-biofeedback training in fibromyalgia syndrome.

    Science.gov (United States)

    Ferraccioli, G; Ghirelli, L; Scita, F; Nolli, M; Mozzani, M; Fontana, S; Scorsonelli, M; Tridenti, A; De Risio, C

    1987-08-01

    Fifteen patients with fibromyalgia syndrome were given EMG-BFB (biofeedback) training sessions because of persistent aches after one year of monthly courses of NSAID. A long-lasting clinical benefit was observed in 56%. The improvement was found in those without overt psychopathological disturbances. In fact, a subgroup of clinically depressed patients responded poorly. Our findings were confirmed in a controlled study. Six patients were allocated into "true EMG-BFB" and 6 into "false EMG-BFB" treatment in a blinded fashion. The rheumatological assessment revealed a significant improvement in most of the variables only in the "true EMG-BFB" group.

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

    Directory of Open Access Journals (Sweden)

    Mizrahi Joseph

    2006-11-01

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

  3. Interpreting sign components from accelerometer and sEMG data for automatic sign language recognition.

    Science.gov (United States)

    Li, Yun; Chen, Xiang; Zhang, Xu; Wang, Kongqiao; Yang, Jihai

    2011-01-01

    The identification of constituent components of each sign gesture is a practical way of establishing large-vocabulary sign language recognition (SLR) system. Aiming at developing such a system using portable accelerometer (ACC) and surface electromyographic (sEMG) sensors, this work proposes a method for automatic SLR at the component level. The preliminary experimental results demonstrate the effectiveness of the proposed method and the feasibility of interpreting sign components from ACC and sEMG data. Our study improves the performance of SLR based on ACC and sEMG sensors and will promote the realization of a large-vocabulary portable SLR system.

  4. Quantitative analysis of surface electromyography: Biomarkers for convulsive seizures.

    Science.gov (United States)

    Beniczky, Sándor; Conradsen, Isa; Pressler, Ronit; Wolf, Peter

    2016-08-01

    Muscle activity during seizures is in electroencephalographical (EEG) praxis often considered an irritating artefact. This article discusses ways by surface electromyography (EMG) to turn it into a valuable tool of epileptology. Muscles are in direct synaptic contact with motor neurons. Therefore, EMG signals provide direct information about the electric activity in the motor cortex. Qualitative analysis of EMG has traditionally been a part of the long-term video-EEG recordings. Recent development in quantitative analysis of EMG signals yielded valuable information on the pathomechanisms of convulsive seizures, demonstrating that it was different from maximal voluntary contraction, and different from convulsive psychogenic non-epileptic seizures. Furthermore, the tonic phase of the generalised tonic-clonic seizures (GTCS) proved to have different quantitative features than tonic seizures. The high temporal resolution of EMG allowed detailed characterisation of temporal dynamics of the GTCS, suggesting that the same inhibitory mechanisms that try to prevent the build-up of the seizure activity, contribute to ending the seizure. These findings have clinical implications: the quantitative EMG features provided the pathophysiologic substrate for developing neurophysiologic biomarkers that accurately identify GTCS. This proved to be efficient both for seizure detection and for objective, automated distinction between convulsive and non-convulsive epileptic seizures. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  5. 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.

  6. Mechanically corrected EMG for the continuous estimation of erector spinae muscle loading during repetitive lifting.

    Science.gov (United States)

    Potvin, J R; Norman, R W; McGill, S M

    1996-01-01

    Few studies have been carried out on the changes in biomechanical loading on low-back tissues during prolonged lifting. The purpose of this paper was to develop a model for continuously estimating erector spinae muscle loads during repetitive lifting and lowering tasks. The model was based on spine kinematics and bilateral lumbar and thoracic erector spinae electromyogram (EMG) signals and was developed with the data from eight male subjects. Each subject performed a series of isometric contractions to develop extensor moments about the low back. Maximum voluntary contractions (MVCs) were used to normalize all recorded EMG and moment time-histories. Ramp contractions were used to determine the non-linear relationship between extensor moments and EMG amplitudes. In addition, the most appropriate low-pass filter cut-off frequencies were calculated for matching the rectified EMG signals with the moment patterns. The mean low-pass cut-off frequency was 2.7 (0.4) Hz. The accuracy of the non-linear EMG-based estimates of isometric extensor moment were tested with data from a series of six rapid contractions by each subject. The mean error over the duration of these contractions was 9.2 (2.6)% MVC. During prolonged lifting sessions of 20 min and of 2 h, a model was used to calculate changes in muscle length based on monitored spine kinematics. EMG signals were first processed according to the parameters determined from the isometric contractions and then further processed to account for the effects of instantaneous muscle length and velocity. Simple EMG estimates were found to underestimate peak loading by 9.1 (4.0) and 25.7 (11.6)% MVC for eccentric and concentric phases of lifting respectively, when compared to load estimates based on the mechanically corrected EMG. To date, the model has been used to analyze over 5300 lifts.

  7. Experimentally Induced Stress Validated by EMG Activity

    Science.gov (United States)

    Luijcks, Rosan; Hermens, Hermie J.; Bodar, Lonneke; Vossen, Catherine J.; Os, Jim van.; Lousberg, Richel

    2014-01-01

    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. PMID:24736740

  8. Experimentally induced stress validated by EMG activity.

    Science.gov (United States)

    Luijcks, Rosan; Hermens, Hermie J; Bodar, Lonneke; Vossen, Catherine J; Van Os, Jim; Lousberg, Richel

    2014-01-01

    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.

  9. 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.

  10. Intensity-dependent EMG response for the biceps brachii during sustained maximal and submaximal isometric contractions.

    Science.gov (United States)

    Carr, Joshua C; Beck, Travis W; Ye, Xin; Wages, Nathan P

    2016-09-01

    There have been recent attempts to characterize the mechanisms associated with fatigue-induced task failure. We compared the time to failure and the corresponding changes in the surface electromyogram (EMG) during sustained maximal and submaximal isometric force tasks. EMG activity was measured from the biceps brachii of 18 male participants as they sustained either a maximal or submaximal (60 % MVC) isometric contraction of the dominant elbow flexors until force could not be maintained above 55 % MVC. Intensity-dependent patterns of change were observed for EMG amplitude and mean power frequency (MNF) between the two force tasks. Interestingly, the only significant predictor of failure time was the rate of change in EMG MNF during the submaximal task (r (2) = 0.304). In addition, EMG amplitude at submaximal failure was significantly lower (p EMG response emphasize the basis of neuromuscular fatigue and task dependency. Additionally, our data suggest that the EMG MNF should be used when monitoring the progression of local muscle fatigue.

  11. 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...

  12. Automatic analysis of EMG during clonus

    Science.gov (United States)

    Mummidisetty, Chaithanya K.; Bohorquez, Jorge; Thomas, Christine K

    2011-01-01

    Clonus can disrupt daily activities after spinal cord injury. Here an algorithm was developed to automatically detect contractions during clonus in 24-hour electromyographic (EMG) records. Filters were created by non-linearly scaling a Mother (Morlet) wavelet to envelope the EMG using different frequency bands. The envelope for the intermediate band followed the EMG best (74.8–193.9 Hz). Threshold and time constraints were used to reduce the envelope peaks to one per contraction. Energy in the EMG was measured 50 ms either side of each envelope (contraction) peak. Energy values at 5 % and 95 % maximal defined EMG start and end time, respectively. The algorithm was as good as a person at identifying contractions during clonus (p = 0.946, n=31 spasms, 7 subjects with cervical spinal cord injury), and marking start and end times to determine clonus frequency (intra class correlation coefficient, α: 0.949), contraction intensity using root mean square EMG (α: 0.997) and EMG duration (α: 0.852). On average the algorithm was 574 times faster than manual analysis performed independently by two people (p≤ 0.001). This algorithm is an important tool for characterization of clonus in long-term EMG records. PMID:22057220

  13. Human joint motion estimation for electromyography (EMG)-based dynamic motion control.

    Science.gov (United States)

    Zhang, Qin; Hosoda, Ryo; Venture, Gentiane

    2013-01-01

    This study aims to investigate a joint motion estimation method from Electromyography (EMG) signals during dynamic movement. In most EMG-based humanoid or prosthetics control systems, EMG features were directly or indirectly used to trigger intended motions. However, both physiological and nonphysiological factors can influence EMG characteristics during dynamic movements, resulting in subject-specific, non-stationary and crosstalk problems. Particularly, when motion velocity and/or joint torque are not constrained, joint motion estimation from EMG signals are more challenging. In this paper, we propose a joint motion estimation method based on muscle activation recorded from a pair of agonist and antagonist muscles of the joint. A linear state-space model with multi input single output is proposed to map the muscle activity to joint motion. An adaptive estimation method is proposed to train the model. The estimation performance is evaluated in performing a single elbow flexion-extension movement in two subjects. All the results in two subjects at two load levels indicate the feasibility and suitability of the proposed method in joint motion estimation. The estimation root-mean-square error is within 8.3% ∼ 10.6%, which is lower than that being reported in several previous studies. Moreover, this method is able to overcome subject-specific problem and compensate non-stationary EMG properties.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. Back muscle EMG of helicopter pilots in flight: effects of fatigue, vibration, and posture.

    Science.gov (United States)

    de Oliveira, Carlos Gomes; Nadal, Jurandir

    2004-04-01

    The high prevalence of low back pain in helicopter pilots has been attributed to back muscle fatigue due to a pilot's required posture and/or aircraft vibration. This study investigated the effect of posture and vibration on the surface electromyogram (EMG) of right and left erector spinae (ES) muscles of pilots and evaluated ES fatigue during flight. There were 12 male pilots who were monitored during helicopter flights lasting an average of 2 h. Prior to the flight, a maximal voluntary contraction (MVC) of ES was performed and the EMG was recorded. Vibration was measured at the pilot's seat through a triaxial accelerometer. The effect of posture on EMG was tested by comparing four characteristics of left and right EMG expressed as % MVC. Effect of Z vibration on EMG was investigated by coherence function and through correlation between coherently averaged EMG and Z for the frequencies of the main rotor of the helicopter (1R) and its first harmonic (2R). Fatigue was investigated through median frequencies (MF) of the EMG power spectra. No effect of posture on EMG was found for any parameter (p > 0.05). Data from one pilot suggested an effect of 1R on EMG, but statistical tests revealed this not to be significant (p > 0.05) for any pilot. No fatigue was evidenced by linear regression of MF. While the scientific literature contains the hypothesis that low back pain in helicopter pilots is mainly due to muscle fatigue caused by posture and/or vibration, the present study did not lend support to this hypothesis.

  19. A more precise, repeatable and diagnostic alternative to surface electromyography

    DEFF Research Database (Denmark)

    Harrison, Adrian P

    2018-01-01

    Acoustic myography (AMG) enables a detailed and accurate measurement of those muscles involved in a particular movement and is independent of electrical signals between the nerve and muscle, measuring solely muscle contractions, unlike surface electromyography (sEMG). With modern amplifiers and d...

  20. 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

  1. 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  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.

  2. Surface light scattering: integrated technology and signal processing

    DEFF Research Database (Denmark)

    Lading, L.; Dam-Hansen, C.; Rasmussen, E.

    1997-01-01

    systems representing increasing levels of integration are considered. It is demonstrated that efficient signal and data processing can be achieved by evaluation of the statistics of the derivative of the instantaneous phase of the detector signal. (C) 1997 Optical Society of America....

  3. An online hybrid BCI system based on SSVEP and EMG

    Science.gov (United States)

    Lin, Ke; Cinetto, Andrea; Wang, Yijun; Chen, Xiaogang; Gao, Shangkai; Gao, Xiaorong

    2016-04-01

    Objective. A hybrid brain-computer interface (BCI) is a device combined with at least one other communication system that takes advantage of both parts to build a link between humans and machines. To increase the number of targets and the information transfer rate (ITR), electromyogram (EMG) and steady-state visual evoked potential (SSVEP) were combined to implement a hybrid BCI. A multi-choice selection method based on EMG was developed to enhance the system performance. Approach. A 60-target hybrid BCI speller was built in this study. A single trial was divided into two stages: a stimulation stage and an output selection stage. In the stimulation stage, SSVEP and EMG were used together. Every stimulus flickered at its given frequency to elicit SSVEP. All of the stimuli were divided equally into four sections with the same frequency set. The frequency of each stimulus in a section was different. SSVEPs were used to discriminate targets in the same section. Different sections were classified using EMG signals from the forearm. Subjects were asked to make different number of fists according to the target section. Canonical Correlation Analysis (CCA) and mean filtering was used to classify SSVEP and EMG separately. In the output selection stage, the top two optimal choices were given. The first choice with the highest probability of an accurate classification was the default output of the system. Subjects were required to make a fist to select the second choice only if the second choice was correct. Main results. The online results obtained from ten subjects showed that the mean accurate classification rate and ITR were 81.0% and 83.6 bits min-1 respectively only using the first choice selection. The ITR of the hybrid system was significantly higher than the ITR of any of the two single modalities (EMG: 30.7 bits min-1, SSVEP: 60.2 bits min-1). After the addition of the second choice selection and the correction task, the accurate classification rate and ITR was

  4. Automatic determination of EMG-contaminated components and validation of independent component analysis using EEG during pharmacologic paralysis.

