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Sample records for surface emg signal

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

    PubMed

    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. Homomorphic Deconvolution for MUAP Estimation From Surface EMG Signals.

    PubMed

    Biagetti, Giorgio; Crippa, Paolo; Orcioni, Simone; Turchetti, Claudio

    2017-03-01

    This paper presents a technique for parametric model estimation of the motor unit action potential (MUAP) from the surface electromyography (sEMG) signal by using homomorphic deconvolution. The cepstrum-based deconvolution removes the effect of the stochastic impulse train, which originates the sEMG signal, from the power spectrum of sEMG signal itself. In this way, only information on MUAP shape and amplitude were maintained, and then, used to estimate the parameters of a time-domain model of the MUAP itself. In order to validate the effectiveness of this technique, sEMG signals recorded during several biceps curl exercises have been used for MUAP amplitude and time scale estimation. The parameters so extracted as functions of time were used to evaluate muscle fatigue showing a good agreement with previously published results.

  3. Analysis of surface EMG signal morphology in Parkinson's disease.

    PubMed

    Rissanen, Saara; Kankaanpää, Markku; Tarvainen, Mika P; Nuutinen, Juho; Tarkka, Ina M; Airaksinen, Olavi; Karjalainen, Pasi A

    2007-12-01

    A novel approach is presented for the analysis of surface electromyogram (EMG) morphology in Parkinson's disease (PD). The method is based on histogram and crossing rate (CR) analysis of the EMG signal. In the method, histograms and CR values are used as high-dimensional feature vectors. The dimensionality of them is then reduced using the Karhunen-Loève transform (KLT). Finally, the discriminant analysis of feature vectors is performed in low-dimensional eigenspace. Histograms and CR values were chosen for analysis, because Parkinsonian EMG signals typically involve patterns of EMG bursts. Traditional methods of EMG amplitude and spectral analysis are not effective in analyzing impulse-like signals. The method, which was tested with EMG signals measured from 25 patients with PD and 22 healthy controls, was promising for discriminating between these two groups of subjects. The ratio of correct discrimination by augmented KLT was 86% for the control group and 72% for the patient group. On the basis of these results, further studies are suggested in order to evaluate the usability of this method in early stage diagnostics of PD.

  4. Characterization of surface EMG signals using improved approximate entropy*

    PubMed Central

    Chen, Wei-ting; Wang, Zhi-zhong; Ren, Xiao-mei

    2006-01-01

    An improved approximate entropy (ApEn) is presented and applied to characterize surface electromyography (sEMG) signals. In most previous experiments using nonlinear dynamic analysis, this certain processing was often confronted with the problem of insufficient data points and noisy circumstances, which led to unsatisfactory results. Compared with fractal dimension as well as the standard ApEn, the improved ApEn can extract information underlying sEMG signals more efficiently and accurately. The method introduced here can also be applied to other medium-sized and noisy physiological signals. PMID:16972328

  5. Preferred Sensor Sites for Surface EMG Signal Decomposition

    PubMed Central

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

    2012-01-01

    Technologies for decomposing the electromyographic (EMG) signal into its constituent motor unit action potential trains have become more practical by the advent of a non-invasive methodology using surface EMG (sEMG) sensors placed on the skin above the muscle of interest (De Luca et al. 2006 and Nawab et al. 2010). This advancement has widespread appeal among researchers and clinicians because of the ease of use, reduced risk of infection, and the greater number of motor unit action potential trains obtained compared to needle sensor techniques. In this study we investigated the influence of the sensor site on the number of identified motor unit action potential trains in six lower limb and one upper limb muscle with the intent of locating preferred sensor sites that provided the greatest number of decomposed motor unit action potential trains, or motor unit yield. Sensor sites rendered varying motor unit yields throughout the surface of a muscle. The preferred sites were located between the center and the tendinous areas of the muscle. The motor unit yield was positively correlated to the signal to noise ratio of the detected sEMG. The signal to noise ratio was inversely related to the thickness of the tissue between the sensor and the muscle fibers. A signal to noise ratio of 3 was found to be the minimum required to obtain a reliable motor unit yield. PMID:22260842

  6. High-Yield Decomposition of Surface EMG Signals

    PubMed Central

    Nawab, S. Hamid; Chang, Shey-Sheen; De Luca, Carlo J.

    2010-01-01

    Objective Automatic decomposition of surface Electromyographic (sEMG) signals into their constituent motor unit action potential trains (MUAPTs). Methods A small five-pin sensor provides four channels of sEMG signals that are in turn processed by an enhanced artificial intelligence algorithm evolved from a previous proof-of-principle. We tested the technology on sEMG signals from five muscles contracting isometrically at force levels ranging up to 100% of their maximal level, including those that were covered with more than 1.5 cm of adipose tissue. Decomposition accuracy was measured by a new method wherein a signal is first decomposed and then reconstructed and the accuracy is measured by comparison. Results were confirmed by the more established two-source method. Results The number of MUAPTs decomposed varied among muscles and force levels and mostly ranged from 20 to 30, with a maximum of 40. The accuracy of all the firings of the MUAPTs was on average 92.5%, at times reaching 97%. Conclusion Reported technology can reliably perform high-yield decomposition of sEMG signals for isometric contractions up to maximal force levels. Significance The small sensor size and the high yield and accuracy of the decomposition should render this technology useful for motor control studies and clinical investigations. PMID:20430694

  7. High-yield decomposition of surface EMG signals.

    PubMed

    Nawab, S Hamid; Chang, Shey-Sheen; De Luca, Carlo J

    2010-10-01

    Automatic decomposition of surface electromyographic (sEMG) signals into their constituent motor unit action potential trains (MUAPTs). A small five-pin sensor provides four channels of sEMG signals that are in turn processed by an enhanced artificial intelligence algorithm evolved from a previous proof-of-principle. We tested the technology on sEMG signals from five muscles contracting isometrically at force levels ranging up to 100% of their maximal level, including those that were covered with more than 1.5cm of adipose tissue. Decomposition accuracy was measured by a new method wherein a signal is first decomposed and then reconstructed and the accuracy is measured by comparison. Results were confirmed by the more established two-source method. The number of MUAPTs decomposed varied among muscles and force levels and mostly ranged from 20 to 30, and occasionally up to 40. The accuracy of all the firings of the MUAPTs was on average 92.5%, at times reaching 97%. Reported technology can reliably perform high-yield decomposition of sEMG signals for isometric contractions up to maximal force levels. The small sensor size and the high yield and accuracy of the decomposition should render this technology useful for motor control studies and clinical investigations. Copyright 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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

    PubMed

    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.

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

    PubMed

    Lobo-Prat, Joan; Janssen, Mariska M H P; Koopman, Bart F J M; Stienen, Arno H A; de Groot, Imelda J M

    2017-08-29

    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. Our previous studies showed the feasibility of using surface electromyography (sEMG) as a control interface to operate robotic arm supports in adults with DMD (22-24 years-old). However, in the biomedical engineering community there is an often raised skepticism on whether adults with DMD at the last stage of their disease have sEMG signals that can be measured and used for control. In this study sEMG signals from Biceps and Triceps Brachii muscles were measured for the first time in a 37 year-old man with DMD (Brooke 6) that lost his arm function 15 years ago. The sEMG signals were measured during maximal and sub-maximal voluntary isometric contractions and evaluated in terms of signal-to-noise ratio and co-activation ratio. Beyond the profound deterioration of the muscles, we found that sEMG signals from both Biceps and Triceps muscles were measurable in this individual, although with a maximum signal amplitude 100 times lower compared to sEMG from healthy subjects. The participant was able to voluntarily modulate the required level of muscle activation during the sub-maximal voluntary isometric contractions. Despite the low sEMG amplitude and a considerable level of muscle co-activation, simulations of an elbow orthosis using the measured sEMG as driving signal indicated that the sEMG signals of the participant had the potential to provide control of elbow movements. To the best of our knowledge this is the first time that sEMG signals from a man with DMD at the last-stage of the disease were measured, analyzed and reported. These findings offer promising perspectives to the use of sEMG as an intuitive and natural control interface for robotic arm supports in adults with DMD until

  10. Assessment of low back muscle fatigue by surface EMG signal analysis: methodological aspects.

    PubMed

    Farina, Dario; Gazzoni, Marco; Merletti, Roberto

    2003-08-01

    This paper focuses on methodological issues related to surface electromyographic (EMG) signal detection from the low back muscles. In particular, we analysed (1) the characteristics (in terms of propagating components) of the signals detected from these muscles; (2) the effect of electrode location on the variables extracted from surface EMG; (3) the effect of the inter-electrode distance (IED) on the same variables; (4) the possibility of assessing fatigue during high and very low force level contractions. To address these issues, we detected single differential surface EMG signals by arrays of eight electrodes from six locations on the two sides of the spine, at the levels of the first (L1), the second (L2), and the fifth (L5) lumbar vertebra. In total, 42 surface EMG channels were acquired at the same time during both high and low force, short and long duration contractions. The main results were: (1) signal quality is poor with predominance of non-travelling components; (2) as a consequence of point (1), in the majority of the cases it is not possible to reliably estimate muscle fiber conduction velocity; (3) despite the poor signal quality, it was possible to distinguish the fatigue properties of the investigated muscles and the fatigability at different contraction levels; (4) IED affects the sensitivity of surface EMG variables to electrode location and large IEDs are suggested when spectral and amplitude analysis is performed; (5) the sensitivity of surface EMG variables to changes in electrode location is on average larger than for other muscles with less complex architecture; (6) IED influences amplitude initial values and slopes, and spectral variable initial values; (7) normalized slopes for both amplitude and spectral variables are not affected by IED and, thus, are suggested for fatigue analysis at different postures or during movement, when IED may change in different conditions (in case of separated electrodes); (8) the surface EMG technique at the

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

    NASA Astrophysics Data System (ADS)

    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%.

  12. Limitations of surface EMG signals of extrinsic muscles in predicting postures of human hand.

    PubMed

    Vinjamuri, Ramana; Mao, Zhi-Hong; Sclabassi, Robert; Sun, Mingui

    2006-01-01

    This paper explores the limitations of sEMG (surface Electromyography) signals collected from the extrinsic muscles in the forearm in predicting the postures of human hand. Four subjects were asked to try ten extreme postures of hand which need high effort. Two of these four subjects were asked to try ten more normal postures which did not need effort During the experiments, muscle activity and static postures of the hand were measured. The data obtained were analyzed by principal component analysis. The results obtained revealed the limitations of sEMG signals of extrinsic muscles in reproducing the postures of the hand.

  13. Pattern recognition of surface EMG biological signals by means of Hilbert spectrum and fuzzy clustering.

    PubMed

    Pinzon-Morales, Ruben-Dario; Baquero-Duarte, Katherine-Andrea; Orozco-Gutierrez, Alvaro-Angel; Grisales-Palacio, Victor-Hugo

    2011-01-01

    A novel method for hand movement pattern recognition from electromyography (EMG) biological signals is proposed. These signals are recorded by a three-channel data acquisition system using surface electrodes placed over the forearm, and then processed to recognize five hand movements: opening, closing, supination, flexion, and extension. Such method combines the Hilbert-Huang analysis with a fuzzy clustering classifier. A set of metrics, calculated from the time contour of the Hilbert Spectrum, is used to compute a discriminating three-dimensional feature space. The classification task in this feature-space is accomplished by a two-stage procedure where training cases are initially clustered with a fuzzy algorithm, and test cases are then classified applying a nearest-prototype rule. Empirical analysis of the proposed method reveals an average accuracy rate of 96% in the recognition of surface EMG signals.

  14. Filterbank spectral estimators for the analysis of surface EMG signals during isometric contractions.

    PubMed

    Alty, Stephen R; Georgakis, Apostolos

    2010-01-01

    The analysis of surface electromyogram (EMG) signals during voluntary isometric contractions can yield important information relating to muscle fatigue. These EMG signals are typically processed to extract specific variables such as the Mean Frequency (MNF) and the Median Frequency (MDF) and studies often follow how these parameters change through time. Traditional approaches to estimate the MNF and MDF variables are based on the periodogram, but this method suffers from a high degree of variability due in part the choice of window size, window function and other inherent limitations. In this paper we propose the use of data-adaptive filterbank spectral analysis techniques, namely the Power Spectrum Capon (PSC) and the Amplitude Spectrum Capon (ASC) methods. These new methods are shown to provide significant reductions in MNF and MDF parameter variability over a wide range of data window sizes.