    Science.gov (United States)

    Fitzgibbon, S P; DeLosAngeles, D; Lewis, T W; Powers, D M W; Grummett, T S; Whitham, E M; Ward, L M; Willoughby, J O; Pope, K J

    2016-03-01

    Validate independent component analysis (ICA) for removal of EMG contamination from EEG, and demonstrate a heuristic, based on the gradient of EEG spectra (slope of graph of log EEG power vs log frequency, 7-70 Hz) from paralysed awake humans, to automatically identify and remove components that are predominantly EMG. We studied the gradient of EMG-free EEG spectra to quantitatively inform the choice of threshold. Then, pre-existing EEG from 3 disparate experimental groups was examined before and after applying the heuristic to validate that the heuristic preserved neurogenic activity (Berger effect, auditory odd ball, visual and auditory steady state responses). (1) ICA-based EMG removal diminished EMG contamination up to approximately 50 Hz, (2) residual EMG contamination using automatic selection was similar to manual selection, and (3) task-induced cortical activity remained, was enhanced, or was revealed using the ICA-based methodology. This study further validates ICA as a powerful technique for separating and removing myogenic signals from EEG. Automatic processing based on spectral gradients to exclude EMG-containing components is a conceptually simple and valid technique. This study strengthens ICA as a technique to remove EMG contamination from EEG whilst preserving neurogenic activity to 50 Hz. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  5. 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

  6. Relationship Between Electromyographic Signal Amplitude and Thickness Change of the Trunk Muscles in Patients With and Without Low Back Pain.

    Science.gov (United States)

    Djordjevic, Olivera; Konstantinovic, Ljubica; Miljkovic, Nadica; Bijelic, Goran

    2015-10-01

    To compare the relative thickness change of the transversal abdominal (TrA) and lumbar multifidus (LM) muscles during activation in individuals with and without low back pain (LBP), and to establish a relationship between surface electromyography (sEMG) signal amplitude and the relative thickness change of the corresponding muscle during clinically relevant activity, with preferential activation of TrA/LM. Thirty-seven pain-free participants and 36 LBP patients were assessed by ultrasound for thickness changes of TrA and LM and by sEMG for changes of electrical activity of the same muscles. sEMG is done with wireless LUMBIA system. The position of the sEMG sensors and activation maneuvers were chosen carefully. Significant group effect was found for relative thickness change of TrA (F1,142=60.69, Pchange of TrA and sEMG signal amplitude on both sides for LBP (r=0.46 to 0.63, Ppain-free patients (r=0.43-0.47, Pchange and sEMG was significant in pain-free participants for both sides (r=0.36 to 0.38 Pchange of the muscle thickness could be used as the indicator of the muscle activity. Insight into the activity of TrA/LM in pain-free individuals and LBP patients during and after painful episodes may clarify the role of functional abnormalities of these muscles in LBP.

  7. EMG Pattern Classification by Split and Merge Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Hyeon-min Shim

    2016-12-01

    Full Text Available In this paper; we introduce an enhanced electromyography (EMG pattern recognition algorithm based on a split-and-merge deep belief network (SM-DBN. Generally, it is difficult to classify the EMG features because the EMG signal has nonlinear and time-varying characteristics. Therefore, various machine-learning methods have been applied in several previously published studies. A DBN is a fast greedy learning algorithm that can identify a fairly good set of weights rapidly—even in deep networks with a large number of parameters and many hidden layers. To reduce overfitting and to enhance performance, the adopted optimization method was based on genetic algorithms (GA. As a result, the performance of the SM-DBN was 12.06% higher than conventional DBN. Additionally, SM-DBN results in a short convergence time, thereby reducing the training epoch. It is thus efficient in reducing the risk of overfitting. It is verified that the optimization was improved using GA.

  8. 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.

  9. Longitudinal high-density EMG classification: Case study in a glenohumeral TMR subject.

    Science.gov (United States)

    Schweisfurth, Meike A; Ernst, Jennifer; Vujaklija, Ivan; Schilling, Arndt F; Farina, Dario; Aszmann, Oskar C; Felmerer, Gunther

    2017-07-01

    Targeted muscle reinnervation (TMR) represents a breakthrough interface for prosthetic control in high-level upper-limb amputees. However, clinically, it is still limited to the direct motion-wise control restricted by the number of reinnervation sites. Pattern recognition may overcome this limitation. Previous studies on EMG classification in TMR patients experienced with myocontrol have shown greater accuracy when using high-density (HD) recordings compared to conventional single-channel derivations. This case study investigates the potential of HD-EMG classification longitudinally over a period of 17 months post-surgery in a glenohumeral amputee. Five experimental sessions, separated by approximately 3 months, were performed. They were timed during a standard rehabilitation protocol that included intensive physio- and occupational therapy, myosignal training, and routine use of the final myoprosthesis. The EMG signals recorded by HD-EMG grids were classified into 12 classes. The first sign of EMG activity was observed in the second experimental session. The classification accuracy over 12 classes was 76% in the third session and ∼95% in the last two sessions. When using training and testing sets that were acquired with a 1-h time interval in between, a much lower accuracy (32%, Session 4) was obtained, which improved upon prosthesis usage (Session 5, 67%). The results document the improvement in EMG classification accuracy throughout the TMR-rehabilitation process.

  10. A switching regime model for the EMG-based control of a robot arm.

    Science.gov (United States)

    Artemiadis, Panagiotis K; Kyriakopoulos, Kostas J

    2011-02-01

    Human-robot control interfaces have received increased attention during the last decades. These interfaces increasingly use signals coming directly from humans since there is a strong necessity for simple and natural control interfaces. In this paper, electromyographic (EMG) signals from the muscles of the human upper limb are used as the control interface between the user and a robot arm. A switching regime model is used to decode the EMG activity of 11 muscles to a continuous representation of arm motion in the 3-D space. The switching regime model is used to overcome the main difficulties of the EMG-based control systems, i.e., the nonlinearity of the relationship between the EMG recordings and the arm motion, as well as the nonstationarity of EMG signals with respect to time. The proposed interface allows the user to control in real time an anthropomorphic robot arm in the 3-D space. The efficiency of the method is assessed through real-time experiments of four persons performing random arm motions.

  11. Analysis of using EMG and mechanical sensors to enhance intent recognition in powered lower limb prostheses.

    Science.gov (United States)

    Young, A J; Kuiken, T A; Hargrove, L J

    2014-10-01

    The purpose of this study was to determine the contribution of electromyography (EMG) data, in combination with a diverse array of mechanical sensors, to locomotion mode intent recognition in transfemoral amputees using powered prostheses. Additionally, we determined the effect of adding time history information using a dynamic Bayesian network (DBN) for both the mechanical and EMG sensors. EMG signals from the residual limbs of amputees have been proposed to enhance pattern recognition-based intent recognition systems for powered lower limb prostheses, but mechanical sensors on the prosthesis-such as inertial measurement units, position and velocity sensors, and load cells-may be just as useful. EMG and mechanical sensor data were collected from 8 transfemoral amputees using a powered knee/ankle prosthesis over basic locomotion modes such as walking, slopes and stairs. An offline study was conducted to determine the benefit of different sensor sets for predicting intent. EMG information was not as accurate alone as mechanical sensor information (p EMG in combination with the mechanical sensor data did significantly reduce intent recognition errors (p EMG and mechanical sensors. Combining EMG and mechanical sensor data with sensor time history reduced the average transitional error from 18.4% to 12.2% and the average steady-state error from 3.8% to 1.0% when classifying level-ground walking, ramps, and stairs in eight transfemoral amputee subjects. These results suggest that a neural interface in combination with time history methods for locomotion mode classification can enhance intent recognition performance; this strategy should be considered for future real-time experiments.

  12. 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

  13. 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

  14. Homotopy based Surface Reconstruction with Application to Acoustic Signals

    DEFF Research Database (Denmark)

    Sharma, Ojaswa; Anton, François

    2011-01-01

    reconstruct information between any pair of successive cross sections are derived. The zero level set of the resulting homotopy field generates the desired surface. Four types of homotopies are suggested that are well suited to generate a smooth surface. We also provide derivation of necessary higher order...

  15. Validity and feasibility of the EMG direct observation tool (EMG-DOT).

    Science.gov (United States)

    Leep Hunderfund, Andrea N; Rubin, Devon I; Laughlin, Ruple S; Sorenson, Eric J; Watson, James C; Jones, Lyell K; Juul, Dorthea; Park, Yoon Soo

    2016-04-26

    To develop a new workplace-based EMG direct observation tool (EMG-DOT) and gather validity evidence supporting its use for assessing electrodiagnostic skills among postgraduate medical trainees. The EMG-DOT was developed by experts using an iterative process. Validity evidence from content, response process, internal structure, relations to other variables, and consequences of testing was collected during the 2013-2014 academic year. Of 3,412 studies performed by trainees during the study period, 299 (9%) were assessed using the EMG-DOT. Of these, 203 (68%) involved a physician rater and 96 (32%) involved a technician rater. The 14-item EMG-DOT had excellent internal-consistency reliability (Cronbach α 0.94). Correlations between individual items and criterion-referenced global ratings of performance ranged from 0.36 to 0.72 (all p EMG rotation (p EMG-DOT improved the quality of care provided to patients in 58% (133/230). Trainees were "satisfied" or "very satisfied" with the observational assessment exercise in 96% of encounters (234/243). This study provides validity evidence supporting the use of EMG-DOT scores to assess electrodiagnostic skills of residents and fellows. The EMG-DOT can be used to inform milestone-based assessments of trainee performance in neurology, child neurology, physical medicine and rehabilitation, neuromuscular, and clinical neurophysiology training programs. © 2016 American Academy of Neurology.

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

    Science.gov (United States)

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

    2014-05-01

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

  17. Paralyzed subject controls telepresence mobile robot using novel sEMG brain-computer interface: case study.

    Science.gov (United States)

    Lyons, Kenneth R; Joshi, Sanjay S

    2013-06-01

    Here we demonstrate the use of a new singlesignal surface electromyography (sEMG) brain-computer interface (BCI) to control a mobile robot in a remote location. Previous work on this BCI has shown that users are able to perform cursor-to-target tasks in two-dimensional space using only a single sEMG signal by continuously modulating the signal power in two frequency bands. Using the cursor-to-target paradigm, targets are shown on the screen of a tablet computer so that the user can select them, commanding the robot to move in different directions for a fixed distance/angle. A Wifi-enabled camera transmits video from the robot's perspective, giving the user feedback about robot motion. Current results show a case study with a C3-C4 spinal cord injury (SCI) subject using a single auricularis posterior muscle site to navigate a simple obstacle course. Performance metrics for operation of the BCI as well as completion of the telerobotic command task are developed. It is anticipated that this noninvasive and mobile system will open communication opportunities for the severely paralyzed, possibly using only a single sensor.

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

    Science.gov (United States)

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

    2015-11-01

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

  19. Electromyography and Mechanomyography Signals During Swallowing in Healthy Adults and Head and Neck Cancer Survivors.

    Science.gov (United States)

    Constantinescu, Gabriela; Hodgetts, William; Scott, Dylan; Kuffel, Kristina; King, Ben; Brodt, Chris; Rieger, Jana

    2017-02-01

    Surface electromyography (sEMG) is used as an adjuvant to dysphagia therapy to demonstrate the activity of submental muscles during swallowing exercises. Mechanomyography (MMG) has been suggested as a potential superior alternative to sEMG; however, this advantage is not confirmed for signal acquired from submental muscles. This study compared the signal-to-noise ratio (SNR) obtained from sEMG and MMG sensors during swallowing tasks, in healthy participants and those with a history of head and neck cancer (HNC), a population with altered anatomy and a high incidence of dysphagia. Twenty-two healthy adults and 10 adults with a history of HNC participated in this study. sEMG and MMG signals were acquired during dry, thin liquid, effortful, and Mendelsohn maneuver swallows. SNR was compared between the two sensors using repeated measures ANOVAs and subsequent planned pairwise comparisons. Test-retest measures were collected on 20 % of participants. In healthy participants, MMG SNR was higher than that of sEMG for dry [t(21) = -3.02, p = 0.007] and thin liquid swallows [t(21) = -4.24, p < 0.001]. Although a significant difference for sensor was found in HNC participants F(1,9) = 5.54, p = 0.043, planned pairwise comparisons by task revealed no statistically significant difference between the two sensors. sEMG also showed much better test-retest reliability than MMG. Biofeedback provided as an adjuvant to dysphagia therapy in patients with HNC should employ sEMG technology, as this sensor type yielded better SNR and overall test-retest reliability. Poor MMG test-retest reliability was noted in both healthy and HNC participants and may have been related to differences in sensor application.