  15. An initial investigation into the real-time conversion of facial surface EMG signals to audible speech.

    PubMed

    Diener, Lorenz; Herff, Christian; Janke, Matthias; Schultz, Tanja

    2016-08-01

    This paper presents early-stage results of our investigations into the direct conversion of facial surface electromyographic (EMG) signals into audible speech in a real-time setting, enabling novel avenues for research and system improvement through real-time feedback. The system uses a pipeline approach to enable online acquisition of EMG data, extraction of EMG features, mapping of EMG features to audio features, synthesis of audio waveforms from audio features and output of the audio waveforms via speakers or headphones. Our system allows for performing EMG-to-Speech conversion with low latency and on a continuous stream of EMG data, enabling near instantaneous audio output during audible as well as silent speech production. In this paper, we present an analysis of our systems components for latency incurred, as well as the tradeoffs between conversion quality, latency and training duration required.

  16. A novel approach for removing ECG interferences from surface EMG signals using a combined ANFIS and wavelet.

    PubMed

    Abbaspour, Sara; Fallah, Ali; Lindén, Maria; Gholamhosseini, Hamid

    2016-02-01

    In recent years, the removal of electrocardiogram (ECG) interferences from electromyogram (EMG) signals has been given large consideration. Where the quality of EMG signal is of interest, it is important to remove ECG interferences from EMG signals. In this paper, an efficient method based on a combination of adaptive neuro-fuzzy inference system (ANFIS) and wavelet transform is proposed to effectively eliminate ECG interferences from surface EMG signals. The proposed approach is compared with other common methods such as high-pass filter, artificial neural network, adaptive noise canceller, wavelet transform, subtraction method and ANFIS. It is found that the performance of the proposed ANFIS-wavelet method is superior to the other methods with the signal to noise ratio and relative error of 14.97dB and 0.02 respectively and a significantly higher correlation coefficient (p<0.05).

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

    PubMed

    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.

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

    PubMed Central

    Shrirao, Nikhil A; Reddy, Narender P; Kosuri, Durga R

    2009-01-01

    Background In virtual reality (VR) systems, the user's finger and hand positions are sensed and used to control the virtual environments. Direct biocontrol of VR environments using surface electromyography (SEMG) signals may be more synergistic and unconstraining to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models. Methodology SEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-extension rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the parameters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects. Results There was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion. Conclusion Although hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals. PMID:19154615

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

    NASA Astrophysics Data System (ADS)

    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.

  20. A simulation model of the surface EMG signal for analysis of muscle activity during the gait cycle.

    PubMed

    Wang, W; De Stefano, A; Allen, R

    2006-06-01

    This work describes a model able to synthetize the surface EMG (electromyography) signal acquired from tibialis anterior and gastrocnemious medialis muscles during walking of asymptomatic adult subjects. The model assumes a muscle structure where the volume conductor is represented by multiple layers of anisotropic media. This model originates from analysis of the single fiber action potential characterized by the conduction velocity. The surface EMG of voluntary contraction is calculated by gathering motor unit action potentials estimated by the summation of all activities of muscle fibers assumed to have a uniformly parallel distribution. The parameters related to the gait cycle, such as onset and cessation timings of muscle activation, amplitude of muscle contraction, periods and sequences of motor units' recruitment, are included in the model presented. In addition, the relative positions of the electrodes during gait can also be specified in order to adapt the simulation to the different acquisition settings.

  1. Gesture recognition by instantaneous surface EMG images

    PubMed Central

    Geng, Weidong; Du, Yu; Jin, Wenguang; Wei, Wentao; Hu, Yu; Li, Jiajun

    2016-01-01

    Gesture recognition in non-intrusive muscle-computer interfaces is usually based on windowed descriptive and discriminatory surface electromyography (sEMG) features because the recorded amplitude of a myoelectric signal may rapidly fluctuate between voltages above and below zero. Here, we present that the patterns inside the instantaneous values of high-density sEMG enables gesture recognition to be performed merely with sEMG signals at a specific instant. We introduce the concept of an sEMG image spatially composed from high-density sEMG and verify our findings from a computational perspective with experiments on gesture recognition based on sEMG images with a classification scheme of a deep convolutional network. Without any windowed features, the resultant recognition accuracy of an 8-gesture within-subject test reached 89.3% on a single frame of sEMG image and reached 99.0% using simple majority voting over 40 frames with a 1,000 Hz sampling rate. Experiments on the recognition of 52 gestures of NinaPro database and 27 gestures of CSL-HDEMG database also validated that our approach outperforms state-of-the-arts methods. Our findings are a starting point for the development of more fluid and natural muscle-computer interfaces with very little observational latency. For example, active prostheses and exoskeletons based on high-density electrodes could be controlled with instantaneous responses. PMID:27845347

  2. Gesture recognition by instantaneous surface EMG images.

    PubMed

    Geng, Weidong; Du, Yu; Jin, Wenguang; Wei, Wentao; Hu, Yu; Li, Jiajun

    2016-11-15

    Gesture recognition in non-intrusive muscle-computer interfaces is usually based on windowed descriptive and discriminatory surface electromyography (sEMG) features because the recorded amplitude of a myoelectric signal may rapidly fluctuate between voltages above and below zero. Here, we present that the patterns inside the instantaneous values of high-density sEMG enables gesture recognition to be performed merely with sEMG signals at a specific instant. We introduce the concept of an sEMG image spatially composed from high-density sEMG and verify our findings from a computational perspective with experiments on gesture recognition based on sEMG images with a classification scheme of a deep convolutional network. Without any windowed features, the resultant recognition accuracy of an 8-gesture within-subject test reached 89.3% on a single frame of sEMG image and reached 99.0% using simple majority voting over 40 frames with a 1,000 Hz sampling rate. Experiments on the recognition of 52 gestures of NinaPro database and 27 gestures of CSL-HDEMG database also validated that our approach outperforms state-of-the-arts methods. Our findings are a starting point for the development of more fluid and natural muscle-computer interfaces with very little observational latency. For example, active prostheses and exoskeletons based on high-density electrodes could be controlled with instantaneous responses.

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

    PubMed

    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.

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

    PubMed

    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

  5. The analysis of surface EMG signals with the wavelet-based correlation dimension method.

    PubMed

    Wang, Gang; Zhang, Yanyan; Wang, Jue

    2014-01-01

    Many attempts have been made to effectively improve a prosthetic system controlled by the classification of surface electromyographic (SEMG) signals. Recently, the development of methodologies to extract the effective features still remains a primary challenge. Previous studies have demonstrated that the SEMG signals have nonlinear characteristics. In this study, by combining the nonlinear time series analysis and the time-frequency domain methods, we proposed the wavelet-based correlation dimension method to extract the effective features of SEMG signals. The SEMG signals were firstly analyzed by the wavelet transform and the correlation dimension was calculated to obtain the features of the SEMG signals. Then, these features were used as the input vectors of a Gustafson-Kessel clustering classifier to discriminate four types of forearm movements. Our results showed that there are four separate clusters corresponding to different forearm movements at the third resolution level and the resulting classification accuracy was 100%, when two channels of SEMG signals were used. This indicates that the proposed approach can provide important insight into the nonlinear characteristics and the time-frequency domain features of SEMG signals and is suitable for classifying different types of forearm movements. By comparing with other existing methods, the proposed method exhibited more robustness and higher classification accuracy.

  6. The Analysis of Surface EMG Signals with the Wavelet-Based Correlation Dimension Method

    PubMed Central

    Zhang, Yanyan; Wang, Jue

    2014-01-01

    Many attempts have been made to effectively improve a prosthetic system controlled by the classification of surface electromyographic (SEMG) signals. Recently, the development of methodologies to extract the effective features still remains a primary challenge. Previous studies have demonstrated that the SEMG signals have nonlinear characteristics. In this study, by combining the nonlinear time series analysis and the time-frequency domain methods, we proposed the wavelet-based correlation dimension method to extract the effective features of SEMG signals. The SEMG signals were firstly analyzed by the wavelet transform and the correlation dimension was calculated to obtain the features of the SEMG signals. Then, these features were used as the input vectors of a Gustafson-Kessel clustering classifier to discriminate four types of forearm movements. Our results showed that there are four separate clusters corresponding to different forearm movements at the third resolution level and the resulting classification accuracy was 100%, when two channels of SEMG signals were used. This indicates that the proposed approach can provide important insight into the nonlinear characteristics and the time-frequency domain features of SEMG signals and is suitable for classifying different types of forearm movements. By comparing with other existing methods, the proposed method exhibited more robustness and higher classification accuracy. PMID:24868240

  7. A threshold-based approach for muscle contraction detection from surface EMG signals

    NASA Astrophysics Data System (ADS)

    Morantes, Gaudi; Fernández, Gerardo; Altuve, Miguel

    2013-11-01

    Surface electromyographic (SEMG) signals are commonly used as control signals in prosthetic and orthotic devices. Super cial electrodes are placed on the skin of the subject to acquire its muscular activity through this signal. The muscle contraction episode is then in charge of activating and deactivating these devices. Nevertheless, there is no gold standard" to detect muscle contraction, leading to delayed responses and false and missed detections. This fact motivated us to propose a new approach that compares a smoothed version of the SEMG signal with a xed threshold, in order to detect muscle contraction episodes. After preprocessing the SEMG signal, the smoothed version is obtained using a moving average lter, where three di erent window lengths has been evaluated. The detector was tuned by maximizing sensitivity and speci city and evaluated using SEMG signals obtained from the anterior tibial and gastrocnemius muscles, taken during the walking of ve subjects. Compared with traditional detection methods, we obtain a reduction of 3 ms in the detection delay, an increase of 8% in sensitivity but a decrease of 15% in speci city. Future work is directed to the inclusion of a temporal threshold (a double-threshold approach) to minimize false detections and reduce detection delays.

  8. Error reduction in EMG signal decomposition.

    PubMed

    Kline, Joshua C; De Luca, Carlo J

    2014-12-01

    Decomposition of the electromyographic (EMG) signal into constituent action potentials and the identification of individual firing instances of each motor unit in the presence of ambient noise are inherently probabilistic processes, whether performed manually or with automated algorithms. Consequently, they are subject to errors. We set out to classify and reduce these errors by analyzing 1,061 motor-unit action-potential trains (MUAPTs), obtained by decomposing surface EMG (sEMG) signals recorded during human voluntary contractions. Decomposition errors were classified into two general categories: location errors representing variability in the temporal localization of each motor-unit firing instance and identification errors consisting of falsely detected or missed firing instances. To mitigate these errors, we developed an error-reduction algorithm that combines multiple decomposition estimates to determine a more probable estimate of motor-unit firing instances with fewer errors. The performance of the algorithm is governed by a trade-off between the yield of MUAPTs obtained above a given accuracy level and the time required to perform the decomposition. When applied to a set of sEMG signals synthesized from real MUAPTs, the identification error was reduced by an average of 1.78%, improving the accuracy to 97.0%, and the location error was reduced by an average of 1.66 ms. The error-reduction algorithm in this study is not limited to any specific decomposition strategy. Rather, we propose it be used for other decomposition methods, especially when analyzing precise motor-unit firing instances, as occurs when measuring synchronization.

  9. Error reduction in EMG signal decomposition

    PubMed Central

    Kline, Joshua C.

    2014-01-01

    Decomposition of the electromyographic (EMG) signal into constituent action potentials and the identification of individual firing instances of each motor unit in the presence of ambient noise are inherently probabilistic processes, whether performed manually or with automated algorithms. Consequently, they are subject to errors. We set out to classify and reduce these errors by analyzing 1,061 motor-unit action-potential trains (MUAPTs), obtained by decomposing surface EMG (sEMG) signals recorded during human voluntary contractions. Decomposition errors were classified into two general categories: location errors representing variability in the temporal localization of each motor-unit firing instance and identification errors consisting of falsely detected or missed firing instances. To mitigate these errors, we developed an error-reduction algorithm that combines multiple decomposition estimates to determine a more probable estimate of motor-unit firing instances with fewer errors. The performance of the algorithm is governed by a trade-off between the yield of MUAPTs obtained above a given accuracy level and the time required to perform the decomposition. When applied to a set of sEMG signals synthesized from real MUAPTs, the identification error was reduced by an average of 1.78%, improving the accuracy to 97.0%, and the location error was reduced by an average of 1.66 ms. The error-reduction algorithm in this study is not limited to any specific decomposition strategy. Rather, we propose it be used for other decomposition methods, especially when analyzing precise motor-unit firing instances, as occurs when measuring synchronization. PMID:25210159

  10. Effects of input frequency content and signal-to-noise ratio on the parametric estimation of surface EMG-torque dynamics.

    PubMed

    Golkar, Mahsa A; Kearney, Robert E

    2016-08-01

    The dynamic relationship between surface EMG (sEMG) and torque can be estimated from data acquired while subjects voluntarily modulate joint torque. We have shown that for such data, the input (EMG) contains a feedback component from the output (torque) and so accurate estimates of the dynamics require the use of closed-loop identification algorithms. Moreover, this approach has several other limitations since the input is controlled indirectly and so the frequency content and signal-to-noise ratio cannot be controlled. This paper investigates how these factors influence the accuracy of estimates. This was studied using experimental sEMG recorded from healthy human subjects for tasks with different modulation rates. Box-Jenkin (BJ) method was used for identification. Results showed that input frequency content had little effect on estimates of gain and natural frequency but had strong effect on damping factor estimates. It was demonstrated that to accurately estimate the damping factor, the command signal switching rate must be less than 2s. It was also shown that random errors increased with noise level but was limited to 10% of the parameters true value for highest noise level tested. To summarize, simulation study of this work showed that voluntary modulation paradigm can accurately identify sEMG-torque dynamics.