  20. 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

  1. Comparison of Constant-Posture Force-Varying EMG-Force Dynamic Models About the Elbow.

    Science.gov (United States)

    Dai, Chenyun; Bardizbanian, Berj; Clancy, Edward A

    2017-09-01

    Numerous techniques have been used to minimize error in relating the surface electromyogram (EMG) to elbow joint torque. We compare the use of three techniques to further reduce error. First, most EMG-torque models only use estimates of EMG standard deviation as inputs. We studied the additional features of average waveform length, slope sign change rate and zero crossing rate. Second, multiple channels of EMG from the biceps, and separately from the triceps, have been combined to produce two low-variance model inputs. We contrasted this channel combination with using each EMG separately. Third, we previously modeled nonlinearity in the EMG-torque relationship via a polynomial. We contrasted our model versus that of the classic exponential power law of Vredenbregt and Rau (1973). Results from 65 subjects performing constant-posture, force-varying contraction gave a "baseline" comparison error (i.e., error with none of the new techniques) of 5.5 ± 2.3% maximum flexion voluntary contraction (%MVC F ). Combining the techniques of multiple features with individual channels reduced error to 4.8 ± 2.2 %MVC F , while combining individual channels with the power-law model reduced error to 4.7 ± 2.0 %MVC F . The new techniques further reduced error from that of the baseline by ≈ 15 %.

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

    Science.gov (United States)

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

    2016-07-01

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

  3. Single-Channel EMG Classification With Ensemble-Empirical-Mode-Decomposition-Based ICA for Diagnosing Neuromuscular Disorders.

    Science.gov (United States)

    Naik, Ganesh R; Selvan, S Easter; Nguyen, Hung T

    2016-07-01

    An accurate and computationally efficient quantitative analysis of electromyography (EMG) signals plays an inevitable role in the diagnosis of neuromuscular disorders, prosthesis, and several related applications. Since it is often the case that the measured signals are the mixtures of electric potentials that emanate from surrounding muscles (sources), many EMG signal processing approaches rely on linear source separation techniques such as the independent component analysis (ICA). Nevertheless, naive implementations of ICA algorithms do not comply with the task of extracting the underlying sources from a single-channel EMG measurement. In this respect, the present work focuses on a classification method for neuromuscular disorders that deals with the data recorded using a single-channel EMG sensor. The ensemble empirical mode decomposition algorithm decomposes the single-channel EMG signal into a set of noise-canceled intrinsic mode functions, which in turn are separated by the FastICA algorithm. A reduced set of five time domain features extracted from the separated components are classified using the linear discriminant analysis, and the classification results are fine-tuned with a majority voting scheme. The performance of the proposed method has been validated with a clinical EMG database, which reports a higher classification accuracy (98%). The outcome of this study encourages possible extension of this approach to real settings to assist the clinicians in making correct diagnosis of neuromuscular disorders.

  4. Arrays of surface-normal electroabsorption modulators for the generation and signal processing of microwave photonics signals

    NARCIS (Netherlands)

    Noharet, Bertrand; Wang, Qin; Platt, Duncan; Junique, Stéphane; Marpaung, D.A.I.; Roeloffzen, C.G.H.

    2011-01-01

    The development of an array of 16 surface-normal electroabsorption modulators operating at 1550nm is presented. The modulator array is dedicated to the generation and processing of microwave photonics signals, targeting a modulation bandwidth in excess of 5GHz. The hybrid integration of the

  5. Further observations on the relationship of EMG and muscle force

    Science.gov (United States)

    Agarwal, G. C.; Cecchini, L. R.; Gottlieb, G. L.

    1972-01-01

    Human skeletal muscle may be regarded as an electro-mechanical transducer. Its physiological input is a neural signal originating at the alpha motoneurons in the spinal cord and its output is force and muscle contraction, these both being dependent on the external load. Some experimental data taken during voluntary efforts around the ankle joint and by direct electrical stimulation of the nerve are described. Some of these experiments are simulated by an analog model, the input of which is recorded physiological soleus muscle EMG. The output is simulated foot torque. Limitations of a linear model and effect of some nonlinearities are discussed.

  6. Physical Reflectivity and Polarization Characteristics for Snow and Ice-Covered Surfaces Interacting with GPS Signals

    Directory of Open Access Journals (Sweden)

    Shuanggen Jin

    2013-08-01

    Full Text Available The Global Positioning System (GPS reflected signal has been demonstrated to remotely sense the oceans, land surfaces and the cryosphere, including measuring snow depth, soil moisture, vegetation growth and wind direction. Since the Earth surface’s characteristics are very complex, the surface reflectivity process and interaction with GPS signals is not well understood. In this study, we investigate the surface’s reflectivity and variability of snow and ice surfaces interacting with GPS L1 and L2 signals in order to retrieve multipath signals and infer surface characteristics by using the direct and reflected polarizations of each signal. Firstly, the effects of both GPS satellite elevation angle and GPS receiver’s antenna height variations on the multipath signal variability have been investigated by numerical formulations. Secondly, the specular reflection coefficients’ features and the total surface polarization for liquid and solid surfaces are discussed. Moreover, the linear polarization and circular polarizations (co-polarized and cross-polarized as well as their corresponding convolution functions are developed horizontally and vertically. The results show that the multipath signals are more sensitive to the satellite elevation angle variations than to changes in the GPS receiver’s antenna height. The convolution function demonstrates that the snowy surface has a minimum reflectance in circular polarization but maximum reflectance in linear polarization. GPS signals reflecting from an ice-covered surface show a maximum value in circular polarization reflectance and a minimum for linear polarization reflectance. Moreover, the values for reflection from soils are between those for snow and ice in all polarization types. The placement of soil surface reflectance values between snowy and icy surface ones may be noteworthy in new remote sensing applications.

  7. Cell surface topology creates high Ca2+ signalling microdomains

    DEFF Research Database (Denmark)

    Brasen, Jens Christian; Olsen, Lars Folke; Hallett, Maurice B

    2010-01-01

    of a smooth cell surface predicts only moderate localized effects, the more realistic "wrinkled" surface topology predicts that Ca2+ concentrations up to 80 microM can persist within the folds of membranes for significant times. This intra-wrinkle location may account for 5% of the total cell volume. Using...... different geometries of wrinkles, our simulations show that high Ca2+ microdomains will be generated most effectively by long narrow membrane wrinkles of similar dimensions to those found experimentally. This is a new concept which has not previously been considered, but which has ramifications as the intra-wrinkle...

  8. Iridescent flowers? : Contribution of surface structures to optical signaling

    NARCIS (Netherlands)

    van der Kooi, Casper J.; Wilts, Bodo D.; Leertouwer, Hein L.; Staal, Marten; Elzenga, J. Theo M.; Stavenga, Doekele G.

    The color of natural objects depends on how they are structured and pigmented. In flowers, both the surface structure of the petals and the pigments they contain determine coloration. The aim of the present study was to assess the contribution of structural coloration, including iridescence, to

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Arakaki Juliano

    2006-07-01

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

  11. 1 μm-thickness ultra-flexible and high electrode-density surface electromyogram measurement sheet with 2 V organic transistors for prosthetic hand control.

    Science.gov (United States)

    Fuketa, Hiroshi; Yoshioka, Kazuaki; Shinozuka, Yasuhiro; Ishida, Koichi; Yokota, Tomoyuki; Matsuhisa, Naoji; Inoue, Yusuke; Sekino, Masaki; Sekitani, Tsuyoshi; Takamiya, Makoto; Someya, Takao; Sakurai, Takayasu

    2014-12-01

    A 64-channel surface electromyogram (EMG) measurement sheet (SEMS) with 2 V organic transistors on a 1 μm-thick ultra-flexible polyethylene naphthalate (PEN) film is developed for prosthetic hand control. The surface EMG electrodes must satisfy the following three requirements; high mechanical flexibility, high electrode density and high signal integrity. To achieve high electrode density and high signal integrity, a distributed and shared amplifier (DSA) architecture is proposed, which enables an in-situ amplification of the myoelectric signal with a fourfold increase in EMG electrode density. In addition, a post-fabrication select-and-connect (SAC) method is proposed to cope with the large mismatch of organic transistors. The proposed SAC method reduces the area and the power overhead by 96% and 98.2%, respectively, compared with the use of conventional parallel transistors to reduce the transistor mismatch by a factor of 10.

  12. The Activity of Surface Electromyographic Signal of Selected Muscles during Classic Rehabilitation Exercise

    OpenAIRE

    Jinzhuang Xiao; Jinli Sun; Junmin Gao; Hongrui Wang; Xincai Yang

    2016-01-01

    Objectives. Prone bridge, unilateral bridge, supine bridge, and bird-dog are classic rehabilitation exercises, which have been advocated as effective ways to improve core stability among healthy individuals and patients with low back pain. The aim of this study was to investigate the activity of seven selected muscles during rehabilitation exercises through the signal of surface electromyographic. Approaches. We measured the surface electromyographic signals of four lower limb muscles, two ab...

  13. Characterization of five novel Pseudomonas aeruginosa cell-surface signalling systems

    NARCIS (Netherlands)

    Llamas, María A.; Mooij, Marlies J.; Sparrius, Marion; Vandenbroucke-Grauls, Christina M. J. E.; Ratledge, Colin; Bitter, Wilbert

    2008-01-01

    Cell-surface signalling is a sophisticated regulatory mechanism used by Gram-negative bacteria to sense signals from outside the cell and transmit them into the cytoplasm. This regulatory system consists of an outer membrane-localized TonB-dependent receptor (TonB-dependent transducer), a

  14. Normalizing EMG to Background Muscle Activation Masks Medication-Induced Reductions in Reflex Amplitudes in Parkinsonian Rigidity.

    Science.gov (United States)

    Powell, Douglas; Muthumani, Anburaj; Xia, Rui-Ping

    2017-02-01

    Exaggerated reflex responses to passive stretch and shortening contribute to parkinsonian rigidity. Studies have reported medication-induced reductions in rigidity in the absence of attenuated reflex magnitudes. The purpose of this study was to determine if normalization procedures mask medication-induced reductions in reflex responses in Parkinson's disease. Twelve participants with PD performed passive wrist flexion and extension movements after a 12-hour withdrawal from dopaminergic medication and 60 minutes after medication was administered. EMG was recorded from wrist flexors and extensors. Raw EMG signals were conditioned and normalized to mean background EMG amplitudes collected 100 ms prior to the onset of passive movement by division and by subtraction. Raw EMG amplitudes were significantly reduced. No medication-related reductions were observed during passive flexion or extension when EMG amplitudes were normalized by division. When EMG amplitudes were normalized by subtraction, significant reductions were observed following administration of dopaminergic medication during flexion and extension. Dopaminergic medication was associated with significant reductions in rigidity work scores and significant increases in moment-angle slope plots. These findings demonstrate that EMG normalization techniques may hinder data interpretation in studies of altered reflex responses in individuals with Parkinson's disease following the administration of dopaminergic medication.

  15. 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.

  16. DMPD: Innate immune sensing of pathogens and danger signals by cell surface Toll-likereceptors. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 17275324 Innate immune sensing of pathogens and danger signals by cell surface Toll... Show Innate immune sensing of pathogens and danger signals by cell surface Toll-likereceptors. PubmedID 172...75324 Title Innate immune sensing of pathogens and danger signals by cell surface

  17. The Probing Radio Signal Polarization Effect on Separation Efficiency of Surface Target Response

    Directory of Open Access Journals (Sweden)

    A. N. Pinchuk

    2015-01-01

    Full Text Available The aim of the study was a quantitative analysis of the level of interference with radar monitoring characteristics of surface targets, caused by the scattered electromagnetic field, arising due to the interaction between radio waves and sea surface, which is a study aspect a radiooceanography encompasses. Backscatter signal, arising from the interaction of radio waves and sea surface, extends in a direction opposite the probing radar signal of spread marine and coastal radar stations.With radar sounding of sea surface at high incidence angles of radio waves, a basic physical mechanism to form the received signal is resonant (Bragg scattering, and at small incidence angles of radio waves it is quasi-specular reflection. Consequently, the energy of electromagnetic radiation, backscattered by the sea surface, depends on the type of wave polarization: for horizontal polarization it is less than for vertical one.The paper presents a mathematical model, which describes dependence of interference level caused by interaction between radio waves and sea surface, on the radio wave polarization for the case when the same polarization is used to sent-out and receive a radio wave.To determine the noise reduction to be achievable with radar monitoring the surface targets by selecting the polarization of the probing radar signal, a signal/noise ratio is analyzed for its different polarizations.It is shown that in order to reduce the noise level caused by the interaction between radio waves and sea surface, it is possible to use the differences in the level of scattered radio signals of different polarization: with horizontally-polarized radar operation at incidence angles of 75°- 85° a signal/noise ratio is by 20-35 dB higher than that of vertically- polarized one.

  18. 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.

  19. 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.

  20. Optimal stimulation during monitored thyroid surgery: EMG response characteristics in a porcine model.

    Science.gov (United States)

    Wu, Che-Wei; Liu, Xiaoli; Barczyński, Marcin; Kim, Hoon Yub; Dionigi, Gianlorenzo; Sun, Hui; Chiang, Feng-Yu; Kamani, Dipti; Randolph, Gregory W

    2017-04-01

    To compare electromyography (EMG) characteristics of the external branch of superior laryngeal nerve (EBSLN), recurrent laryngeal nerve (RLN), and vagus nerve (VN) evoked with different stimulation probes/dissectors during monitored thyroid surgery. Experimental porcine model. In five piglets (10 EBSLNs/RLNs/VNs), laryngeal EMG was recorded by endotracheal tube surface electrodes with stimulation using five monopolar probes (group I), three bipolar probes (group II), and two stimulation dissectors (group III). The detectable EMG response (DER) was defined as > 100 μV and was obtained with these different probes/dissectors. Electromyography parameters, stimulus-response curve, and distance-sensitivity results were compared. All stimulation probes/dissectors evoked typical EMG waveforms from the EBSLN/RLN/VN with 1 mA current. A stimulus-response curve with increasing EMG amplitude with increase in stimulating current was noted, with the maximum EMG elicited by group I/III probes/dissectors at EMG amplitudes when the nerve was stimulated with overlying fascia or when probe/dissector to nerve distance was greater. The mean amplitude decreased by 11%/33%/13% in group I/II/III probes/dissectors when stimulating nerves covered by fascia versus nerves dissected free of overlying fascia. The rate of obtaining DER at 1- or 2-mm distance was significantly higher in group I than in group II/III probes/dissectors (P < 0.001). Latency did not change with any of the stimulation probes/dissectors or trials. Monopolar, bipolar probes, and newer stimulation dissectors all provided valid evoked VN/RLN/EBSLN waveforms. They have different functional sensitivity profiles and vary when stimulating with fascia and at a distance from the nerve. Selection of a stimulation probe/dissector for nerve monitoring can be based on the stimulation characteristics, the intended nerve monitoring application, and the surgeon's preference. N/A. Laryngoscope, 127:998-1005, 2017. © 2016 The American

  1. 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.

  2. Technical Device for Prevention of Spinal Column Disorders. Pilot EMG Study for Estimation of Back Muscle Activity

    Directory of Open Access Journals (Sweden)

    Rositza Raikova

    2011-07-01

    Full Text Available One possible cause of abnormal spinal column curvatures in adolescents is standing in “bad posture” for a long time. If this bad habit can be corrected on time, by creating a dynamic stereotype for correct body position maintenance, further health problems can be avoided. To present a technical device for prevention of scoliotic deformations signaling when the angles of inclination forward or sideward are bigger than preliminary set ones. To elaborate an experimental protocol based on analysis of EMG activity (EMGs of spine muscles for verification of its effect. Study design: Devising of the device and of software for EMGs processing. Pilot experiments were conducted recording EMGs of eight spinal muscles for estimation of the device efficiency. Different mathematical procedures were proposed and programmed for data processing and illustration. Two device prototypes (with sound and vibration signal are developed and experimentally used. EMG data from 20 motor tasks (half of them with carrying the device are processed. The device can be used as a simple tool for biofeedback-type pupil teaching of dynamic stereotype for right posture maintenance. The developed software for EMGs processing can be used for tracing the effect of using the device.

  3. 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 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.

  4. Muscle synergy control model-tuned EMG driven torque estimation system with a musculo-skeletal model.

    Science.gov (United States)

    Min, Kyuengbo; Shin, Duk; Lee, Jongho; Kakei, Shinji

    2013-01-01

    Muscle activity is the final signal for motion control from the brain. Based on this biological characteristic, Electromyogram (EMG) signals have been applied to various systems that interface human with external environments such as external devices. In order to use EMG signals as input control signal for this kind of system, the current EMG driven torque estimation models generally employ the mathematical model that estimates the nonlinear transformation function between the input signal and the output torque. However, these models need to estimate too many parameters and this process cause its estimation versatility in various conditions to be poor. Moreover, as these models are designed to estimate the joint torque, the input EMG signals are tuned out of consideration for the physiological synergetic contributions of multiple muscles for motion control. To overcome these problems of the current models, we proposed a new tuning model based on the synergy control mechanism between multiple muscles in the cortico-spinal tract. With this synergetic tuning model, the estimated contribution of multiple muscles for the motion control is applied to tune the EMG signals. Thus, this cortico-spinal control mechanism-based process improves the precision of torque estimation. This system is basically a forward dynamics model that transforms EMG signals into the joint torque. It should be emphasized that this forward dynamics model uses a musculo-skeletal model as a constraint. The musculo-skeletal model is designed with precise musculo-skeletal data, such as origins and insertions of individual muscles or maximum muscle force. Compared with the mathematical model, the proposed model can be a versatile model for the torque estimation in the various conditions and estimates the torque with improved accuracy. In this paper, we also show some preliminary experimental results for the discussion about the proposed model.

  5. Intra-Individual Variability of Surface Electromyography in Front Crawl Swimming.

    Science.gov (United States)

    Martens, Jonas; Daly, Daniel; Deschamps, Kevin; Fernandes, Ricardo Jorge Pinto; Staes, Filip

    2015-01-01

    The variability of electromyographic (EMG) recordings between and within participants is a complex problem, rarely studied in swimming. The importance of signal normalization has long been recognized, but the method used might influence variability. The aims of this study were to: (i) assess the intra-individual variability of the EMG signal in highly skilled front crawl swimmers, (ii) determine the influence of two methods of both amplitude and time normalization of the EMG signal on intra-individual variability and of time normalization on muscle activity level and (iii) describe the muscle activity, normalized using MVIC, in relation to upper limb crawl stroke movements. Muscle activity of rectus abdominis and deltoideus medialis was recorded using wireless surface EMG in 15 adult male competitive swimmers during three trials of 12.5 m front crawl at maximal speed without breathing. Two full upper limb cycles were analyzed from each of the swimming trials, resulting in six full cycles used for the intra-individual variability assessment, quantified with the coefficient of variation (CV), coefficient of quartile variation (CQV) and the variance ratio (VR). The results of this study support previous findings on EMG patterns of deltoideus medialis and rectus abdominis as prime mover during the recovery (45% activity relative to MVIC), and stabilizer of the trunk during the pull (14.5% activity) respectively. The intra-individual variability was lower (VR of 0.34-0.47) when compared to other cyclic movements. No meaningful differences were found between variability measures CV or VR when applying either of the amplitude or the time normalization methods. In addition to reporting the mean amplitude and standard deviation, future EMG studies in swimming should also report the intra-individual variability, preferably using VR as it is independent of peak amplitude, provides a good measure of repeatability and is insensitive to mean EMG amplitude and the degree of

  6. Intra-Individual Variability of Surface Electromyography in Front Crawl Swimming.

    Directory of Open Access Journals (Sweden)

    Jonas Martens

    Full Text Available The variability of electromyographic (EMG recordings between and within participants is a complex problem, rarely studied in swimming. The importance of signal normalization has long been recognized, but the method used might influence variability. The aims of this study were to: (i assess the intra-individual variability of the EMG signal in highly skilled front crawl swimmers, (ii determine the influence of two methods of both amplitude and time normalization of the EMG signal on intra-individual variability and of time normalization on muscle activity level and (iii describe the muscle activity, normalized using MVIC, in relation to upper limb crawl stroke movements. Muscle activity of rectus abdominis and deltoideus medialis was recorded using wireless surface EMG in 15 adult male competitive swimmers during three trials of 12.5 m front crawl at maximal speed without breathing. Two full upper limb cycles were analyzed from each of the swimming trials, resulting in six full cycles used for the intra-individual variability assessment, quantified with the coefficient of variation (CV, coefficient of quartile variation (CQV and the variance ratio (VR. The results of this study support previous findings on EMG patterns of deltoideus medialis and rectus abdominis as prime mover during the recovery (45% activity relative to MVIC, and stabilizer of the trunk during the pull (14.5% activity respectively. The intra-individual variability was lower (VR of 0.34-0.47 when compared to other cyclic movements. No meaningful differences were found between variability measures CV or VR when applying either of the amplitude or the time normalization methods. In addition to reporting the mean amplitude and standard deviation, future EMG studies in swimming should also report the intra-individual variability, preferably using VR as it is independent of peak amplitude, provides a good measure of repeatability and is insensitive to mean EMG amplitude and the

  7. Aerosol optical depth under "clear" sky conditions derived from sea surface reflection of lidar signals.

    Science.gov (United States)

    He, Min; Hu, Yongxiang; Huang, Jian Ping; Stamnes, Knut

    2016-12-26

    There are considerable demands for accurate atmospheric correction of satellite observations of the sea surface or subsurface signal. Surface and sub-surface reflection under "clear" atmospheric conditions can be used to study atmospheric correction for the simplest possible situation. Here "clear" sky means a cloud-free atmosphere with sufficiently small aerosol particles. The "clear" aerosol concept is defined according to the spectral dependence of the scattering cross section on particle size. A 5-year combined CALIPSO and AMSR-E data set was used to derive the aerosol optical depth (AOD) from the lidar signal reflected from the sea surface. Compared with the traditional lidar-retrieved AOD, which relies on lidar backscattering measurements and an assumed lidar ratio, the AOD retrieved through the surface reflectance method depends on both scattering and absorption because it is based on two-way attenuation of the lidar signal transmitted to and then reflected from the surface. The results show that the clear sky AOD derived from the surface signal agrees with the clear sky AOD available in the CALIPSO level 2 database in the westerly wind belt located in the southern hemisphere, but yields significantly higher aerosol loadings in the tropics and in the northern hemisphere.

  8. The Effectiveness of FES-Evoked EMG Potentials to Assess Muscle Force and Fatigue in Individuals with Spinal Cord Injury

    Directory of Open Access Journals (Sweden)

    Morufu Olusola Ibitoye

    2014-07-01

    Full Text Available The evoked electromyographic signal (eEMG potential is the standard index used to monitor both electrical changes within the motor unit during muscular activity and the electrical patterns during evoked contraction. However, technical and physiological limitations often preclude the acquisition and analysis of the signal especially during functional electrical stimulation (FES-evoked contractions. Hence, an accurate quantification of the relationship between the eEMG potential and FES-evoked muscle response remains elusive and continues to attract the attention of researchers due to its potential application in the fields of biomechanics, muscle physiology, and rehabilitation science. We conducted a systematic review to examine the effectiveness of eEMG potentials to assess muscle force and fatigue, particularly as a biofeedback descriptor of FES-evoked contractions in individuals with spinal cord injury. At the outset, 2867 citations were identified and, finally, fifty-nine trials met the inclusion criteria. Four hypotheses were proposed and evaluated to inform this review. The results showed that eEMG is effective at quantifying muscle force and fatigue during isometric contraction, but may not be effective during dynamic contractions including cycling and stepping. Positive correlation of up to r = 0.90 (p < 0.05 between the decline in the peak-to-peak amplitude of the eEMG and the decline in the force output during fatiguing isometric contractions has been reported. In the available prediction models, the performance index of the eEMG signal to estimate the generated muscle force ranged from 3.8% to 34% for 18 s to 70 s ahead of the actual muscle force generation. The strength and inherent limitations of the eEMG signal to assess muscle force and fatigue were evident from our findings with implications in clinical management of spinal cord injury (SCI population.

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

    Science.gov (United States)

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

    2015-01-01

    Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for partial-hand applications. PMID:25955989

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

    Directory of Open Access Journals (Sweden)

    Irfan Hussain

    2016-11-01

    Full Text Available In this paper, we present an electromyographic (EMG control interface for a supernumerary robotic finger. This novel wearable robot can be used to compensate the missing grasping abilities in chronic stroke patients or to augment human healthy hand so to enhance its grasping capabilities and workspace. The proposed EMG interface controls the motion of the robotic extra finger and its joint compliance. 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 validated the proposed interface with two sets of experiments related to compensation and augmentation. In the first set of experiments, different bi-manual tasks have been performed with the help of the robotic device and simulating a paretic hand. In the second set, the robotic extra finger is used to enlarge the workspace and manipulation capability of healthy hands. In both the sets, the same EMG control interface has been used. The obtained results demonstrate that the proposed control interface is intuitive and can successfully be used for both compensation and augmentation purposes. The proposed approach can be exploited also for the control of different wearable devices that has to actively cooperate with the human limbs.