  11. Distinction of Abnormality of Surgical Operation on the Basis of Surface EMG Signals

    NASA Astrophysics Data System (ADS)

    Nakaya, Yusuke; Ishii, Chiharu; Nakakuki, Takashi; Nishitani, Yosuke; Hikita, Mitsutaka

    In this paper, a novel method for automatic identification of a surgical operation and on-line recognition of the singularity of the identified surgical operation is proposed. Suturing is divided into six operations. The features of the operation are extracted from the measurements of the movement of the forceps, and then, on the basis of the threshold criteria for the six operations, a surgical operation is identified as one of the six operations. Next, the features of any singularity of operation are extracted from operator's surface electromyogram signals, and the identified surgical operation is classified as either normal or singular using a self-organizing map. Using the built laparoscopic-surgery simulator with two forceps, the identification of each surgical operation and the distinction of the singularity of the identified surgical operation were carried out for a specific surgical operation, namely, insertion of a needle during suturing. Each surgical operation in suturing could be identified with more than 80% accuracy, and the singularity of the surgical operation of insertion could be distinguished with approximately 80% accuracy on an average. The experimental results showed the effectiveness of the proposed method.

  12. [Evaluation of work-related biomechanical overload: techniques for the acquisition and analysis of surface EMG signal].

    PubMed

    Pigini, Lucia; Colombini, Daniela; Rabuffetti, M; Ferrarin, M

    2010-01-01

    The aim of this research was to obtain information concerning muscle fatigue and muscle activation levels by measuring quantitative parameters through the surface electromyographic signal, and use such information to integrate the OCRA (Occupational Repetitive Actions) method for risk assessment of upper limb biomechanical overload Along with the main risk factors associated with the development of work-related upper limb musculoskeletal disorders (UL WMSDs) like posture, movement, frequency of action and organizational factors, this method also takes into account the muscular effort. Unlike the other risk factors that can be directly measured during inspections on farms, muscular effort is currently estimated only via a subjective assessment scale (Borg CR-10 scale). A new apparatus and new procedures were implemented for synchronized EMG and video acquisition, which guarantee a high degree of inter- and intra-subject repeatability, and an ad hoc software for data elaboration was developed They have been specifically designed for "on the field" applications. The methodology was first tested in the laboratory on a group of 12 healthy subjects, studying a repetitive task, running in two different ways, (high/low OCRA index) and interspersed with isometric tests for an indirect measurement of dynamic fatigue. The methodology was then tested in a working environment to compare the muscular effort required during the use of different types of tools for pruning. Results of the laboratory protocol showed onset of fatigue for Anterior Deltoid, Middle Deltoid and Brachial Triceps muscles only for the high-risk index mode, as demonstrated by the significance of the Bonferroni tests (p < 0.05) on MDF (Median Frequency) calculated from isometric tests. They also showed significant differences in terms of higher level of muscle activation, and thus required force, in the case of high OCRA index work task compared to the one at low risk (Wilcoxon, p < 0.05) for all analysed

  13. An EMG-based robot control scheme robust to time-varying EMG signal features.

    PubMed

    Artemiadis, Panagiotis K; Kyriakopoulos, Kostas J

    2010-05-01

    Human-robot control interfaces have received increased attention during the past decades. With the introduction of robots in everyday life, especially in providing services to people with special needs (i.e., elderly, people with impairments, or people with disabilities), there is a strong necessity for simple and natural control interfaces. In this paper, electromyographic (EMG) signals from muscles of the human upper limb are used as the control interface between the user and a robot arm. EMG signals are recorded using surface EMG electrodes placed on the user's skin, making the user's upper limb free of bulky interface sensors or machinery usually found in conventional human-controlled systems. The proposed interface allows the user to control in real time an anthropomorphic robot arm in 3-D space, using upper limb motion estimates based only on EMG recordings. Moreover, the proposed interface is robust to EMG changes with respect to time, mainly caused by muscle fatigue or adjustments of contraction level. The efficiency of the method is assessed through real-time experiments, including random arm motions in the 3-D space with variable hand speed profiles.

  14. Emg Signal Analysis of Healthy and Neuropathic Individuals

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed Central

    Farahi, Morteza; Rojas, Monica; Mañanas, Miguel Angel; Farina, Dario

    2016-01-01

    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 performed

  16. Techniques of EMG signal analysis: detection, processing, classification and applications

    PubMed Central

    Hussain, M.S.; Mohd-Yasin, F.

    2006-01-01

    Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications. PMID:16799694

  17. Accuracy assessment of CKC high-density surface EMG decomposition in biceps femoris muscle

    NASA Astrophysics Data System (ADS)

    Marateb, H. R.; McGill, K. C.; Holobar, A.; Lateva, Z. C.; Mansourian, M.; Merletti, R.

    2011-10-01

    The aim of this study was to assess the accuracy of the convolution kernel compensation (CKC) method in decomposing high-density surface EMG (HDsEMG) signals from the pennate biceps femoris long-head muscle. Although the CKC method has already been thoroughly assessed in parallel-fibered muscles, there are several factors that could hinder its performance in pennate muscles. Namely, HDsEMG signals from pennate and parallel-fibered muscles differ considerably in terms of the number of detectable motor units (MUs) and the spatial distribution of the motor-unit action potentials (MUAPs). In this study, monopolar surface EMG signals were recorded from five normal subjects during low-force voluntary isometric contractions using a 92-channel electrode grid with 8 mm inter-electrode distances. Intramuscular EMG (iEMG) signals were recorded concurrently using monopolar needles. The HDsEMG and iEMG signals were independently decomposed into MUAP trains, and the iEMG results were verified using a rigorous a posteriori statistical analysis. HDsEMG decomposition identified from 2 to 30 MUAP trains per contraction. 3 ± 2 of these trains were also reliably detected by iEMG decomposition. The measured CKC decomposition accuracy of these common trains over a selected 10 s interval was 91.5 ± 5.8%. The other trains were not assessed. The significant factors that affected CKC decomposition accuracy were the number of HDsEMG channels that were free of technical artifact and the distinguishability of the MUAPs in the HDsEMG signal (P < 0.05). These results show that the CKC method reliably identifies at least a subset of MUAP trains in HDsEMG signals from low force contractions in pennate muscles.

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

    PubMed

    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.

  19. Voiceless Bangla vowel recognition using sEMG signal.

    PubMed

    Mostafa, S S; Awal, M A; Ahmad, M; Rashid, M A

    2016-01-01

    Some people cannot produce sound although their facial muscles work properly due to having problem in their vocal cords. Therefore, recognition of alphabets as well as sentences uttered by these voiceless people is a complex task. This paper proposes a novel method to solve this problem using non-invasive surface Electromyogram (sEMG). Firstly, eleven Bangla vowels are pronounced and sEMG signals are recorded at the same time. Different features are extracted and mRMR feature selection algorithm is then applied to select prominent feature subset from the large feature vector. After that, these prominent features subset is applied in the Artificial Neural Network for vowel classification. This novel Bangla vowel classification method can offer a significant contribution in voice synthesis as well as in speech communication. The result of this experiment shows an overall accuracy of 82.3 % with fewer features compared to other studies in different languages.

  20. Can standard surface EMG processing parameters be used to estimate motor unit global firing rate?

    NASA Astrophysics Data System (ADS)

    Zhou, Ping; Zev Rymer, William

    2004-06-01

    The relations between motor unit global firing rates and established quantitative measures for processing the surface electromyogram (EMG) signals were explored using a simulation approach. Surface EMG signals were simulated using the reported properties of the first dorsal interosseous muscle in man, and the models were varied systematically, using several hypothetical relations between motor unit electrical and force output, and also using different motor unit firing rate strategies. The utility of using different EMG processing parameters to help estimate global motor unit firing rate was evaluated based on their relations to the number of motor unit action potentials (MUAPs) in the simulated surface EMG signals. Our results indicate that the relation between motor unit electrical and mechanical properties, and the motor unit firing rate scheme are all important factors determining the form of the relation between surface EMG amplitude and motor unit global firing rate. Conversely, these factors have less impact on the relations between turn or zero-crossing point counts and the number of MUAPs in surface EMG. We observed that the number of turn or zero-crossing points tends to saturate with the increase in the MUAP number in surface EMG, limiting the utility of these measures as estimates of MUAP number. The simulation results also indicate that the mean or median frequency of the surface EMG power spectrum is a poor indicator of the global motor unit firing rate.

  1. Extraction of the EPP Component from the Surface EMG

    PubMed Central

    Kumai, Toshifumi

    2009-01-01

    A surface electromyogram (EMG), especially when recorded near the neuromuscular junction, is expected to contain the endplate potential (EPP) component which can be extracted with an appropriate signal filter. Two factors are important: the EMG must be recorded in monopolar fashion, and the recording must be done so the low frequency signal corresponding the EPP is not eliminated. This report explains how to extract the EPP component from the EMG of the masseter muscle in a human subject. The surface EMG is recorded from eight sites using traditional disc electrodes aligned along over the muscle, with equal inter-electrode distance from the zygomatic arch to the angle of mandible in response to quick gum clenching. A reference electrode is placed on the tip of the nose. The EPP component is extracted from the raw EMGs by applying a high-cut digital filter (2nd dimension Butterworth filter) with a range of 10-35 Hz. When the filter is set to 10 Hz, the extracted EPP wave deflects either negative or positive depending on the recording site. The difference in the polarity reflects the sink-source relation of the end plate current, with the site showing the most negative deflection corresponding to the neuromuscular junction. In the case of the masseter muscle, the neuromuscular junction is estimated to be located in the inferior portion close to the angle of mandible. The EPP component exhibits an interesting oscillation when the cut-off frequency of the high-cut digital filter is set to 30 Hz. The EPP oscillation indicates that muscle contraction is adjusted in an intermittent manner. Abnormal tremors accompanying various sorts of diseases may be substantially due to this EPP oscillation, which becomes slower and is difficult to cease. PMID:20016459

  2. Extraction of the EPP component from the surface EMG.

    PubMed

    Kumai, Toshifumi

    2009-12-16

    A surface electromyogram (EMG), especially when recorded near the neuromuscular junction, is expected to contain the endplate potential (EPP) component which can be extracted with an appropriate signal filter. Two factors are important: the EMG must be recorded in monopolar fashion, and the recording must be done so the low frequency signal corresponding the EPP is not eliminated. This report explains how to extract the EPP component from the EMG of the masseter muscle in a human subject. The surface EMG is recorded from eight sites using traditional disc electrodes aligned along over the muscle, with equal inter-electrode distance from the zygomatic arch to the angle of mandible in response to quick gum clenching. A reference electrode is placed on the tip of the nose. The EPP component is extracted from the raw EMGs by applying a high-cut digital filter (2nd dimension Butterworth filter) with a range of 10-35 Hz. When the filter is set to 10 Hz, the extracted EPP wave deflects either negative or positive depending on the recording site. The difference in the polarity reflects the sink-source relation of the end plate current, with the site showing the most negative deflection corresponding to the neuromuscular junction. In the case of the masseter muscle, the neuromuscular junction is estimated to be located in the inferior portion close to the angle of mandible. The EPP component exhibits an interesting oscillation when the cut-off frequency of the high-cut digital filter is set to 30 Hz. The EPP oscillation indicates that muscle contraction is adjusted in an intermittent manner. Abnormal tremors accompanying various sorts of diseases may be substantially due to this EPP oscillation, which becomes slower and is difficult to cease.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

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

    PubMed Central

    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 < 0.001) and also compared with experimental data collected during gait (55 vs. 124 ms, p < 0.001). In conclusion, addition of TKEO as a step in conditioning surface EMG signals increases the detection accuracy of EMG burst boundaries. PMID:20526612

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  8. Individual finger classification from surface EMG: Influence of electrode set.