  11. Detection of non-standard EMG profiles in walking

    NARCIS (Netherlands)

    Hof, A.L.; Elzinga, H.; Grimmius, W.; Halbertsma, J.P.

    The amplitude of an EMG and the temporal pattern can be used when considering if an EMG profile is normal or not. In the method described in this paper a gain factor of the complete EMG profile was determined and then the profile normalised with this gain factor. This normalised individual profile

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

    OpenAIRE

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

    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 m...

  13. Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix.

    Science.gov (United States)

    Naik, Ganesh R; Acharyya, Amit; Nguyen, Hung T

    2014-01-01

    This paper reports the classification of finger flexion and extension of surface Electromyography (EMG) and Cyberglove data using the modified Independent Component Analysis (ICA) weight matrix. The finger flexion and extension data are processed through Principal Component Analysis (PCA), and next separated using modified ICA for each individual with customized weight matrix. The extension and flexion features of sEMG and Cyberglove (extracted from modified ICA) were classified using Linear Discriminant Analysis (LDA) with near 90% classification accuracy. The applications of this study include Human Computer Interface (HCI), virtual reality and neural prosthetics.

  14. 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...... as the mutual electrical influence between the electrode surfaces. A three-dimensional sensitivity function is defined from which information about the preferential direction of sensitivity, blind spots, phase changes, rate of attenuation, and range of pick-up radius can be derived. The study focuses...

  15. The influence of digital filter type, amplitude normalisation method, and co-contraction algorithm on clinically relevant surface electromyography data during clinical movement assessments.

    Science.gov (United States)

    Devaprakash, Daniel; Weir, Gillian J; Dunne, James J; Alderson, Jacqueline A; Donnelly, Cyril J

    2016-12-01

    There is a large and growing body of surface electromyography (sEMG) research using laboratory-specific signal processing procedures (i.e., digital filter type and amplitude normalisation protocols) and data analyses methods (i.e., co-contraction algorithms) to acquire practically meaningful information from these data. As a result, the ability to compare sEMG results between studies is, and continues to be challenging. The aim of this study was to determine if digital filter type, amplitude normalisation method, and co-contraction algorithm could influence the practical or clinical interpretation of processed sEMG data. Sixteen elite female athletes were recruited. During data collection, sEMG data was recorded from nine lower limb muscles while completing a series of calibration and clinical movement assessment trials (running and sidestepping). Three analyses were conducted: (1) signal processing with two different digital filter types (Butterworth or critically damped), (2) three amplitude normalisation methods, and (3) three co-contraction ratio algorithms. Results showed the choice of digital filter did not influence the clinical interpretation of sEMG; however, choice of amplitude normalisation method and co-contraction algorithm did influence the clinical interpretation of the running and sidestepping task. Care is recommended when choosing amplitude normalisation method and co-contraction algorithms if researchers/clinicians are interested in comparing sEMG data between studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. 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…

  17. 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.

  18. 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

  19. 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

  20. Time-of-Day Effects on EMG Parameters During the Wingate Test in Boys

    National Research Council Canada - National Science Library

    Souissi, Hichem; Chtourou, Hamdi; Chaouachi, Anis; Chamari, Karim; Souissi, Nizar; Amri, Mohamed

    2012-01-01

    ... (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...

  1. Signal Processing for Determining Water Height in Steam Pipes with Dynamic Surface Conditions

    Science.gov (United States)

    Lih, Shyh-Shiuh; Lee, Hyeong Jae; Bar-Cohen, Yoseph

    2015-01-01

    An enhanced signal processing method based on the filtered Hilbert envelope of the auto-correlation function of the wave signal has been developed to monitor the height of condensed water through the steel wall of steam pipes with dynamic surface conditions. The developed signal processing algorithm can also be used to estimate the thickness of the pipe to determine the cut-off frequency for the low pass filter frequency of the Hilbert Envelope. Testing and analysis results by using the developed technique for dynamic surface conditions are presented. A multiple array of transducers setup and methodology are proposed for both the pulse-echo and pitch-catch signals to monitor the fluctuation of the water height due to disturbance, water flow, and other anomaly conditions.

  2. Determination of an Optimal Threshold Value for Muscle Activity Detection in EMG Analysis

    Science.gov (United States)

    Özgünen, Kerem Tuncay; Çelik, Umut; Kurdak, Sanlı Sadi

    2010-01-01

    It is commonly agreed that one needs to use a threshold value in the detection of muscle activity timing in electromyographic (EMG) signal analysis. However, the algorithm for threshold determination lacks an agreement between the investigators. In this study we aimed to determine a proper threshold value in an incremental cycling exercise for accurate EMG signal analysis. Nine healthy recreationally active male subjects cycled until exhaustion. EMG recordings were performed on four low extremity muscle groups; gastrocnemius lateralis (GL), gastrocnemius medialis (GM), soleus (SOL) and vastus medialis (VM). We have analyzed our data using three different threshold levels: 25%, 35% and 45% of the mean RMS EMG value. We compared the appropriateness of these threshold values using two criteria: (1) significant correlation between the actual and estimated number of bursts and (2) proximity of the regression line of the actual and estimated number of bursts to the line of identity. It had been possible to find a significant correlation between the actual and estimated number of bursts with the 25, 35 and 45% threshold values for the GL muscle. Correlation analyses for the VM muscle had shown that the number of bursts estimated with the 35% threshold value was found to be significantly correlated with the actual number of bursts. For the GM muscle, it had been possible to predict the burst number by using either the 35% or 45% threshold value and for the SOL muscle the 25% threshold value was found as the best predictor for actual number of burst estimation. Detailed analyses of the actual and estimated number of bursts had shown that success of threshold estimation may differ among muscle groups. Evaluation of our data had clearly shown that it is important to select proper threshold values for correct EMG signal analyses. Using a single threshold value for different exercise intensities and different muscle groups may cause misleading results. Key points α priori

  3. Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning

    Science.gov (United States)

    García Plaza, E.; Núñez López, P. J.

    2018-01-01

    On-line monitoring of surface finish in machining processes has proven to be a substantial advancement over traditional post-process quality control techniques by reducing inspection times and costs and by avoiding the manufacture of defective products. This study applied techniques for processing cutting force signals based on the wavelet packet transform (WPT) method for the monitoring of surface finish in computer numerical control (CNC) turning operations. The behaviour of 40 mother wavelets was analysed using three techniques: global packet analysis (G-WPT), and the application of two packet reduction criteria: maximum energy (E-WPT) and maximum entropy (SE-WPT). The optimum signal decomposition level (Lj) was determined to eliminate noise and to obtain information correlated to surface finish. The results obtained with the G-WPT method provided an in-depth analysis of cutting force signals, and frequency ranges and signal characteristics were correlated to surface finish with excellent results in the accuracy and reliability of the predictive models. The radial and tangential cutting force components at low frequency provided most of the information for the monitoring of surface finish. The E-WPT and SE-WPT packet reduction criteria substantially reduced signal processing time, but at the expense of discarding packets with relevant information, which impoverished the results. The G-WPT method was observed to be an ideal procedure for processing cutting force signals applied to the real-time monitoring of surface finish, and was estimated to be highly accurate and reliable at a low analytical-computational cost.

  4. Recognizing hand movements from a single SEMG sensor using guided under-determined source signal separation.

    Science.gov (United States)

    Rivera, L A; DeSouza, G N

    2011-01-01

    Rehabilitation devices, prosthesis and human machine interfaces are among many applications for which surface electromyographic signals (sEMG) can be employed. Systems reliant on these muscle-generated electrical signals require various forms of machine learning algorithms for specific signature recognition. Those systems vary in terms of the signal detection methods, the feature selection and the classification algorithm used. However, in all those cases, the use of multiple sensors is a constant. In this paper, we present a new technique for source signal separation that relies on a single sEMG sensor. This proposed technique was employed in a classification framework for hand movements that achieved comparable results to other approaches in the literature, but yet, it relied on a much simpler classifier and used a very small number of features. © 2011 IEEE

  5. Extracting nanosecond pulse signals via stochastic resonance generated by surface plasmon bistability.

    Science.gov (United States)

    Han, Jing; Liu, Hongjun; Sun, Qibing; Huang, Nan; Wang, Zhaolu; Li, Shaopeng

    2015-11-15

    A technology is investigated to extract nanosecond pulse noise hidden signals via stochastic resonance, which is based on surface plasmon bistability. A theoretical model for recovering nanosecond pulse signals is derived to describe the nonlinear process. It is found that the incident angle, polarization state, medium properties, and input noise intensity all determine the efficiency and fidelity of the output signal. The bistable behavior of the output intensity can be accurately controlled to obtain a cross-correlation gain larger than 6 in a wide range of input signal-to-noise ratio from 1∶5 to 1∶30. Meanwhile, the distortion in the time domain induced by phase shift can be reduced to a negligible level. This work provides a potential method for detecting low-level or hidden pulse signals in various communication fields.

  6. A comparison of EMG feedback and alternative anxiety treatment programs.

    Science.gov (United States)

    Hiebert, B A; Fitzsimmons, G

    1981-12-01

    Four cohorts of 40 subjects each were randomly assigned to 1 of 10 treatment conditions utilizing EMG feedback, cognitive monitoring training, systematic desensitization, high expectancy discussion group, or waiting list controls either in isolation or in various combinations. A three-way ANOVA for repeated measures indicated that significant anxiety reductions were experienced in all noncontrol treatment conditions. Treatment groups employing EMG feedback demonstrated significantly greater anxiety decrements on Cattell's IPAT Self-Analysis Form, and baseline frontalis EMG. Adding desensitization or cognitive monitoring to EMG feedback did not produce a more powerful effect than using EMG feedback alone. Sex and age differences were also observed. Some implications are discussed.

  7. Agreement between clinical and portable EMG/ECG diagnosis of sleep bruxism.

    Science.gov (United States)

    Castroflorio, T; Bargellini, A; Rossini, G; Cugliari, G; Deregibus, A; Manfredini, D

    2015-10-01

    The aim of this study was to compare clinical sleep bruxism (SB) diagnosis with an instrumental diagnosis obtained with a device providing electromyography/electrocardiography (EMG/ECG) recordings. Forty-five (N = 45) subjects (19 males and 26 females, mean age 28 ± 11 years) were selected among patients referring to the Gnathology Unit of the Dental School of the University of Torino. An expert clinician assessed the presence of SB based on the presence of one or more signs/symptoms (i.e., transient jaw muscle pain in the morning, muscle fatigue at awakening, presence of tooth wear, masseter hypertrophy). Furthermore, all participants underwent an instrumental recording at home with a portable device (Bruxoff; OT Bioelettronica, Torino, Italy) allowing a simultaneous recording of EMG signals from both the masseter muscles as well as heart frequency. Statistical procedures were performed with the software Statistical Package for the Social Science v. 20.0 (SPSS 20.0; IBM, Milan, Italy). Based on the EMG/ECG analysis, 26 subjects (11 males, 15 females, mean age 28 ± 10 years) were diagnosed as sleep bruxers, whilst 19 subjects (7 males, 12 females, mean age 30 ± 10 years) were diagnosed as non-bruxers. The correlation between the clinical and EMG/ECG SB diagnoses was low (ϕ value = 0.250), with a 62.2% agreement (28/45 subjects) between the two approaches (kappa = 0.248). Assuming instrumental EMG/ECG diagnosis as the standard of reference for definite SB diagnosis in this investigation, the false-positive and false-negative rates were unacceptable for all clinical signs/symptoms. In conclusion, findings from clinical assessment are not related with SB diagnosis performed with a portable EMG/ECG recorder. © 2015 John Wiley & Sons Ltd.

  8. Autogenic EMG-Controlled Functional Electrical Stimulation for Ankle Dorsiflexion Control

    Science.gov (United States)

    Yeom, Hojun; Chang, Young-Hui

    2010-01-01

    Our objectives were to develop and test a new system for the potential for stable, real-time cancellation of residual stimulation artefacts (RSA) using surface electrode autogenic electromyography-controlled functional electrical stimulator (aEMGcFES). This type of closed-loop FES could be used to provide more natural, continuous control of lower extremity paretic muscles. We built upon work that has been done in the field of FES with one major technological innovation, an adaptive Gram-Schmidt filtering algorithm, which allowed us to digitally cancel RSA in real-time. This filtering algorithm resulted in a stable real-time estimation of the volitional intent of the stimulated muscle, which then acted as the direct signal for continuously controlling homonymous muscle stimulation. As a first step toward clinical application, we tested the viability of our aEMGcFES system to continuously control ankle dorsiflexion in a healthy subject. Our results indicate positively that an aEMGcFES device with adaptive filtering can respond proportionally to voluntary EMG and activate forceful movements to assist dorsiflexion during controlled isometric activation at the ankle. We also verified that normal ankle joint range of movement could be maintained while using the aEMGcFES system. We suggest that real-time cancellation of both primary and RSA is possible with surface electrode aEMGcFES in healthy subjects and shows promising potential for future clinical application to gait pathologies such as drop foot related to hemiparetic stroke. PMID:20713086

  9. 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.

  10. A MATLAB-based graphical user interface for the identification of muscular activations from surface electromyography signals.

    Science.gov (United States)

    Mengarelli, Alessandro; Cardarelli, Stefano; Verdini, Federica; Burattini, Laura; Fioretti, Sandro; Di Nardo, Francesco

    2016-08-01

    In this paper a graphical user interface (GUI) built in MATLAB® environment is presented. This interactive tool has been developed for the analysis of superficial electromyography (sEMG) signals and in particular for the assessment of the muscle activation time intervals. After the signal import, the tool performs a first analysis in a totally user independent way, providing a reliable computation of the muscular activation sequences. Furthermore, the user has the opportunity to modify each parameter of the on/off identification algorithm implemented in the presented tool. The presence of an user-friendly GUI allows the immediate evaluation of the effects that the modification of every single parameter has on the activation intervals recognition, through the real-time updating and visualization of the muscular activation/deactivation sequences. The possibility to accept the initial signal analysis or to modify the on/off identification with respect to each considered signal, with a real-time visual feedback, makes this GUI-based tool a valuable instrument in clinical, research applications and also in an educational perspective.

  11. EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model

    Science.gov (United States)

    2014-01-01

    Background This paper describes the “EMG Driven Force Estimator (EMGD-FE)”, a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. Results An example of the application’s functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. Conclusions The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues. PMID:24708668

  12. EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model.

    Science.gov (United States)

    Menegaldo, Luciano Luporini; de Oliveira, Liliam Fernandes; Minato, Kin K

    2014-04-04

    This paper describes the "EMG Driven Force Estimator (EMGD-FE)", a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. An example of the application's functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues.

  13. The relationship of extraneous movements to lumbar paraspinal muscle activity: implications for EMG biofeedback training applications to low back pain patients.

    Science.gov (United States)

    Wolf, S L; Wolf, L B; Segal, R L

    1989-03-01

    Within recent years clinicians and researchers have applied paraspinal EMG biofeedback procedures during static and dynamic movement retraining of chronic low back pain patients. Most of these applications make use of surface electromyography, an approach complicated by the fact that the erector spinae muscles are deeply situated. This descriptive study reveals that extraneous movements, such as neck flexion and pelvic rotation, can elicit profound activity from percutaneously placed EMG electrodes while little change is seen at the skin surface. The implications of these observations for the use of EMG feedback to remediate low back pain are discussed.

  14. The pattern of anthropogenic signal emergence in Greenland Ice Sheet surface mass balance

    NARCIS (Netherlands)

    Fyke, J.G.; Vizcaino, M.; Lipscomb, W.H.

    2014-01-01

    Surface mass balance (SMB) trends influence observed Greenland Ice Sheet (GrIS) mass loss, but the component of these trends related to anthropogenic forcing is unclear. Here we study the simulated spatial pattern of emergence of an anthropogenically derived GrIS SMB signal between 1850 and 2100

  15. GPS Signal Scattering from Sea Surface: Wind Speed Retrieval Using Experimental Data and Theoretical Model

    Science.gov (United States)

    Komjathy, Attila; Zavorotny, Valery U.; Axelrad, Penina; Born, George H.; Garrison, James L.

    2000-01-01

    Global Positioning System (GPS) signals reflected from the ocean surface have potential use for various remote sensing purposes. Some possibilities arc measurements of surface roughness characteristics from which ware height, wind speed, and direction could be determined. For this paper, GPS-reflected signal measurements collected at aircraft altitudes of 2 km to 5 km with a delay-Doppler mapping GPS receiver arc used to explore the possibility of determining wind speed. To interpret the GPS data, a theoretical model has been developed that describes the power of the reflected GPS signals for different time delays and Doppler frequencies as a function of geometrical and environmental parameters. The results indicate a good agreement between the measured and the modeled normalized signal power waveforms during changing surface wind conditions. The estimated wind speed using surface- reflected GPS data, obtained by comparing actual and modeled waveforms, shows good agreement (within 2 m/s) with data obtained from a nearby buoy and independent wind speed measurements derived from the TOPEX/Poseidon altimetric satellite.

  16. Azimuthal asymmetry in the risetime of the surface detector signals of the Pierre Auger Observatory

    NARCIS (Netherlands)

    Aab, A.; Abreu, P.; Aglietta, M.; Ahn, E. J.; Al Samarai, I.; Albuquerque, I. F. M.; Allekotte, I.; Messina, S.; Scholten, O.; van den Berg, A.M.

    2016-01-01

    The azimuthal asymmetry in the risetime of signals in Auger surface detector stations is a source of information on shower development. The azimuthal asymmetry is due to a combination of the longitudinal evolution of the shower and geometrical effects related to the angles of incidence of the

  17. Radar signal pre-processing to suppress surface bounce and multipath

    Science.gov (United States)

    Paglieroni, David W; Mast, Jeffrey E; Beer, N. Reginald

    2013-12-31

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes that return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

  18. Proof of Concept of an Online EMG-Based Decoding of Hand Postures and Individual Digit Forces for Prosthetic Hand Control.

    Science.gov (United States)

    Gailey, Alycia; Artemiadis, Panagiotis; Santello, Marco

    2017-01-01

    Options currently available to individuals with upper limb loss range from prosthetic hands that can perform many movements, but require more cognitive effort to control, to simpler terminal devices with limited functional abilities. We attempted to address this issue by designing a myoelectric control system to modulate prosthetic hand posture and digit force distribution. We recorded surface electromyographic (EMG) signals from five forearm muscles in eight able-bodied subjects while they modulated hand posture and the flexion force distribution of individual fingers. We used a support vector machine (SVM) and a random forest regression (RFR) to map EMG signal features to hand posture and individual digit forces, respectively. After training, subjects performed grasping tasks and hand gestures while a computer program computed and displayed online feedback of all digit forces, in which digits were flexed, and the magnitude of contact forces. We also used a commercially available prosthetic hand, the i-Limb (Touch Bionics), to provide a practical demonstration of the proposed approach's ability to control hand posture and finger forces. Subjects could control hand pose and force distribution across the fingers during online testing. Decoding success rates ranged from 60% (index finger pointing) to 83-99% for 2-digit grasp and resting state, respectively. Subjects could also modulate finger force distribution. This work provides a proof of concept for the application of SVM and RFR for online control of hand posture and finger force distribution, respectively. Our approach has potential applications for enabling in-hand manipulation with a prosthetic hand.

  19. 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.

  20. Secondary ion mass spectrometric signal enhancement of phosphatidylcholine dioleoyl on enlarged nanoparticles surface

    Science.gov (United States)

    Gulin, A.; Mochalova, M.; Denisov, N.; Nadtochenko, V.

    2014-10-01

    A silicon wafer surface coverage of nanoparticles (NPs) can enhance the L-α-phosphatidylcholine dioleoyl (DOPC) signal intensity in time-of-flight secondary ion mass spectrometry (TOF-SIMS). A ToF-SIMS mass spectrometer was used with a pulsed primary beam of focused 30 keV Bi3+ ions. The signal enhancing effect has been studied for metallic (Ag, Au, Pb), semiconductor (TiO2), dielectric (SiO2) and hybrid (Au/TiO2NPs, core-shell Au/SiO2) nanoparticles. Ag NPs can attenuate secondary ions signal, whereas all other studied NPs show the signal enhancement. The emission of DOPC lipid secondary ions immobilized on core-shell Au/SiO2NPs was enhanced up to 42 times. This technique is a simple preparatory method enabling an overall increase in molecular lipid ions.

  1. Real-time simultaneous and proportional myoelectric control using intramuscular EMG

    Science.gov (United States)

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

    2014-12-01

    Objective. Myoelectric prostheses use electromyographic (EMG) signals to control movement of prosthetic joints. Clinically available myoelectric control strategies do not allow simultaneous movement of multiple degrees of freedom (DOFs); however, the use of implantable devices that record intramuscular EMG signals could overcome this constraint. The objective of this study was to evaluate the real-time simultaneous control of three DOFs (wrist rotation, wrist flexion/extension, and hand open/close) using intramuscular EMG. Approach. We evaluated task performance of five able-bodied subjects in a virtual environment using two control strategies with fine-wire EMG: (i) parallel dual-site differential control, which enabled simultaneous control of three DOFs and (ii) pattern recognition control, which required sequential control of DOFs. Main results. Over the course of the experiment, subjects using parallel dual-site control demonstrated increased use of simultaneous control and improved performance in a Fitts’ Law test. By the end of the experiment, performance using parallel dual-site control was significantly better (up to a 25% increase in throughput) than when using sequential pattern recognition control for tasks requiring multiple DOFs. The learning trends with parallel dual-site control suggested that further improvements in performance metrics were possible. Subjects occasionally experienced difficulty in performing isolated single-DOF movements with parallel dual-site control but were able to accomplish related Fitts’ Law tasks with high levels of path efficiency. Significance. These results suggest that intramuscular EMG, used in a parallel dual-site configuration, can provide simultaneous control of a multi-DOF prosthetic wrist and hand and may outperform current methods that enforce sequential control.

  2. Gender differences in time-frequency EMG analysis of unanticipated cutting maneuvers.

    Science.gov (United States)

    Beaulieu, Mélanie L; Lamontagne, Mario; Xu, Lanyi

    2008-10-01

    The purpose of this study is to compare the time-frequency characteristic, using nonlinearly scaled wavelets, of the EMG signal as well as the three-dimensional (3D) knee kinematics of female and male elite soccer players performing an unanticipated cutting maneuver. Fifteen female and 15 male elite soccer players performed several cutting maneuvers during which EMG of eight muscles of the leg and 3D kinematics of the knee were recorded. To create an unanticipated condition, the participants executed one of three tasks, which were signaled to them with an illuminated target board. Male participants generally executed the unanticipated cutting maneuver with a quadriceps activation of higher frequency components. These gender differences were also found at initial ground contact (IC) for the vastii and biceps femoris (BF) muscles. These higher frequencies dominated the signal earlier in time for the BF and later for the tibialis anterior (TA) in women. Furthermore, women performed the cutting task with greater knee abduction than did the men. Female athletes adopted a different motor unit recruitment strategy that was particularly evident at, and near, IC resulting in lower frequency components in the EMG signal of the lateral hamstring. This strategy may play a role in explaining the gender bias in anterior cruciate ligament (ACL) injury rates. Gender differences in knee kinematics were also observed, exposing the female ACL to higher strain, which may be the result of differences in neuromuscular strategies to stabilize the knee joint.

  3. 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

  4. 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 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.

  5. RssAB signaling coordinates early development of surface multicellularity in Serratia marcescens.

    Directory of Open Access Journals (Sweden)

    Yu-Huan Tsai

    Full Text Available Bacteria can coordinate several multicellular behaviors in response to environmental changes. Among these, swarming and biofilm formation have attracted significant attention for their correlation with bacterial pathogenicity. However, little is known about when and where the signaling occurs to trigger either swarming or biofilm formation. We have previously identified an RssAB two-component system involved in the regulation of swarming motility and biofilm formation in Serratia marcescens. Here we monitored the RssAB signaling status within single cells by tracing the location of the translational fusion protein EGFP-RssB following development of swarming or biofilm formation. RssAB signaling is specifically activated before surface migration in swarming development and during the early stage of biofilm formation. The activation results in the release of RssB from its cognate inner membrane sensor kinase, RssA, to the cytoplasm where the downstream gene promoters are located. Such dynamic localization of RssB requires phosphorylation of this regulator. By revealing the temporal activation of RssAB signaling following development of surface multicellular behavior, our findings contribute to an improved understanding of how bacteria coordinate their lifestyle on a surface.

  6. 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.