    PubMed

    Celadon, Nicolo; Dosen, Strahinja; Paleari, Marco; Farina, Dario; Ariano, Paolo

    2015-01-01

    The aim of this work was to minimize the number of channels, determining acceptable electrode locations and optimizing electrode-recording configurations to decode isometric flexion and extension of individual fingers. Nine healthy subjects performed cyclical isometric contractions activating individual fingers. During the experiment they tracked a moving visual marker indicating the contraction type (flexion/extension), desired activation level and the finger that should be employed. Surface electromyography (sEMG) signals were detected from the forearm muscles using a matrix of 192 channels (24 longitudinal columns and 8 transversal rows, 10 mm inter-electrode distance). The classification was evaluated in the context of a linear discriminant analysis (LDA) with different sets of EMG electrodes: A) one linear array of 8 electrodes, B) two arrays of 8 electrodes each, C) a set with one electrode on the barycenter of each sEMG activity area, D) all the recorded channels. The results showed that the classification accuracy depended on the electrode set (F=14.67, p<;0.001). The best reduction approaches were the barycenter calculation and the use of two linear arrays of electrodes, which performed similarly to each other (both > 82% of average success rate). Considering the computation time and electrode positioning, it is concluded that two arrays of 8 electrodes provide an optimal configuration to classify the isometric flexion and extension of individual fingers.

  9. Driving Electric Vehicle by EMG Signal Considering Frequency Components

    NASA Astrophysics Data System (ADS)

    Aso, Shinichi; Sasaki, Akinori; Hashimoto, Hiroshi; Ishii, Chiharu

    This paper proposes a useful method driving the electric vehicle by EMG signals (Electromyographic signals) which are filtered on the basis of frequency components which change with muscle contraction. This method estimates strength of muscular tension by a single EMG signal. By our method, user is able to control speed of the electric vehicle by strength of muscular tension. The method of speed control may give user good or bad operation feeling in the meaning of SD (Semantic Differential) method and factor analysis. The operation feeling is evaluated by experiment on EMG interface in cases of using filters or not. As a result, it is shown that operation feeling is influenced by this method.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed Central

    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

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

    PubMed

    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.

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  15. Motor unit size estimation: confrontation of surface EMG with macro EMG.

    PubMed

    Roeleveld, K; Stegeman, D F; Falck, B; Stålberg, E V

    1997-06-01

    Surface EMG (SEMG) is little used for diagnostic purposes in clinical neurophysiology, mainly because it provides little direct information on individual motor units (MUs). One of the techniques to estimate the MU size is intra-muscular Macro EMG. The present study compares SEMG with Macro EMG. Fifty-eight channel SEMG was recorded simultaneously with Macro EMG. Individual MUPs were obtained by single fiber triggered averaging. All recordings were made from the biceps brachii of healthy subjects during voluntary contraction at low force. High positive correlations were found between all Macro and Surface motor unit potential (MUP) parameters: area, peak-to-peak amplitude, negative peak amplitude and positive peak amplitude. The MUPs recorded with SEMG were dependent on the distance between the MU and the skin surface. Normalizing the SEMG parameters for MU location did not improve the correlation coefficient between the parameters of both techniques. The two measurement techniques had almost the same relative range in MUP parameters in any individual subject compared to the others, especially after normalizing the surface MUP parameters for MU location. MUPs recorded with this type of SEMG provide useful information about the MU size.

  16. Analysis of surface EMG baseline for detection of hidden muscle activity

    NASA Astrophysics Data System (ADS)

    Zhang, Xu; Zhou, Ping

    2014-02-01

    Objective. This study explored the feasibility of detecting hidden muscle activity in surface electromyogram (EMG) baseline. Approach. Power spectral density (PSD) analysis and multi-scale entropy (MSE) analysis were used. Both analyses were applied to computer simulations of surface EMG baseline with the presence (representing activity data) or absence (representing reference data) of hidden muscle activity, as well as surface electrode array EMG baseline recordings of healthy control and amyotrophic lateral sclerosis (ALS) subjects. Main results. Although the simulated reference data and the activity data yielded no distinguishable difference in the time domain, they demonstrated a significant difference in the frequency and signal complexity domains with the PSD and MSE analyses. For a comparison using pooled data, such a difference was also observed when the PSD and MSE analyses were applied to surface electrode array EMG baseline recordings of healthy control and ALS subjects, which demonstrated no distinguishable difference in the time domain. Compared with the PSD analysis, the MSE analysis appeared to be more sensitive for detecting the difference in surface EMG baselines between the two groups. Significance. The findings implied the presence of a hidden muscle activity in surface EMG baseline recordings from the ALS subjects. To promote the presented analysis as a useful diagnostic or investigatory tool, future studies are necessary to assess the pathophysiological nature or origins of the hidden muscle activity, as well as the baseline difference at the individual subject level.

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

    PubMed

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

    2013-01-01

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

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

    PubMed Central

    Sezgin, Necmettin

    2012-01-01

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

  19. Surface EMG of jaw elevator muscles: effect of electrode location and inter-electrode distance.

    PubMed

    Castroflorio, T; Farina, D; Bottin, A; Piancino, M G; Bracco, P; Merletti, R

    2005-06-01

    This study addresses methodological issues on surface electromyographic (EMG) signal recording from jaw elevator muscles. The aims were (i) to investigate the sensitivity to electrode displacements of amplitude and spectral surface EMG variables, (ii) to analyse if this sensitivity is affected by the inter-electrode distance of the bipolar recording, and (iii) to investigate the effect of inter-electrode distance on the estimated amplitude and spectral EMG variables. The superficial masseter and anterior temporalis muscles of 13 subjects were investigated by means of a linear electrode array. The percentage difference in EMG variable estimates from signals detected at different locations over the muscle was larger than 100% of the estimated value. Increasing the inter-electrode distance resulted in a significant reduction of the estimation variability because of electrode displacement. A criterion for electrode placement selection is suggested, with which the sensitivity of EMG variables to small electrode displacements was of the order of 2% for spectral and 6% for amplitude variables. Finally, spectral and, in particular, amplitude EMG variables were very sensitive to inter-electrode distance, which thus should be fixed when subjects or muscles are compared in the same or different experimental conditions.

  20. Subauditory Speech Recognition based on EMG/EPG Signals

    NASA Technical Reports Server (NTRS)

    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.

  1. Assessment of the non-Gaussianity and non-linearity levels of simulated sEMG signals on stationary segments.

    PubMed

    Messaoudi, Noureddine; Bekka, Raïs El'hadi; Ravier, Philippe; Harba, Rachid

    2017-02-01

    The purpose of this paper was to evaluate the effects of the longitudinal single differential (LSD), the longitudinal double differential (LDD) and the normal double differential (NDD) spatial filters, the electrode shape, the inter-electrode distance (IED) on non-Gaussianity and non-linearity levels of simulated surface EMG (sEMG) signals when the maximum voluntary contraction (MVC) varied from 10% to 100% by a step of 10%. The effects of recruitment range thresholds (RR), the firing rate (FR) strategy and the peak firing rate (PFR) of motor units were also considered. A cylindrical multilayer model of the volume conductor and a model of motor unit (MU) recruitment and firing rate were used to simulate sEMG signals in a pool of 120 MUs for 5s. Firstly, the stationarity of sEMG signals was tested by the runs, the reverse arrangements (RA) and the modified reverse arrangements (MRA) tests. Then the non-Gaussianity was characterised with bicoherence and kurtosis, and non-linearity levels was evaluated with linearity test. The kurtosis analysis showed that the sEMG signals detected by the LSD filter were the most Gaussian and those detected by the NDD filter were the least Gaussian. In addition, the sEMG signals detected by the LSD filter were the most linear. For a given filter, the sEMG signals detected by using rectangular electrodes were more Gaussian and more linear than that detected with circular electrodes. Moreover, the sEMG signals are less non-Gaussian and more linear with reverse onion-skin firing rate strategy than those with onion-skin strategy. The levels of sEMG signal Gaussianity and linearity increased with the increase of the IED, RR and PFR. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    PubMed

    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.

  3. Classification of EMG signals using PCA and FFT.

    PubMed

    Güler, Nihal Fatma; Koçer, Sabri

    2005-06-01

    In this study, the fast Fourier transform (FFT) analysis was applied to EMG signals recorded from ulnar nerves of 59 patients to interpret data. The data of the patients were diagnosed by the neurologists as 19 patients were normal, 20 patients had neuropathy and 20 patients had myopathy. The amount of FFT coefficients had been reduced by using principal components analysis (PCA). This would facilitate calculation and storage of EMG data. PCA coefficients were applied to multilayer perceptron (MLP) and support vector machine (SVM) and both classified systems of performance values were computed. Consequently, the results show that SVM has high anticipation level in the diagnosis of neuromuscular disorders. It is proved that its test performance is high compared with MLP.

  4. Muscle force estimation with surface EMG during dynamic muscle contractions: a wavelet and ANN based approach.

    PubMed

    Bai, Fengjun; Chew, Chee-Meng

    2013-01-01

    Human muscle force estimation is important in biomechanics studies, sports and assistive devices fields. Therefore, it is essential to develop an efficient algorithm to estimate force exerted by muscles. The purpose of this study is to predict force/torque exerted by muscles under dynamic muscle contractions based on continuous wavelet transform (CWT) and artificial neural networks (ANN) approaches. Mean frequency (MF) of the surface electromyography (EMG) signals power spectrum was calculated from CWT. ANN models were trained to derive the MF-force relationships from the subset of EMG signals and the measured forces. Then we use the networks to predict the individual muscle forces for different muscle groups. Fourteen healthy subjects (10 males and 4 females) were voluntarily recruited in this study. EMG signals were collected from the biceps brachii, triceps, hamstring and quadriceps femoris muscles to evaluate the proposed method. Root mean square errors (RMSE) and correlation coefficients between the predicted forces and measured actual forces were calculated.

  5. Identification of swallowing events from sEMG Signals Obtained from Healthy Adults.

    PubMed

    Crary, Michael A; Carnaby Mann, Giselle D; Groher, Michael E

    2007-04-01

    Surface electromyography (sEMG) is being used with increasing frequency to identify the occurrence of swallowing, to describe swallow physiology, and to treat impaired swallowing function in dysphagic patients. Despite this increased utilization, limited information is available regarding the validity and reliability of investigators and clinicians to interpret sEMG data in reference to swallowing. This study examines the validity and interjudge reliability of swallow identification using sEMG records obtained from healthy adults. Validity and reliability estimates were compared between experienced and naïve judges in the identification of swallows from graphic sEMG records. Multiple validity estimates were high, indicating a strong degree of accuracy in identification of swallows versus nonswallow movements from sEMG traces. Experienced judges were more accurate than naïve judges (classification accuracy: experienced = 90% vs. naïve = 81%; p = 0.006, kappa: experienced = 0.89 vs. naïve 0.62; p = 0.008). Judges in both groups were more likely to classify swallows as nonswallow movements (false negatives) than to classify nonswallow movements as swallows (false positives). Interjudge reliability estimates indicated a high degree of agreement among judges in the identification of swallows versus nonswallow movements from the sEMG signal, with higher agreement among experienced judges (average kappa coefficient: experienced = 0.75 vs. naïve = 0.51). These results suggest that the sEMG graphic record is a valid and reliable tool for identifying normal swallows and that experience with this technique results in better identification and interjudge agreement.

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

    PubMed Central

    2010-01-01

    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 classification of EMG signals by

  7. Reliability of surface EMG during sustained contractions of the quadriceps.

    PubMed

    Mathur, S; Eng, J J; MacIntyre, D L

    2005-02-01

    The purpose of this study was to determine test-retest reliability for median frequency (MDF) and amplitude of surface EMG during sustained fatiguing contractions of the quadriceps. Twenty-two healthy subjects (11 males and 11 females) were tested on two days held one week apart. Surface EMG was recorded from rectus femoris (RF), vastus lateralis (VL) and vastus medialis (VM) during sustained isometric contractions at 80% and 20% of maximal voluntary contraction (MVC) held to exhaustion. Quadriceps fatigue was described using four measures for both MDF and amplitude of EMG: initial, final, normalized final and slope. For both MDF and amplitude, the initial, final and normalized EMG showed moderate to high reliability for all three muscle groups at both contraction levels (ICC=0.59-0.88 for MDF; ICC=0.58-0.99 for amplitude). Slope of MDF and amplitude was associated with a large degree of variability and low ICCs for the 80% but not the 20% MVC. MDF and amplitude of EMG during sustained contractions of the quadriceps are reproducible; normalized final values of MDF and amplitude show better reliability than slope.

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

    PubMed Central

    2014-01-01

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

  9. Surface EMG-Based Inter-Session Gesture Recognition Enhanced by Deep Domain Adaptation.

    PubMed

    Du, Yu; Jin, Wenguang; Wei, Wentao; Hu, Yu; Geng, Weidong

    2017-02-24

    High-density surface electromyography (HD-sEMG) is to record muscles' electrical activity from a restricted area of the skin by using two dimensional arrays of closely spaced electrodes. This technique allows the analysis and modelling of sEMG signals in both the temporal and spatial domains, leading to new possibilities for studying next-generation muscle-computer interfaces (MCIs). sEMG-based gesture recognition has usually been investigated in an intra-session scenario, and the absence of a standard benchmark database limits the use of HD-sEMG in real-world MCI. To address these problems, we present a benchmark database of HD-sEMG recordings of hand gestures performed by 23 participants, based on an 8 × 16 electrode array, and propose a deep-learning-based domain adaptation framework to enhance sEMG-based inter-session gesture recognition. Experiments on NinaPro, CSL-HDEMG and our CapgMyo dataset validate that our approach outperforms state-of-the-arts methods on intra-session and effectively improved inter-session gesture recognition.