  7. Secondary ion mass spectrometric signal enhancement of phosphatidylcholine dioleoyl on enlarged nanoparticles surface

    Energy Technology Data Exchange (ETDEWEB)

    Gulin, A. [N.N. Semenov Institute of Chemical Physics, RAS, Kosigin str. 4, Moscow 119991 (Russian Federation); Mochalova, M. [Moscow Institute of Physics and Technology, Institutskii per. 9, Dolgoprudny, Moscow 141700 (Russian Federation); Denisov, N. [Institute of Problem of Chemical Physics, RAS, Semenov av. 1, Chernogolovka, 142432 (Russian Federation); Nadtochenko, V., E-mail: nadtochenko@gmail.com [N.N. Semenov Institute of Chemical Physics, RAS, Kosigin str. 4, Moscow 119991 (Russian Federation); Moscow Institute of Physics and Technology, Institutskii per. 9, Dolgoprudny, Moscow 141700 (Russian Federation); Institute of Problem of Chemical Physics, RAS, Semenov av. 1, Chernogolovka, 142432 (Russian Federation)

    2014-10-15

    Graphical abstract: - Highlights: • TOF-SIMS mass-spectra of DOPC lipid on enlarged nanoparticles surface were studied. • Metallic, semiconductor, dielectric and hybrid nanoparticles were examined. • Effect of nanoparticles on mass-spectral peaks intensity was investigated. • The highest signal enhancement of 42 times was found for hybrid core–shell Au/SiO{sub 2} nanoparticles. - Abstract: A silicon wafer surface coverage of nanoparticles (NPs) can enhance the L-α-phosphatidylcholine dioleoyl (DOPC) signal intensity in time-of-flight secondary ion mass spectrometry (TOF-SIMS). A ToF-SIMS mass spectrometer was used with a pulsed primary beam of focused 30 keV Bi{sub 3}{sup +} ions. The signal enhancing effect has been studied for metallic (Ag, Au, Pb), semiconductor (TiO{sub 2}), dielectric (SiO{sub 2}) and hybrid (Au/TiO{sub 2}NPs, core–shell Au/SiO{sub 2}) nanoparticles. Ag NPs can attenuate secondary ions signal, whereas all other studied NPs show the signal enhancement. The emission of DOPC lipid secondary ions immobilized on core–shell Au/SiO{sub 2}NPs was enhanced up to 42 times. This technique is a simple preparatory method enabling an overall increase in molecular lipid ions.

  8. Delineating PAS-HAMP interaction surfaces and signalling-associated changes in the aerotaxis receptor Aer.

    Science.gov (United States)

    Garcia, Darysbel; Watts, Kylie J; Johnson, Mark S; Taylor, Barry L

    2016-04-01

    The Escherichia coli aerotaxis receptor, Aer, monitors cellular oxygen and redox potential via FAD bound to a cytosolic PAS domain. Here, we show that Aer-PAS controls aerotaxis through direct, lateral interactions with a HAMP domain. This contrasts with most chemoreceptors where signals propagate along the protein backbone from an N-terminal sensor to HAMP. We mapped the interaction surfaces of the Aer PAS, HAMP and proximal signalling domains in the kinase-off state by probing the solvent accessibility of 129 cysteine substitutions. Inaccessible PAS-HAMP surfaces overlapped with a cluster of PAS kinase-on lesions and with cysteine substitutions that crosslinked the PAS β-scaffold to the HAMP AS-2 helix. A refined Aer PAS-HAMP interaction model is presented. Compared to the kinase-off state, the kinase-on state increased the accessibility of HAMP residues (apparently relaxing PAS-HAMP interactions), but decreased the accessibility of proximal signalling domain residues. These data are consistent with an alternating static-dynamic model in which oxidized Aer-PAS interacts directly with HAMP AS-2, enforcing a static HAMP domain that in turn promotes a dynamic proximal signalling domain, resulting in a kinase-off output. When PAS-FAD is reduced, PAS interaction with HAMP is relaxed and a dynamic HAMP and static proximal signalling domain convey a kinase-on output. © 2015 John Wiley & Sons Ltd.

  9. Real-time fusion of gaze and EMG for a reaching neuroprosthesis.

    Science.gov (United States)

    Corbett, Elaine A; Kording, Konrad P; Perreault, Eric J

    2012-01-01

    For rehabilitative devices to restore functional movement to paralyzed individuals, user intent must be determined from signals that remain under voluntary control. Tracking eye movements is a natural way to learn about an intended reach target and, when combined with just a small set of electromyograms (EMGs) in a probabilistic mixture model, can reliably generate accurate trajectories even when the target information is uncertain. To experimentally assess the effectiveness of our algorithm in closed-loop control, we developed a robotic system to simulate a reaching neuroprosthetic. Incorporating target information by tracking subjects' gaze greatly improved performance when the set of EMGs was most limited. In addition we found that online performance was better than predicted by the offline accuracy of the training data. By enhancing the trajectory model with target information the decoder relied less on neural control signals, reducing the burden on the user.

  10. Identification of Spurious Signals from Permeable Ffowcs Williams and Hawkings Surfaces

    Science.gov (United States)

    Lopes, Leonard V.; Boyd, David D., Jr.; Nark, Douglas M.; Wiedemann, Karl E.

    2017-01-01

    Integral forms of the permeable surface formulation of the Ffowcs Williams and Hawkings (FW-H) equation often require an input in the form of a near field Computational Fluid Dynamics (CFD) solution to predict noise in the near or far field from various types of geometries. The FW-H equation involves three source terms; two surface terms (monopole and dipole) and a volume term (quadrupole). Many solutions to the FW-H equation, such as several of Farassat's formulations, neglect the quadrupole term. Neglecting the quadrupole term in permeable surface formulations leads to inaccuracies called spurious signals. This paper explores the concept of spurious signals, explains how they are generated by specifying the acoustic and hydrodynamic surface properties individually, and provides methods to determine their presence, regardless of whether a correction algorithm is employed. A potential approach based on the equivalent sources method (ESM) and the sensitivity of Formulation 1A (Formulation S1A) is also discussed for the removal of spurious signals.

  11. Estudi de la señal de EMG pel tratactament de la incontinència urinària

    OpenAIRE

    Benasques Borau, Laura

    2016-01-01

    This project is focused on the analysis of the Electromyographic signal (EMG) of the pelvic floor muscles during the realization of physical exercises oriented to increase the strength of the muscles. These exercises are oriented to reduce urinary incontinence in adult women. Studying records of electromyography (EMG) under conditions similar to a randomized clinical trial. With the records obtained, it is expected to study where is the best location of the electrodes in the abdomen to det...

  12. Thinking Outside the Button Box: EMG as a Computer Input Device for Psychological Research

    OpenAIRE

    Crawford, L. Elizabeth; Vavra, Dylan T.; Corbin, Jonathan C.

    2017-01-01

    Experimental psychology research commonly has participants respond to stimuli by pressing buttons or keys. Standard computer input devices constrain the range of motoric responses participants can make, even as the field advances theory about the importance of the motor system in cognitive and social information processing. Here we describe an inexpensive way to use an electromyographic (EMG) signal as a computer input device, enabling participants to control a computer by contracting muscles...

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

    Science.gov (United States)

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

    2015-12-01

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

  14. A Combined sEMG and Accelerometer System for Monitoring Functional Activity in Stroke

    Science.gov (United States)

    Roy, Serge H.; Cheng, M. Samuel; Chang, Shey-Sheen; Moore, John; De Luca, Gianluca; Nawab, S. Hamid; De Luca, Carlo J.

    2010-01-01

    Remote monitoring of physical activity using body-worn sensors provides an alternative to assessment of functional independence by subjective, paper-based questionnaires. This study investigated the classification accuracy of a combined surface electromyographic (sEMG) and accelerometer (ACC) sensor system for monitoring activities of daily living in patients with stroke. sEMG and ACC data (eight channels each) were recorded from 10 hemiparetic patients while they carried out a sequence of 11 activities of daily living (identification tasks), and 10 activities used to evaluate misclassification errors (nonidentification tasks). The sEMG and ACC sensor data were analyzed using a multilayered neural network and an adaptive neuro-fuzzy inference system to identify the minimal sensor configuration needed to accurately classify the identification tasks, with a minimal number of misclassifications from the nonidentification tasks. The results demonstrated that the highest sensitivity and specificity for the identification tasks was achieved using a subset of four ACC sensors and adjacent sEMG sensors located on both upper arms, one forearm, and one thigh, respectively. This configuration resulted in a mean sensitivity of 95.0%, and a mean specificity of 99.7% for the identification tasks, and a mean misclassification error of system for automatic recognition of motor tasks used to assess functional independence in patients with stroke. PMID:20051332

  15. Force production and EMG activity of neck muscles in adolescent headache.

    Science.gov (United States)

    Oksanen, Airi; Pöyhönen, Tapani; Ylinen, Jari J; Metsähonkala, Liisa; Anttila, Pirjo; Laimi, Katri; Hiekkanen, Heikki; Aromaa, Minna; Salminen, Jouko J; Sillanpää, Matti

    2008-01-01

    This study compared the maximal force, EMG/force ratio and co-activation characteristics of the neck-shoulder muscles between 30 adolescents with migraine-type headache, 29 with tension-type headache, and 30 headache-free controls. Force was measured with surface electromyography (EMG) from the cervical erector spinae (CES), the sternocleidomastoid (SCM) and trapezius muscles during the maximal isometric neck flexion, neck extension and shoulder flexion. Girls with migraine-type headache had higher EMG/force ratios between the EMG of the left agonist SCM muscle and the corresponding maximal neck flexion (p = 0.030) and neck rotation force to the right side (p = 0.024) than the girls with tension-type headache. Migrainous girls had more co-activation of right antagonist CES muscle during maximal neck flexion force than the girls without headache (p = 0.015). Neck force production showed no significant differences between girls. Girls with tension-type headache displayed lower left shoulder flexion force than girls with migraine-type headache (p = 0.005) or with no headache (p = 0.005). In boys, no significant differences were observed. Girls with tension-type headache and migraine-type headache have differences in neuromuscular function in the neck-shoulder muscles. The data amplify our knowledge of the neck-shoulder muscle dysfunction in adolescent headache, and may encourage the use of specific rehabilitation methods in the management of different types of headache.

  16. 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.

  17. 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.

  18. 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.

  19. Broadband polarimetry of exoplanets: modelling signals of surfaces, hazes and clouds

    OpenAIRE

    Karalidi, Theodora

    2013-01-01

    It is less than 20 years since astronomers discovered the first exoplanet orbiting a Sun-like star. In this short period more than 770 confirmed exoplanets have been detected. With so many exoplanets the next step is their characterization. What is their atmosphere made of? Does it contain water clouds? Is there water on the planetary surface? Could there be life on these planets? To answer all these questions good and reliable models are necessary for interpreting the signal we observe from ...

  20. A quantitative analysis of signal reproduction from cylinder recordings measured via noncontact full surface mapping.

    Science.gov (United States)

    Nascè, Antony; Hill, Martyn; McBride, John W; Boltryk, Peter J

    2008-10-01

    Sound reproduction via a noncontact surface mapping technique has great potential for sound archives, aiming to digitize content from early sound recordings such as wax cylinders, which may otherwise be "unplayable" with a stylus. If the noncontact techniques are to be considered a viable solution for sound archivists, a method for quantifying the quality of the reproduced signal needs to be developed. In this study, a specially produced test cylinder recording, encoded with sinusoids, provides the basis for the first quantitative analysis of signal reproduction from the noncontact full surface mapping method. The sampling and resolution of the measurement system are considered with respect to the requirements for digital archiving of cylinder recordings. Two different methods of audio signal estimation from a discrete groove cross section are described and rated in terms of signal-to-noise ratio and total harmonic distortion. Noncontact and stylus methods of sound reproduction are then compared using the same test cylinder. It is shown that noncontact methods appear to have distinct advantages over stylus reproduction, in terms of reduced harmonic distortion and lower frequency modulation.

  1. Confocal signal evaluation algorithms for surface metrology: uncertainty and numerical efficiency.

    Science.gov (United States)

    Rahlves, Maik; Roth, Bernhard; Reithmeier, Eduard

    2017-07-20

    Confocal microscopy is one of the dominating measurement techniques in surface metrology, with an enhanced lateral resolution compared to alternative optical methods. However, the axial resolution in confocal microscopy is strongly dependent on the accuracy of signal evaluation algorithms, which are limited by random noise. Here, we discuss the influence of various noise sources on confocal intensity signal evaluating algorithms, including center-of-mass, parabolic least-square fit, and cross-correlation-based methods. We derive results in closed form for the uncertainty in height evaluation on surface microstructures, also accounting for the number of axially measured intensity values and a threshold that is commonly applied before signal evaluation. The validity of our results is verified by numerical Monte Carlo simulations. In addition, we implemented all three algorithms and analyzed their numerical efficiency. Our results can serve as guidance for a suitable choice of measurement parameters in confocal surface topography measurement, and thus lead to a shorter measurement time in practical applications.

  2. Nanometer Scale Titanium Surface Texturing Are Detected by Signaling Pathways Involving Transient FAK and Src Activations

    Science.gov (United States)

    Zambuzzi, Willian F.; Bonfante, Estevam A.; Jimbo, Ryo; Hayashi, Mariko; Andersson, Martin; Alves, Gutemberg; Takamori, Esther R.; Beltrão, Paulo J.; Coelho, Paulo G.; Granjeiro, José M.