  10. Surface EMG-Based Inter-Session Gesture Recognition Enhanced by Deep Domain Adaptation

    PubMed Central

    Du, Yu; Jin, Wenguang; Wei, Wentao; Hu, Yu; Geng, Weidong

    2017-01-01

    High-density surface electromyography (HD-sEMG) is to record muscles’ electrical activity from a restricted area of the skin by using two dimensional arrays of closely spaced electrodes. This technique allows the analysis and modelling of sEMG signals in both the temporal and spatial domains, leading to new possibilities for studying next-generation muscle-computer interfaces (MCIs). sEMG-based gesture recognition has usually been investigated in an intra-session scenario, and the absence of a standard benchmark database limits the use of HD-sEMG in real-world MCI. To address these problems, we present a benchmark database of HD-sEMG recordings of hand gestures performed by 23 participants, based on an 8 × 16 electrode array, and propose a deep-learning-based domain adaptation framework to enhance sEMG-based inter-session gesture recognition. Experiments on NinaPro, CSL-HDEMG and our CapgMyo dataset validate that our approach outperforms state-of-the-arts methods on intra-session and effectively improved inter-session gesture recognition. PMID:28245586

  11. Examination of Poststroke Alteration in Motor Unit Firing Behavior Using High-Density Surface EMG Decomposition.

    PubMed

    Li, Xiaoyan; Holobar, Ales; Gazzoni, Marco; Merletti, Roberto; Rymer, William Zev; Zhou, Ping

    2015-05-01

    Recent advances in high-density surface electromyogram (EMG) decomposition have made it a feasible task to discriminate single motor unit activity from surface EMG interference patterns, thus providing a noninvasive approach for examination of motor unit control properties. In the current study, we applied high-density surface EMG recording and decomposition techniques to assess motor unit firing behavior alterations poststroke. Surface EMG signals were collected using a 64-channel 2-D electrode array from the paretic and contralateral first dorsal interosseous (FDI) muscles of nine hemiparetic stroke subjects at different isometric discrete contraction levels between 2 to 10 N with a 2 N increment step. Motor unit firing rates were extracted through decomposition of the high-density surface EMG signals and compared between paretic and contralateral muscles. Across the nine tested subjects, paretic FDI muscles showed decreased motor unit firing rates compared with contralateral muscles at different contraction levels. Regression analysis indicated a linear relation between the mean motor unit firing rate and the muscle contraction level for both paretic and contralateral muscles (p < 0.001), with the former demonstrating a lower increment rate (0.32 pulses per second (pps)/N) compared with the latter (0.67 pps/N). The coefficient of variation (averaged over the contraction levels) of the motor unit firing rates for the paretic muscles (0.21 ± 0.012) was significantly higher than for the contralateral muscles (0.17 ± 0.014) (p < 0.05). This study provides direct evidence of motor unit firing behavior alterations poststroke using surface EMG, which can be an important factor contributing to hemiparetic muscle weakness.

  12. Wiener filtering of surface EMG with a priori SNR estimation toward myoelectric control for neurological injury patients.

    PubMed

    Liu, Jie; Ying, Dongwen; Zhou, Ping

    2014-12-01

    Voluntary surface electromyogram (EMG) signals from neurological injury patients are often corrupted by involuntary background interference or spikes, imposing difficulties for myoelectric control. We present a novel framework to suppress involuntary background spikes during voluntary surface EMG recordings. The framework applies a Wiener filter to restore voluntary surface EMG signals based on tracking a priori signal to noise ratio (SNR) by using the decision-directed method. Semi-synthetic surface EMG signals contaminated by different levels of involuntary background spikes were constructed from a database of surface EMG recordings in a group of spinal cord injury subjects. After the processing, the onset detection of voluntary muscle activity was significantly improved against involuntary background spikes. The magnitude of voluntary surface EMG signals can also be reliably estimated for myoelectric control purpose. Compared with the previous sample entropy analysis for suppressing involuntary background spikes, the proposed framework is characterized by quick and simple implementation, making it more suitable for application in a myoelectric control system toward neurological injury rehabilitation.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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

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

    PubMed

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

    2015-05-01

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

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

    NASA Astrophysics Data System (ADS)

    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

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

    PubMed

    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.

  18. Analysis of the EMG Signal During Cyclic Movements Using Multicomponent AM-FM Decomposition.

    PubMed

    Biagetti, Giorgio; Crippa, Paolo; Curzi, Alessandro; Orcioni, Simone; Turchetti, Claudio

    2015-09-01

    Sport, fitness, as well as rehabilitation activities, often require the accomplishment of repetitive movements. The correctness of the exercises is often related to the capability of maintaining the required cadence and muscular force. Failure to maintain the required force, also known as muscle fatigue, is accompanied by a shift in the spectral content of the surface electromyography (EMG) signal toward lower frequencies. This paper presents a novel approach for simultaneously obtaining exercise repetition frequency and evaluating muscular fatigue, as functions of time, by only using the EMG signal. The mean frequency of the amplitude spectrum (MFA) of the EMG signal, considered as a function of time, is directly related to the dynamics of the movement performed and to the fatigue of the involved muscles. If the movement is cyclic, MFA will display the same pattern and its average will tend to decrease. These two effects have been simultaneously modeled by a two-component AM-FM model based on the Hilbert transform. The method was tested on signals recorded using a wireless system applied to healthy subjects performing dumbbell biceps curls, dumbbell lateral rises, and bodyweight squats. Experimental results show the excellent performance of the proposed technique.

  19. Nonlinear Analysis of Surface EMG Time Series

    NASA Astrophysics Data System (ADS)

    Zurcher, Ulrich; Kaufman, Miron; Sung, Paul

    2004-04-01

    Applications of nonlinear analysis of surface electromyography time series of patients with and without low back pain are presented. Limitations of the standard methods based on the power spectrum are discussed.

  20. Surface EMG of jaw-elevator muscles and chewing pattern in complete denture wearers.

    PubMed

    Piancino, M G; Farina, D; Talpone, F; Castroflorio, T; Gassino, G; Margarino, V; Bracco, P

    2005-12-01

    The aim of this study was to investigate the adaptation process of masticatory patterns to a new complete denture in edentulous subjects. For this purpose, muscle activity and kinematic parameters of the chewing pattern were simultaneously assessed in seven patients with complete maxillary and mandibular denture. The patients were analysed (i) with the old denture, (ii) with the new denture at the delivery, (iii) after 1 month and (iv) after 3 months from the delivery of the new denture. Surface electromyographic (EMG) signals were recorded from the masseter and temporalis anterior muscles of both sides and jaw movements were tracked measuring the motion of a tiny magnet attached at the lower inter-incisor point. The subjects were asked to chew a bolus on the right and left side. At the delivery of the new denture, peak EMG amplitude of the masseter of the side of the bolus was lower than with the old denture and the masseters of the two sides showed the same intensity of EMG activity, contrary to the case with the old denture. EMG amplitude and asymmetry of the two masseter activities returned as with the old denture in 3 months. The EMG activity in the temporalis anterior was larger with the old denture than in the other conditions. The chewing cycle width and lateral excursion decreased at the delivery of the new denture and recovered after 3 months.

  1. Surface EMG-recordings using a miniaturised matrix electrode: a new technique for small animals.

    PubMed

    Biedermann, F; Schumann, N P; Fischer, M S; Scholle, H C

    2000-04-01

    A new method for multichannel surface-EMG measurements in small animals is presented. The underlying scientific aim is the characterisation of the spreading and the co-ordination of skeletal muscle activation between different muscles or muscle parts, depending on various motor tasks. The myoelectrical signals were recorded monopolarly by a 16-channel matrix electrode on the muscle surface directly under the skin on the fascia of the investigated muscle, without damaging the muscle. Surface-EMG's were recorded for at least 5 days after surgery without electrical interferences. During defined motor tasks, the projection of the myoelectrical activation of the different parts of the M. triceps brachii of rats (Rattus norvegicus), pikas (Ochotona rufescens) and cuis (Galea musteloides) or the M. anconeus of toads (Bufo marinus) on the muscle surface was mapped. The locomotion of the investigated animals was monitored by a three-dimensional kinematic analysis (video and/or high-speed cineradiography). There was no perceptible influence from application of EMG matrix electrode. The miniaturised matrix electrode seemed practicable in gaining insight into changes in myoelectrical activation patterns (EMG mapping). This allows a characterisation of the intramuscular co-ordination processes corresponding to the actual morphofunctional state of the investigated animals.

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

    PubMed

    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

  3. Super wavelet for sEMG signal extraction during dynamic fatiguing contractions.

    PubMed

    Al-Mulla, Mohamed R; Sepulveda, Francisco

    2015-01-01

    In this research an algorithm was developed to classify muscle fatigue content from dynamic contractions, by using a genetic algorithm (GA) and a pseudo-wavelet function. Fatiguing dynamic contractions of the biceps brachii were recorded using Surface Electromyography (sEMG) from thirteen subjects. Labelling the signal into two classes (Fatigue and Non-Fatigue) aided in the training and testing phase. The genetic algorithm was used to develop a pseudo-wavelet function that can optimally decompose the sEMG signal and classify the fatigue content of the signal. The evolved pseudo wavelet was tuned using the decomposition of 70% of the sEMG trials. 28 independent pseudo-wavelet evolution were run, after which the best run was selected and then tested on the remaining 30% of the trials to measure the classification performance. Results show that the evolved pseudo-wavelet improved the classification rate of muscle fatigue by 4.45 percentage points to 14.95 percentage points when compared to other standard wavelet functions (p<0.05), giving an average correct classification of 87.90%.

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

    PubMed

    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.

  5. Surface EMG in advanced hand prosthetics.

    PubMed

    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.

  6. The surface EMG-force relationship during isometric dorsiflexion in males and females.

    PubMed

    Lenhardt, S A; McIntosh, K C; Gabriel, D A

    2009-01-01

    This study compared the tibialis anterior (TA) surface electromyographic (sEMG) to force relationship for males and females. One-hundred participants (50 males and 50 females) performed three isometric contractions at 20, 40, 60, 80, and 100% of maximal voluntary contraction (MVC) in an apparatus designed to isolate the action of the dorsiflexors. The sEMG signal was amplified (1000x), band-pass filtered (10-500 Hz), and sampled at 2048 Hz. The load cell signal was low-pass filtered at 100 Hz and sampled at the same rate. Males were stronger than females (p < 0.05). However, there was no significant difference in the root-mean-square (RMS) amplitude of the sEMG signal between males and females (p < 0.05). Both groups exhibited a quadratic increase in the RMS across force levels (p < 0.05). The mean power frequency (MNF) of the sEMG signal for males was greater than for females (p < 0.05). Males and females exhibited a linear increase in MNF means up to 80% of MVC (p < 0.05). Between 80 and 100% MVC, the frequency values for the females plateaued while males showed a decrease (p < 0.05). The magnitude of the difference in MNF between males and females was consistent with the observation that males have greater type II muscle fiber diameters. In general, the pattern of means for RMS and MNF between males and females revealed no differences between groups in the sEMG-force relationship. We therefore conclude that there are no differences between males and females in the gradation of muscle force.

  7. Intramuscular and surface EMG power spectrum from dynamic and static contractions.

    PubMed

    Christensen, H; Søgaard, K; Jensen, B R; Finsen, L; Sjøgaard, G

    1995-03-01

    During sustained static contractions an increase in the root mean square (rms) amplitude and a decrease in mean power frequency (MPF), or median power frequency (MF) of the electromyographic (EMG) signal are indicators for the development of muscle fatigue. However, when studying dynamic contractions the interpretation of these variables has been questioned. Therefore, the purpose was to compare the EMG variables recorded from a non-fatigued muscle during a slow low level dynamic contraction to those during a static contraction of similar force level. Surface and intramuscular EMG registrations were obtained from the brachial biceps muscle during: (a) a static isotonic contraction, (b) a dynamic contraction and (c) a static anisotonic contraction. During contractions (a) and (b) the recruitment pattern was analysed using the precision decomposition method. No differences in rms, MPF or MF between the dynamic and static contractions or between the concentric and eccentric phase of the dynamic contraction were found. Furthermore 60% of the identified motor units were active both in the concentric and the eccentric phase. This indicates that motor control during a slow dynamic contraction at low force level does not influence the power spectrum. We suggest that in occupational studies a possible muscle fatigue development with time can be estimated using EMG recordings from the work tasks.

  8. Reproducibility of surface EMG in the human masseter and anterior temporalis muscle areas.

    PubMed

    Castroflorio, Tommaso; Icardi, Katia; Torsello, Ferruccio; Deregibus, Andrea; Debernardi, Cesare; Bracco, Pietro

    2005-04-01

    The aim of this study was to test the hypothesis that surface electromyography (sEMG) recordings, made at mandibular rest position from the masseter and temporalis anterior areas, are intra- and inter-session reproducible. A template was designed and built to permit the correct electrode placement from one session to the next session. A sample of 18 subjects was examined. Two groups, homogeneous for age, sex, and craniofacial morphology were selected. The first group included asymptomatic subjects with no signs or symptoms of temporomandibular joint dysfunction (TMD) and the second group included patients suffering from muscle-related TMD. Data were obtained from different sEMG recordings made at mandibular rest position in the same session and in different sessions, repositioning the electrodes using a template designed for that purpose. The electromyograph used in this, study is part of the EMG K6-I Win Diagnostic System. Results showed that reproducibility of sEMG signals from the masseter and anterior temporalis areas at mandibular rest position is possible.

  9. Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition

    PubMed Central

    Chen, Maoqi

    2016-01-01

    Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. Very recently, a progressive FastICA peel-off (PFP) framework has also been developed for high density surface EMG decomposition. In this study, the CKC and PFP methods were independently applied to decompose the same sets of high density surface EMG signals. Across 91 trials of 64-channel surface EMG signals recorded from the first dorsal interosseous (FDI) muscle of 9 neurologically intact subjects, there were a total of 1477 motor units identified from the two methods, including 969 common motor units. On average, 10.6 ± 4.3 common motor units were identified from each trial, which showed a very high matching rate of 97.85 ± 1.85% in their discharge instants. The high degree of agreement of common motor units from the CKC and the PFP processing provides supportive evidence of the decomposition accuracy for both methods. The different motor units obtained from each method also suggest that combination of the two methods may have the potential to further increase the decomposition yield. PMID:27642525

  10. Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition.

    PubMed

    Chen, Maoqi; Holobar, Ales; Zhang, Xu; Zhou, Ping

    2016-01-01

    Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. Very recently, a progressive FastICA peel-off (PFP) framework has also been developed for high density surface EMG decomposition. In this study, the CKC and PFP methods were independently applied to decompose the same sets of high density surface EMG signals. Across 91 trials of 64-channel surface EMG signals recorded from the first dorsal interosseous (FDI) muscle of 9 neurologically intact subjects, there were a total of 1477 motor units identified from the two methods, including 969 common motor units. On average, 10.6 ± 4.3 common motor units were identified from each trial, which showed a very high matching rate of 97.85 ± 1.85% in their discharge instants. The high degree of agreement of common motor units from the CKC and the PFP processing provides supportive evidence of the decomposition accuracy for both methods. The different motor units obtained from each method also suggest that combination of the two methods may have the potential to further increase the decomposition yield.

  11. Musculoskeletal model predicts multi-joint wrist and hand movement from limited EMG control signals.

    PubMed

    Crouch, Dustin L; He Huang

    2015-08-01

    Electromyography (EMG)-driven human-machine systems permit volitional control of external devices, including powered prosthetic arms. However, current control schemes are either non-intuitive to operate or lack robustness across different arm postures and dynamics, partly because these methods did not incorporate the full knowledge of biological movement production. In this study, we developed and evaluated a new musculoskeletal model to predict hand and wrist motion based on surface EMG signals. Kinematic and EMG data were collected from an able-bodied subject while performing wrist and metacarpophalangeal (MCP) joint movements with either a fixed or random speed in two static upper limb postures. A part of data collected in one posture was used to develop the model with four virtual muscles. Four parameters were optimized for each of four muscles in one posture. The model kinematic predictions were evaluated offline using the other part of the data recorded from both postures. Mean (±SD) RMS errors in predicting the joint movement were significantly lower at the MCP joint (10.1±2.5°) than at the wrist (23.5±5.2°) (p<;0.05). At both the wrist and MCP joints, the model predicted the timing and trend of joint movements reasonably well across postures and for both simple (fixed speed, single joint) and complex (random speed, simultaneous, multi-joint) movements. The results implied that our EMG-driven musculoskeletal model was promising for predicting simultaneous joint motions without significant posture and dynamics dependency. Additional engineering efforts are still needed to improve the musculoskeletal model for various human-machine interfacing applications.

  12. Knee angle-specific MVIC for triceps surae EMG signal normalization in weight and non weight-bearing conditions.

    PubMed

    Hébert-Losier, Kim; Holmberg, Hans-Christer

    2013-08-01

    Varying the degree of weight-bearing (WB) and/or knee flexion (KF) angle during a plantar-flexion maximal voluntary isometric contraction (MVIC) has been proposed to alter soleus and/or gastrocnemius medialis and lateralis activation. This study compared the surface EMG signals from the triceps surae of 27 men and 27 women during WB and non weight bearing (NWB) plantar-flexion MVICs performed at 0° and 45° of KF. The aim was to determine which condition was most effective at eliciting the greatest EMG signals from soleus, gastrocnemius medialis, and gastrocnemius lateralis, respectively, for subsequent use for the normalization of EMG signals. WB was more effective than NWB at eliciting the greatest signals from soleus (p=0.0021), but there was no difference with respect to gastrocnemius medialis and lateralis (p⩾0.2482). Although the greatest EMG signals during MVICs were more frequently elicited at 0° of KF from gastrocnemius medialis and lateralis, and at 45° from soleus (p<0.001); neither angle consistently captured peak gastrocnemius medialis, gastrocnemius lateralis or soleus activity. The present findings encourage more consistent use of WB plantar flexion MVICs for soleus normalization; confirm that both WB and NWB procedures can elicit peak gastrocnemius activity; and emphasize the fact that no single KF angle consistently evokes selective maximal activity of any individual triceps surae muscle.

  13. Examination of Hand Muscle Activation and Motor Unit Indices Derived from Surface EMG in Chronic Stroke

    PubMed Central

    Li, Xiaoyan; Liu, Jie; Li, Sheng; Wang, Ying-Chih

    2014-01-01

    In this study, we used muscle and motor unit indices, derived from convenient surface electromyography (EMG) measurements, for examination of paretic muscle changes post stroke. For 12 stroke subjects, compound muscle action potential and voluntary surface EMG signals were recorded from paretic and contralateral first dorsal interosseous, abductor pollicis brevis, and abductor digiti minimi muscles. Muscle activation index (AI), motor unit number index (MUNIX), and motor unit size index (MUSIX) were then calculated for each muscle. There was a significant AI reduction for all the three muscles in paretic side compared with contralateral side, providing an evidence of muscle activation deficiency after stroke. The hand MUNIX (defined by summing the values from the three muscles) was significantly reduced in paretic side compared with contralateral side, whereas the hand MUSIX was not significantly different. Furthermore, diverse changes in MUNIX and MUSIX were observed from the three muscles. A major feature of the present examinations is the primary reliance on surface EMG, which offers practical benefits because it is noninvasive, induces minimal discomfort and can be performed quickly. PMID:24967982

  14. Interpretation of surface EMGs in children with cerebral palsy: An initial study using a fuzzy expert system.

    PubMed

    Schmidt-Rohlfing, Bernhard; Bergamo, Ferdinand; Williams, Sybele; Erli, Hans J; Rau, Günther; Niethard, Fritz U; Disselhorst-Klug, Catherine

    2006-03-01

    Surface EMG detected simultaneously at different muscles has become an important tool for analysing the gait of children with cerebral palsy (CP), as it offers essential information about muscular coordination. However, the interpretation of surface EMG is a difficult task that assumes extensive knowledge and experience. As such, this noninvasive procedure is not frequently used in the general clinical routine. An Artificial Intelligence (AI) system for interpreting surface EMG signals and the resulting muscular coordination patterns could overcome these limitations. To support such interpretation, an expert system based on fuzzy inference methodology was developed. The knowledge-base of the system implemented 15 rules, from which the fuzzy inference methodology performs a prediction of the effectiveness of the muscular coordination during gait. Our aim was to assess the feasibility and value of such an expert system in clinical applications. Surface EMG signals were recorded from the tibialis anterior, soleus muscle, and gastrocnemius muscles of children with CP to assess muscular coordination patterns of ankle movement during gait. Nineteen children underwent 114 surface EMG measurements. Simultaneously, the gait cycles of each patient were determined using foot switches and videotapes. From the EMG signals, the effectiveness of the ankle movement was predicted by the expert system, and predictions were classified using a three-point ordinal scale. In 91 cases (80%), the clinical findings matched the predictions of the expert system. In 23 cases (20%) the predictions of the expert system differed from the clinical findings with 12 cases revealing worse and 11 cases revealing better results in comparison to the clinical findings. As this study is a first attempt to verify the feasibility and correctness of this expert system, the results are promising. Further study is required to assess the correlation with the kinematic data and to include the whole leg

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

    PubMed Central

    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

  16. EMG signal amplitude normalization technique in stretch-shortening cycle movements.

    PubMed

    Allison, G T; Marshall, R N; Singer, K P

    1993-01-01

    Analysis of functional movements using surface electromyography (EMG) often involves recording both eccentric and concentric muscle activity during a stretch-shorten cycle (SSC). The techniques used for amplitude normalization are varied and are independent of the type of muscle activity involved. The purpose of this study was: (i) to determine the effect of 11 amplitude normalization techniques on the coefficient of variation (CV) during the eccentric and concentric phases of the SSC; and (ii) to establish the effect of the normalization techniques on the EMG signal under variable load and velocity. The EMG signal of the biceps brachii of eight normal subjects was recorded under four SSC conditions and three levels of isometric contraction. The 11 derived normalization values were total rms, mean rms and peak rms (100 ms time constant) for the isometric contractions and the mean rms and peak rms values of the ensemble values for each set of isotonic contractions. Normalization using maximal voluntary isometric contractions (MVIC), irrespective of rms processing (total, mean or peak), demonstrated greater CV above the raw data for both muscle actions. Mean ensemble values and submaximal isometric recordings reduced the CV of concentric data. No amplitude normalization technique reduced the CV for eccentric data under loaded conditions. An ANOVA demonstrated significant (P < 0.01) main effects for load and velocity on concentric raw data and an interaction (P < 0.05) for raw eccentric data. No significant effects were demonstrated for changes in velocity when the data were normalized using mean rms values. The reduction of the CV should not be at the expense of true biological variance and current normalization techniques poorly serve the analysis of eccentric muscle activity during the SSC. Copyright © 1993. Published by Elsevier Ltd.

  17. Surface EMG based muscle activity analysis for aerobic cyclist.

    PubMed

    Balasubramanian, Venkatesh; Jayaraman, Srinivasan

    2009-01-01

    In this study, we determined the muscle activity of aerobic cyclist on biceps brachii medial, trapezius medial, latissimus dorsi medial, and erector spinae muscles bilaterally during 30 min of cycling. Thirteen male volunteers were chosen and placed in two groups (with and without low back pain (LBP)). Surface electromyography (sEMG) was recorded bilaterally from selected muscle groups for 30 min of cycling for each subject. Statistical tests were performed to determine the difference in fatigue, using mean power frequency difference. LBP group showed a significantly higher fatigue (p<0.05) in left biceps brachii medial when compared to the control group. High fatigue in the back muscles in the LBP group was not found; however, when linear regression was performed for these individuals, the data showed a possibility of worsening in their condition due to 30 min of cycling.

  18. Repeatability of surface EMG during gait in children

    PubMed Central

    Granata, Kevin P.; Padua, Darin A.; Abel, Mark F.