    2014-01-01

    Background It is known that physico/chemical alterations on biomaterial surfaces have the capability to modulate cellular behavior, affecting early tissue repair. Such surface modifications are aimed to improve early healing response and, clinically, offer the possibility to shorten the time from implant placement to functional loading. Since FAK and Src are intracellular proteins able to predict the quality of osteoblast adhesion, this study evaluated the osteoblast behavior in response to nanometer scale titanium surface texturing by monitoring FAK and Src phosphorylations. Methodology Four engineered titanium surfaces were used for the study: machined (M), dual acid-etched (DAA), resorbable media microblasted and acid-etched (MBAA), and acid-etch microblasted (AAMB). Surfaces were characterized by scanning electron microscopy, interferometry, atomic force microscopy, x-ray photoelectron spectroscopy and energy dispersive X-ray spectroscopy. Thereafter, those 4 samples were used to evaluate their cytotoxicity and interference on FAK and Src phosphorylations. Both Src and FAK were investigated by using specific antibody against specific phosphorylation sites. Principal Findings The results showed that both FAK and Src activations were differently modulated as a function of titanium surfaces physico/chemical configuration and protein adsorption. Conclusions It can be suggested that signaling pathways involving both FAK and Src could provide biomarkers to predict osteoblast adhesion onto different surfaces. PMID:24999733

  3. Non-Linear Signal Analysis Applied to Surface Wear Condition Monitoring in Reciprocating Sliding Testing Machines

    Directory of Open Access Journals (Sweden)

    Francisco Paulo Lépore Neto

    2006-01-01

    Full Text Available When the surfaces of two elastic bodies present relative motions under certain amount of contact pressure the mechanical system can be unstable. Experiments conducted on elastic bodies in contact shown that the dynamic system is self-excited by the non-linear behavior of the friction forces. The main objective of this paper is to estimate the friction force using the vibrations signals, measured on a reciprocating wear testing machine, by the proposed non-linear signal analysis formulation. In the proposed formulation the system global output is the sum of two outputs produced by a linear path associated in parallel with a non-linear path. This last path is a non-linear model that represents the friction force. Since the linear path can be identified by traditional signal analysis, the non-linear function can be evaluated by the global input/output relationships. Validation tests are conducted in a tribological system composed by a sphere in contact with and a prismatic body, which has an imposed harmonic motion. The global output force is simultaneously measured by a piezoelectric and by a piezoresistive load cells. The sphere and prismatic body vibrations are measured by a laser Doppler vibrometer and by an accelerometer respectively. All signals are digitalized at the same time base and the data is transferred to a microcomputer. The non-linear signal analysis technique uses this data to identify the friction force.

  4. Onset Detection in Surface Electromyographic Signals: A Systematic Comparison of Methods

    Directory of Open Access Journals (Sweden)

    Claus Flachenecker

    2001-06-01

    Full Text Available Various methods to determine the onset of the electromyographic activity which occurs in response to a stimulus have been discussed in the literature over the last decade. Due to the stochastic characteristic of the surface electromyogram (SEMG, onset detection is a challenging task, especially in weak SEMG responses. The performance of the onset detection methods were tested, mostly by comparing their automated onset estimations to the manually determined onsets found by well-trained SEMG examiners. But a systematic comparison between methods, which reveals the benefits and the drawbacks of each method compared to the other ones and shows the specific dependence of the detection accuracy on signal parameters, is still lacking. In this paper, several classical threshold-based approaches as well as some statistically optimized algorithms were tested on large samples of simulated SEMG data with well-known signal parameters. Rating between methods is performed by comparing their performance to that of a statistically optimal maximum likelihood estimator which serves as reference method. In addition, performance was evaluated on real SEMG data obtained in a reaction time experiment. Results indicate that detection behavior strongly depends on SEMG parameters, such as onset rise time, signal-to-noise ratio or background activity level. It is shown that some of the threshold-based signal-power-estimation procedures are very sensitive to signal parameters, whereas statistically optimized algorithms are generally more robust.

  5. How can we understand the global distribution of the solar cycle signal on the Earth's surface?

    Directory of Open Access Journals (Sweden)

    K. Kodera

    2016-10-01

    Full Text Available To understand solar cycle signals on the Earth's surface and identify the physical mechanisms responsible, surface temperature variations from observations as well as climate model data are analysed to characterize their spatial structure. The solar signal in the annual mean surface temperature is characterized by (i mid-latitude warming and (ii no overall tropical warming. The mid-latitude warming during solar maxima in both hemispheres is associated with a downward penetration of zonal mean zonal wind anomalies from the upper stratosphere during late winter. During the Northern Hemisphere winter this is manifested by a modulation of the polar-night jet, whereas in the Southern Hemisphere, the upper stratospheric subtropical jet plays the major role. Warming signals are particularly apparent over the Eurasian continent and ocean frontal zones, including a previously reported lagged response over the North Atlantic. In the tropics, local warming occurs over the Indian and central Pacific oceans during high solar activity. However, this warming is counterbalanced by cooling over the cold tongue sectors in the southeastern Pacific and the South Atlantic, and results in a very weak zonally averaged tropical mean signal. The cooling in the ocean basins is associated with stronger cross-equatorial winds resulting from a northward shift of the ascending branch of the Hadley circulation during solar maxima. To understand the complex processes involved in the solar signal transfer, results of an idealized middle atmosphere–ocean coupled model experiment on the impact of stratospheric zonal wind changes are compared with solar signals in observations. Model integration of 100 years of strong or weak stratospheric westerly jet condition in winter may exaggerate long-term ocean feedback. However, the role of ocean in the solar influence on the Earth's surface can be better seen. Although the momentum forcing differs from that of solar radiative forcing

  6. Frenulectomy of the tongue and the influence of rehabilitation exercises on the sEMG activity of masticatory muscles.

    Science.gov (United States)

    Tecco, Simona; Baldini, Aberto; Mummolo, Stefano; Marchetti, Enrico; Giuca, Maria Rita; Marzo, Giuseppe; Gherlone, Enrico Felice

    2015-08-01

    This study aimed to assess by surface electromyography (sEMG) the changes in sub-mental, orbicularis oris, and masticatory muscle activity after a lingual frenulectomy. Rehabilitation exercises in subjects with ankyloglossia, characterized by Class I malocclusion, were assessed as well. A total of 24 subjects were selected. Thirteen subjects (mean age 7±2.5years) with Class I malocclusion and ankyloglossia were treated with lingual frenulectomy and rehabilitation exercises, while 11 subjects (mean age 7±0.8years) with normal occlusion and normal lingual frenulum were used as controls. The inclusion criteria for both groups were the presence of mixed dentition and no previous orthodontic treatment. The sEMG recordings were taken at the time of the first visit (T0), and after 1 (T1) and 6months (T2) for the treated group. Recordings were taken at the same time for the control group. Due to the noise inherent with the sEMG recording, special attention was paid to obtain reproducible and standardized recordings. The tested muscles were the masseter, anterior temporalis, upper and lower orbicularis oris, and sub-mental muscles. The sEMG recordings were performed at rest, while kissing, swallowing, opening the mouth, clenching the teeth and during protrusion of the mandible. These recordings were made by placing electrodes in the area of muscle contraction. At T0, the treated group showed different sEMG activity of the muscles with respect to the control group, with significant differences at rest and during some test tasks (pmuscle, from T0 to T2, during maximal voluntary clenching. During swallowing and kissing, the masseter and sub-mental muscles showed a significant increase in their sEMG potentials from T0 to T2. During the protrusion of the mandible, the masseter and anterior temporalis significantly decreased their sEMG activity, while the sub-mental area increased significantly. No significant change was observed in the control group during the follow-up. The sEMG

  7. Heart rate variability (HRV and muscular system activity (EMG in cases of crash threat during simulated driving of a passenger car

    Directory of Open Access Journals (Sweden)

    Krystyna Zużewicz

    2013-10-01

    Full Text Available Objectives: The aim of the study was to verify whether simultaneous responses from the muscular and circulatory system occur in the driver's body under simulated conditions of a crash threat. Materials and Methods: The study was carried out in a passenger car driving simulator. The crash was included in the driving test scenario developed in an urban setting. In the group of 22 young male subjects, two physiological signals - ECG and EMG were continuously recorded. The length of the RR interval in the ECG signal was assessed. A HRV analysis was performed in the time and frequency domains for 1-minute record segments at rest (seated position, during undisturbed driving as well as during and several minutes after the crash. For the left and right side muscles: m. trapezius (TR and m. flexor digitorum superficialis (FDS, the EMG signal amplitude was determined. The percentage of maximal voluntary contraction (MVC was compared during driving and during the crash. Results: As for the ECG signal, it was found that in most of the drivers changes occurred in the parameter values reflecting HRV in the time domain. Significant changes were noted in the mean length of RR intervals (mRR. As for the EMG signal, the changes in the amplitude concerned the signal recorded from the FDS muscle. The changes in ECG and EMG were simultaneous in half of the cases. Conclusion: Such parameters as mRR (ECG signal and FDS-L amplitude (EMG signal were the responses to accident risk. Under simulated conditions, responses from the circulatory and musculoskeletal systems are not always simultaneous. The results indicate that a more complete driver's response to a crash in road traffic is obtained based on parallel recording of two physiological signals (ECG and EMG.

  8. Toward EMG-controlled force field generation for training and rehabilitation: From movement data to muscle geometry.

    Science.gov (United States)

    Lotti, Nicola; Sanguinati, Vittorio

    2017-07-01

    EMG signals are often used to control prostheses or assistive devices, but have been rarely used in rehabilitation. We propose a novel approach to personalised rehabilitation, based on EMG-driven force field adaptation. As a step toward this direction, here we show how EMG activity and movement data during a robot-assisted motor task can be used to estimate muscle geometry. We compare three different models of muscle geometry, characterised by (i) constant moment arms (CM); (ii) a normative model, based on polynomial functions of joint angles with fixed coefficients (normative polynomial, NP); and (iii) a person-adaptive model, in which the same polynomial model is fitted to individual subjects data (fitted polynomial, FP). We found that the FP model has the best performance, specially for subjects whose size is farther from 'average'. The fitting results also emphasise the adverse effect of muscles co-contraction.

  9. Oxycodone and Dexamethasone for pain management after tonsillectomy: A placebo-controlled EMG assessed clinical trial

    Science.gov (United States)

    Vaiman, Michael; Krakovski, Daniel; Haitov, Zoe

    2011-01-01

    Summary Background Surface electromyographic (sEMG) study of post-tonsillectomy swallow-evoked muscular reactions was performed in order to evaluate the efficacy and safety of oxycodone and dexamethasone in pain management after tonsillectomy. Material/Methods 90 randomly chosen operated adults were divided into three groups. Group 1 (n=30) was treated with OxyContin (Oxycodone) injections; Group 2 (n=30) was treated with Dexacort (Dexamethasone), and Group 3 (n=30) was a placebo group. Pain assessment included visual analogue scale (VAS) pain score and the EMG data like the timing, electric amplitude and graphic patterns of muscular activity during deglutition. We investigated masseter, infrahyoid and submental-submandibular muscles. Records from trapezius muscle were used for control. The results were compared with previously established normative database. The patients were tested 24 h after surgery. The sEMG data were compared with VAS pain score with regard to changes in clinical condition of the patients. Results Analgesia with oxycodone smoothed the recorded sEMG swallow peaks and increases time of deglutition. Dexamethasone normalized muscular activity in deglutition in cases with edema as detected by the EMG records. Statistically significant difference in muscle reactions was detected between the two Groups and the placebo group. Conclusions Application of oxycodone significantly reduces the postoperative pain. Application of dexamethasone after tonsillectomy is advisable because of the reduction of postoperative morbidity while the reduction of the postoperative pain is secondary to the reduction of edema. SEMG might be used as an adjunctive measure of pain behavior via assessment of muscular reactions to pain and to analgesia. PMID:21959624

  10. Redundancy or heterogeneity in the electric activity of the biceps brachii muscle? Added value of PCA-processed multi-channel EMG muscle activation estimates in a parallel-fibered muscle.

    Science.gov (United States)

    Staudenmann, Didier; Stegeman, Dick F; van Dieën, Jaap H

    2013-08-01

    Conventional bipolar EMG provides imprecise muscle activation estimates due to possibly heterogeneous activity within muscles and due to improper alignment of the electrodes with the muscle fibers. Principal component analysis (PCA), applied on multi-channel monopolar EMG yielded substantial improvements in muscle activation estimates in pennate muscles. We investigated the degree of heterogeneity in muscle activity and the contribution of PCA to muscle activatio