    2006-01-01

    Although mean amplitude and ON–OFF timing of muscle recruitment and electromyography (EMG) activation during gait is achieved by an age of six to eight years in normally developing children, recruitment dynamics illustrated by the shape of the EMG waveform may require continued developmental practice to achieve a stable pattern. Previous analyses have quantified the repeatability of the EMG waveform in adult subjects, but EMG variability for a pediatric population may be significantly different. The goal of this study was to quantify intra-session and inter-session variability in the phasic EMG waveform patterns from the lower limb muscles during self-selected speeds of walking in healthy-normal children for comparison with adult variability in gait EMG. The variance ratio quantifies the repeatability of the integrated EMG waveform shape in a group of normally-developing children. Results reveal that between-session EMG waveform variability were similar in adult and pediatric populations, but within-session variability for the children was approximately twice the published value for adults. Clinical implications of this pediatric EMG variability suggest cautious interpretation of data from limited trial samples or inter-session changes in performance of gait data. PMID:16274917

  19. Examination of Post-stroke Alteration in Motor Unit Firing Behavior Using High Density Surface EMG Decomposition

    PubMed Central

    Li, Xiaoyan; Holobar, Aleš; Gazzoni, Marco; Merletti, Roberto; Rymer, William Z.; Zhou, Ping

    2014-01-01

    Recent advances in high density surface electromyogram (EMG) decomposition have made it a feasible task to discriminate single motor unit activity from surface EMG interference patterns, thus providing a noninvasive approach for examination of motor unit control properties. In the current study we applied high density surface EMG recording and decomposition techniques to assess motor unit firing behavior alterations post-stroke. Surface EMG signals were collected using a 64-channel 2-dimensional electrode array from the paretic and contralateral first dorsal interosseous (FDI) muscles of nine hemiparetic stroke subjects at different isometric discrete contraction levels between 2 N to 10 N with a 2 N increment step. Motor unit firing rates were extracted through decomposition of the high density surface EMG signals, and compared between paretic and contralateral muscles. Across the nine tested subjects, paretic FDI muscles showed decreased motor unit firing rates compared with contralateral muscles at different contraction levels. Regression analysis indicated a linear relation between the mean motor unit firing rate and the muscle contraction level for both paretic and contralateral muscles (p < 0.001), with the former demonstrating a lower increment rate (0.32 pulses per second (pps)/N) compared with the latter (0.67 pps/N). The coefficient of variation (CoV, averaged over the contraction levels) of the motor unit firing rates for the paretic muscles (0.21 ± 0.012) was significantly higher than for the contralateral muscles (0.17 ± 0.014) (p < 0.05). This study provides direct evidence of motor unit firing behavior alterations post-stroke using surface EMG, which can be an important factor contributing to hemiparetic muscle weakness. PMID:25389239

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

    PubMed Central

    Song, Zhibin; Zhang, Songyuan

    2016-01-01

    Surface electromyography (sEMG) signals are closely related to the activation of human muscles and the motion of the human body, which can be used to estimate the dynamics of human limbs in the rehabilitation field. They also have the potential to be used in the application of bilateral rehabilitation, where hemiplegic patients can train their affected limbs following the motion of unaffected limbs via some rehabilitation devices. Traditional methods to process the sEMG focused on motion pattern recognition, namely, discrete patterns, which are not satisfactory for use in bilateral rehabilitation. In order to overcome this problem, in this paper, we built a relationship between sEMG signals and human motion in elbow flexion and extension on the sagittal plane. During the conducted experiments, four participants were required to perform elbow flexion and extension on the sagittal plane smoothly with only an inertia sensor in their hands, where forearm dynamics were not considered. In these circumstances, sEMG signals were weak compared to those with heavy loads or high acceleration. The contrastive experimental results show that continuous motion can also be obtained within an acceptable precision range. PMID:27775573

  1. Sensitivity of EMG-EMG coherence to detect the common oscillatory drive to hand muscles in young and older adults.

    PubMed

    Keenan, Kevin G; Massey, William V; Walters, Tygh J; Collins, Joseph D

    2012-05-01

    Multichannel surface electromyograms (EMGs) were used to examine the sensitivity of EMG-EMG coherence to infer changes in common oscillatory drive to hand muscles in young and older adults. Previous research has shown that measures of coherence calculated from different neurophysiological signals are influenced by the age of the subject, the visual feedback provided to the subject, and the task being performed. The change in the magnitude of EMG-EMG coherence across experimental conditions is often interpreted as a change in the oscillatory drive to motoneuron pools of a pair of muscles. However, signal processing (e.g., full-wave rectification) and electrode location are also reported to influence EMG-EMG coherence, which could decrease the sensitivity of EMG-EMG coherence to infer a change in common oscillatory drive to motoneurons. In this study, multichannel EMGs were used to compare EMG-EMG coherence in young (n = 11) and older (n = 10) adults during index finger abduction and pinch grip tasks performed at 2 and 3.5 N with a low and a high visual feedback gain. We found that, across all conditions, EMG-EMG coherence was influenced by electrode location (P < 0.001) but not by subject age, visual feedback gain, task, or signal processing. These results suggest that EMG-EMG coherence is most sensitive to electrode location. The results are discussed in terms of the potential issues related to inferring a common oscillatory drive to hand muscles with surface EMGs.

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

    PubMed

    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.

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

    ERIC Educational Resources Information Center

    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…

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

    PubMed Central

    Yang, Zhongliang; Chen, Yumiao

    2016-01-01

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

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

    PubMed

    Yang, Zhongliang; Chen, Yumiao

    2016-01-01

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

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

    PubMed Central

    Balouchestani, Mohammadreza; Krishnan, Sridhar

    2014-01-01

    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. PMID:25526357

  7. Effective low-power wearable wireless surface EMG sensor design based on analog-compressed sensing.

    PubMed

    Balouchestani, Mohammadreza; Krishnan, Sridhar

    2014-12-17

    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.

  8. Multichannel surface EMG based estimation of bilateral hand kinematics during movements at multiple degrees of freedom.

    PubMed

    Muceli, Silvia; Jiang, Ning; Farina, Dario

    2010-01-01

    The paper proposes a method to estimate wrist kinematics from surface EMG signals for proportional and simultaneous control of multiple degrees of freedom (DOFs). The approach is based on the concurrent detection of surface EMG signals from forearm muscles and hand kinematics of both limbs during mirrored bilateral movements in free space which involve the simultaneous activation of wrist flexion/extension, radial/ulnar deviation and forearm pronation/supination. The estimation was based on one multilayer perceptron (MLP) neural network for each DOF. The three MLPs were trained to estimate angular displacements corresponding to the three DOFs. The average coefficient of determination between the true and the predicted angular displacement was 82.7 ± 2.9% (80.9 ± 3.4%) for flexion/extension, 75.0 ± 3.8% (72.6 ± 9.4%) for radial/ulnar deviation, 76.6 ± 11.8% (75.1 ± 11.7%) for pronation/supination for the ipsi-lateral (contra-lateral) hand. The scheme represents a step forward towards the simultaneous control of DOFs and thus a more natural prosthetic control.

  9. EMG signals detection and processing for on-line control of functional electrical stimulation.

    PubMed

    Frigo, C; Ferrarin, M; Frasson, W; Pavan, E; Thorsen, R

    2000-10-01

    The surface EMG signal detected from voluntarily activated muscles can be used as a control signal for functional neuromuscular electrical stimulation. A proper positioning of the recording electrodes in relation to the stimulation electrodes, and a proper processing of the recorded signals is required to reduce the stimulus artefact and the non-voluntary contribution (M-wave). Six orientations and six locations of the recording electrodes were investigated in the present work. A comb filter (with and without a blanking windowing) was applied to remove the signal components synchronously correlated to the stimulus. An operative definition of the signal to noise ratio and an efficiency index were implemented. It resulted that when the recording electrodes were located within the two stimulation electrodes the best orientation was perpendicular to the longitudinal line. However the best absolute indexes were obtained when the recording electrodes were located externally of the stimulation electrodes, and in that case the best orientation was longitudinal. Concerning the filtering procedure, the use of a blanking window before the application of the comb filter, gave the best performance.

  10. Nonlinear Analysis of Surface EMG Time Series of Back Muscles

    NASA Astrophysics Data System (ADS)

    Dolton, Donald C.; Zurcher, Ulrich; Kaufman, Miron; Sung, Paul

    2004-10-01

    A nonlinear analysis of surface electromyography time series of subjects with and without low back pain is presented. The mean-square displacement and entropy shows anomalous diffusive behavior on intermediate time range 10 ms < t < 1 s. This behavior implies the presence of correlations in the signal. We discuss the shape of the power spectrum of the signal.

  11. Short latency hand movement classification based on surface EMG spectrogram with PCA.

    PubMed

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

    2016-08-01

    Hand gesture recognition from forearm surface electromyography (sEMG) is an active research field in the development of motor prosthesis. Studies have shown that classification accuracy and efficiency is highly dependent on the features extracted from the EMG. In this paper, we show that EMG spectrograms are a particularly effective feature for discriminating multiple classes of hand gesture when subjected to principal component analysis for dimensionality reduction. We tested our method on the Ninapro database which includes sEMG data (12 channels) of 40 subjects performing 50 different hand movements. Our results demonstrate improved classification accuracy (by ~10%) over purely time domain features for 50 different hand movements, including small finger movements and different levels of force exertion. Our method has also reduced the error rate (by ~12%) at the transition phase of gestures which could improve robustness of gesture recognition when continuous classification from sEMG is required.

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

    PubMed

    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.

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

    PubMed

    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

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

    PubMed Central

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

    2015-01-01

    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

  15. EMG and acceleration signal analysis for quantifying the effects of medication in Parkinson's disease.

    PubMed

    Rissanen, Saara M; Kankaanpaa, Markku; Tarvainen, Mika P; Nuutinen, Juho; Airaksinen, Olavi; Karjalainen, Pasi A

    2011-01-01

    Parkinson's disease (PD) is characterized by motor disabilities that can be alleviated reasonably with appropriate medication. However, there is a lack of objective methods for quantifying the efficacy of treatment in PD. We applied here an objective method for quantifying the effects of medication in PD using EMG and acceleration measurements and analysis. In the method, four signal features were calculated from the EMG and acceleration recordings of both sides of the body: the kurtosis and recurrence rate of EMG, and the amplitude and sample entropy of acceleration. Principal component approach was used for reducing the number of variables. EMG and acceleration data measured from nine PD patients were used for analysis. The patients were measured in four different medication conditions: with medication off, and two and three and four hours after taking the medication. The results showed that in eight patients the EMG recordings changed into less spiky and the acceleration recordings into more complex after taking the medication. A reverse phenomenon in the signal characteristics was observed in seven patients 3-4 hours after taking the medication. The results indicate that the presented method is potentially useful for quantifying objectively the effects of medication on the neuromuscular function in PD.

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

    PubMed

    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.

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

    PubMed Central

    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. PMID:28282410

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

    PubMed

    Subasi, Abdulhamit

    2013-06-01

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

  19. Wingate performance and surface EMG frequency variables are not affected by caffeine ingestion.

    PubMed

    Greer, Felicia; Morales, Jacobo; Coles, Michael

    2006-10-01

    The ergogenic effect of caffeine and its mechanism of action on short-term, high-intensity exercise are controversial. One proposed mechanism is caffeine's stimulatory effect on the central nervous system and thus, motor-unit excitation. The latter is non-invasively determined from surface electromyographic signal (EMG) frequency measures. The purpose of this study was to determine if power output and surface EMG frequency variables during high-intensity cycling were altered following caffeine ingestion. Eighteen recreationally active college males (mean +/- SD age, 21.5 +/- 1.8 y; height, 181.8 +/- 0.5 cm; body mass, 84.7 +/- 11.4 kg) performed the Wingate test (WG) after ingestion of gelatin capsules containing either placebo (PL; dextrose) or caffeine (CAFF; 5 mg/kg body mass). The trials were separated by 1 week and subjects were asked to withdraw from all caffeine-containing products for 48 h before each trial. From the resulting power-time records, peak power (PP; highest power output in 5 s), minimum power (MP; lowest power output in 5 s), and the percent decline in power (Pd) were calculated. Surface EMG records of the right vastus lateralis (VL) and the gastrocnemius (GA) muscles corresponding to the PP and MP periods were collected and used to determine the integrated electromyogram (IEMG), the mean (MNPF), and the median (MDPF) of the signal's power spectrum. A 2-way repeated measures analysis of variance (ANOVA) (treatment x time) was conducted to determine the effect of caffeine on these variables across levels of time. Caffeine ingestion had no effect on PP (PL, 1049 +/- 192 W; CAFF, 1098 +/- 198 W), MP (PL, 762 +/- 104 W; CAFF, 802 +/- 124 W), or the Pd (PL, 47% +/- 8.9%; CAFF, 48.2% +/- 7.3%) compared with the placebo. For both muscles, MNPF and MDPF diminished significantly (p < 0.001) across time and to a similar degree in both the CAFF and PL trials. Regardless of muscle, CAFF had no effect on the percent change in IEMG from the first 5 s to the

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

    PubMed Central

    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

  1. A comparative study of surface EMG classification by fuzzy relevance vector machine and fuzzy support vector machine.

    PubMed

    Xie, Hong-Bo; Huang, Hu; Wu, Jianhua; Liu, Lei

    2015-02-01

    We present a multiclass fuzzy relevance vector machine (FRVM) learning mechanism and evaluate its performance to classify multiple hand motions using surface electromyographic (sEMG) signals. The relevance vector machine (RVM) is a sparse Bayesian kernel method which avoids some limitations of the support vector machine (SVM). However, RVM still suffers the difficulty of possible unclassifiable regions in multiclass problems. We propose two fuzzy membership function-based FRVM algorithms to solve such problems, based on experiments conducted on seven healthy subjects and two amputees with six hand motions. Two feature sets, namely, AR model coefficients and room mean square value (AR-RMS), and wavelet transform (WT) features, are extracted from the recorded sEMG signals. Fuzzy support vector machine (FSVM) analysis was also conducted for wide comparison in terms of accuracy, sparsity, training and testing time, as well as the effect of training sample sizes. FRVM yielded comparable classification accuracy with dramatically fewer support vectors in comparison with FSVM. Furthermore, the processing delay of FRVM was much less than that of FSVM, whilst training time of FSVM much faster than FRVM. The results indicate that FRVM classifier trained using sufficient samples can achieve comparable generalization capability as FSVM with significant sparsity in multi-channel sEMG classification, which is more suitable for sEMG-based real-time control applications.

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

    PubMed

    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.

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

    PubMed

    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, p<0.001). Examination of force factor on the surface EMG 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

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

    PubMed

    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 < 0.007) for all performance metrics: coefficient of determination (R(2)), Pearson correlation coefficient (PCC), and root mean square error (RMSE). The performance of surface 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.

  5. Clinical relevance of surface EMG of the masticatory muscles. (Part 1): Resting activity, maximal and submaximal voluntary contraction, symmetry of EMG activity.

    PubMed

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

    2012-01-01

    Based on a comprehensive computerized literature search supplemented by a specific manual search of the literature, the present review article focuses on concrete aspects of the application of surface electromyography (EMG) for evaluation of the masticatory muscles in general and of the masseter and anterior temporal muscles in particular, and presents the current base of knowledge on the clinical relevance of surface EMG in dental applications. In the first stage of the review, publications from the year 2000 or later reporting the results of controlled clinical trials (randomized as far as available) of patients with craniomandibular or temporomandibular disorders (TMD) were analyzed. Data from the selected publications were systematically compiled and divided into subject areas as follows: Resting activity, maximal and sub-maximal voluntary contraction, symmetry of EMG activity, and fatigue effects; EMG activity during mastication, factors (including pain) that affect EMG activity, and the impact of adjusting static and dynamic occlusal relationships; Effects of occlusal splints and other occlusal treatments. Surface electromyography is in principle a suitable tool for neuromuscular function analysis in the field of dentistry. If used according to the specific recommendations and in conjunction with a thorough and conscientious clinical history and physical examination, surface EMG measurements can provide objective, documentable, valid, and reproducible data on the functional condition of the masticatory muscles of an individual patient.

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

    PubMed Central

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

    2016-01-01

    This paper introduces a new method for data analysis of animal muscle activation during locomotion. 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. Furthermore, it provides new opportunities for analysis and exploration of sEMG data by using the resulting Gaussian modes as atomic building blocks for a hierarchical clustering. In our experiments, composite peak models representing the general activation pattern per sensor location (one sensor on the long back muscle, three sensors on the gluteus muscle on each body side) were identified per individual for all 14 horses during walk and trot in the present study. Hereby we show the applicability of the method to identify composite peak models, which describe activation of different muscles throughout cycles of locomotion. PMID:27362752

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

    PubMed

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Nonlinear parameters of surface EMG in schizophrenia patients depend on kind of antipsychotic therapy

    PubMed Central

    Meigal, Alexander Yu.; Miroshnichenko, German G.; Kuzmina, Anna P.; Rissanen, Saara M.; Georgiadis, Stefanos D.; Karjalainen, Pasi A.

    2015-01-01

    We compared a set of surface EMG (sEMG) parameters in several groups of schizophrenia (SZ, n = 74) patients and healthy controls (n = 11) and coupled them with the clinical data. sEMG records were quantified with spectral, mutual information (MI) based and recurrence quantification analysis (RQA) parameters, and with approximate and sample entropies (ApEn and SampEn). Psychotic deterioration was estimated with Positive and Negative Syndrome Scale (PANSS) and with the positive subscale of PANSS. Neuroleptic-induced parkinsonism (NIP) motor symptoms were estimated with Simpson-Angus Scale (SAS). Dyskinesia was measured with Abnormal Involuntary Movement Scale (AIMS). We found that there was no difference in values of sEMG parameters between healthy controls and drug-naïve SZ patients. The most specific group was formed of SZ patients who were administered both typical and atypical antipsychotics (AP). Their sEMG parameters were significantly different from those of SZ patients taking either typical or atypical AP or taking no AP. This may represent a kind of synergistic effect of these two classes of AP. For the clinical data we found that PANSS, SAS, and AIMS were not correlated to any of the sEMG parameters. Conclusion: with nonlinear parameters of sEMG it is possible to reveal NIP in SZ patients, and it may help to discriminate between different clinical groups of SZ patients. Combined typical and atypical AP therapy has stronger effect on sEMG than a therapy with AP of only one class. PMID:26217236

  10. EMG versus torque control of human-machine systems: equalizing control signal variability does not equalize error or uncertainty.

    PubMed

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

    2016-08-25

    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.

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

    PubMed

    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.

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

    PubMed

    Ngeo, Jimson; Tamei, Tomoya; Shibata, Tomohiro

    2014-01-01

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

  13. Improving surface EMG burst detection in infrahyoid muscles during swallowing using digital filters and discrete wavelet analysis.

    PubMed

    Restrepo-Agudelo, Sebastian; Roldan-Vasco, Sebastian; Ramirez-Arbelaez, Lina; Cadavid-Arboleda, Santiago; Perez-Giraldo, Estefania; Orozco-Duque, Andres

    2017-08-01

    The visual inspection is a widely used method for evaluating the surface electromyographic signal (sEMG) during deglutition, a process highly dependent of the examiners expertise. It is desirable to have a less subjective and automated technique to improve the onset detection in swallowing related muscles, which have a low signal-to-noise ratio. In this work, we acquired sEMG measured in infrahyoid muscles with high baseline noise of ten healthy adults during water swallowing tasks. Two methods were applied to find the combination of cutoff frequencies that achieve the most accurate onset detection: discrete wavelet decomposition based method and fixed steps variations of low and high cutoff frequencies of a digital bandpass filter. Teager-Kaiser Energy operator, root mean square and simple threshold method were applied for both techniques. Results show a narrowing of the effective bandwidth vs. the literature recommended parameters for sEMG acquisition. Both level 3 decomposition with mother wavelet db4 and bandpass filter with cutoff frequencies between 130 and 180Hz were optimal for onset detection in infrahyoid muscles. The proposed methodologies recognized the onset time with predictive power above 0.95, that is similar to previous findings but in larger and more superficial muscles in limbs. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Effect of experimental jaw-muscle pain on the spatial distribution of surface EMG activity of the human masseter muscle during tooth clenching.

    PubMed

    Castroflorio, T; Falla, D; Wang, K; Svensson, P; Farina, D

    2012-02-01

    This study tested the hypothesis that painful injections of glutamate into the human masseter muscle differentially affect the distribution of the electromyographic (EMG) activity in the masseter muscle at rest and during tooth clenching. Surface EMG signals were recorded bilaterally from the superficial masseter of nine healthy men with a grid of 32 electrodes, before and after intramuscular injection of glutamate or isotonic saline, during rest and isometric contractions at 20%, 40%, 60% and 80% of the maximal voluntary bite force. Intramuscular injection of glutamate evoked moderate pain (0-10 visual analogue scale: 6·4 ± 1·4), with sensory-discriminative characteristics of the perceived pain, evaluated with the use of the McGill Pain Questionnaire (MPQ), similar to those previously reported for patients with temporomandibular disorders. There was no effect of the glutamate injection on EMG amplitude during rest, whereas during tooth clenching, the spatial distribution of the masseter EMG activity on both sides was more uniform in the painful condition compared to the control condition. Moreover, the overall EMG amplitude decreased on both sides during the more forceful tooth clenching following glutamate injection. In conclusion, a unilateral painful stimulation was associated with a bilateral inhibition of the masseter muscles during tooth clenching which resulted in a more uniform distribution of EMG activity. © 2011 Blackwell Publishing Ltd.

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

    ERIC Educational Resources Information Center

    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. THREE-DIMENSIONAL INNERVATION ZONE IMAGING FROM MULTI-CHANNEL SURFACE EMG RECORDINGS

    PubMed Central

    LIU, YANG; NING, YONG; LI, SHENG; ZHOU, PING; RYMER, WILLIAM Z.; ZHANG, YINGCHUN

    2017-01-01

    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 3-dimensional 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 motor unit 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. PMID:26160432

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

    ERIC Educational Resources Information Center

    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…

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

    PubMed

    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.

  19. Relationship between EMG signals and force in human vastus lateralis muscle using multiple bipolar wire electrodes.

    PubMed

    Onishi, H; Yagi, R; Akasaka, K; Momose, K; Ihashi, K; Handa, Y

    2000-02-01

    This paper describes the relationship between knee extension force and EMG signals detected by multiple bipolar wire electrodes inserted into the human vastus lateralis muscle under isometric conditions. Six healthy male volunteers participated in this study. Eight pairs of bipolar wire electrodes were inserted into the right vastus lateralis muscle and the EMG data were simultaneously detected and analyzed. The EMG raw data and individual force-IEMG relations were influenced by the location of the electrode inserted into the muscle. The force and IEMG relationship averaged across subjects detected from the eight electrodes, however, showed almost the same linear correlation in spite of different electrode locations. No linear correlation was observed between MdF and the knee extension force. This result suggests that, if all of the muscle fibers participate in the same action at the same time, the averaged normalized IEMG from any places using wire electrodes could reflect the total activities of that muscle even if the muscle is large.

  20. The effect of 630-nm light stimulation on the sEMG signal of forearm muscle

    NASA Astrophysics Data System (ADS)

    Yang, Dan D.; Hou, W. Sheng; Wu, Xiao Y.; Zheng, Xiao L.; Zheng, Jun; Jiang, Ying T.

    2010-11-01

    This study aimed to explore if the red light irradiation can affect the electrophysiology performance of flexor digitorum superficialis (FDS) and fatigue recovery. Four healthy volunteers were randomly divided into two groups. In the designed force-tracking tasks, all subjects performed the four fingertip isometric force production except thumb with a load of 30% of the maximum voluntary contraction (MVC) force until exhaustion. Subsequently, for the red light group, red light irradiation (640 nm wavelength, 0.23J/cm2, 20 min) was used on the right forearm; for the control group, the subjects relaxed without red light irradiation. Then subjects were required to perform fatigue trail again, and sEMG signal was collected simultaneously from FDS during finger force production. Average rectified value (ARV) and median frequency (MF) of sEMG were calculated. Compared to the control group, the red light irradiation induced more smoother value of ARV between 30% and 40%, and the value of MF was obviously large and smooth. The above electrophysiological markers indicated that recovery from muscle fatigue may be positively affected by the red light irradiation, suggesting that sEMG would become a power tool for exploring the effect of red light irradiation on local muscle fatigue.

  1. A preliminary investigation of reproducibility of EMG signals during daytime masticatory muscle activity using a portable EMG logging device.

    PubMed

    Omoto, Katsuhiro; Shigemoto, Shuji; Suzuki, Yoshitaka; Nakamura, Mayumi; Okura, Kazuo; Nishigawa, Keisuke; Goto, Nami; Rodis, Omar Marianito Maningo; Matsuka, Yoshizo

    2015-08-01

    Continuous parafunctional masseter muscle activities (MMA) that are associated with daytime bruxism have been suspected to be one of the main pathoetiology for orofacial pain. The purpose of this study was to examine the long-term stability and reliability of daytime EMG measurement of MMA using a portable device (Actiwave; CamNtech Ltd). Daytime masseter muscle EMG of five subjects were recorded for four days in their normal living environment. There was no significant time dependent effect on EMG amplitude during recording period. A total of 4923 MMA events were detected in all analysis periods (129.4h) and classified into phasic type (1209 events, 24.6%), tonic type (1759 events, 37.0%), and mixed type (1377 events, 28.0%). There was no significant difference in the number of occurrence among three MMA types. With respect to the duration and peak MMA, there were significant differences among three MMA types. The result of this study indicated that Actiwave can be used to measure MMA events during daytime with high stability and reliability under the normal living environment and it was suspected that parafunctional habits may be associated with the occurrence patterns of MMA during daytime.

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

    PubMed

    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 < 0.001). In a multivariate regression model, surface EMG activity was significantly associated with RBD severity (p < 0.001) after adjustment for age, PD disease duration, PD severity and co-morbid sleep abnormalities. Surface EMG activity during 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.

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

    NASA Astrophysics Data System (ADS)

    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.

  4. Between-day reliability of triceps surae responses to standing perturbations in people post-stroke and healthy controls: A high-density surface EMG investigation.

    PubMed

    Gallina, A; Pollock, C L; Vieira, T M; Ivanova, T D; Garland, S J

    2016-02-01

    The reliability of triceps surae electromyographic responses to standing perturbations in people after stroke and healthy controls is unknown. High-Density surface Electromyography (HDsEMG) is a technique that records electromyographic signals from different locations over a muscle, overcoming limitations of traditional surface EMG such as between-day differences in electrode placement. In this study, HDsEMG was used to measure responses from soleus (SOL, 18 channels) and medial and lateral gastrocnemius (MG and LG, 16 channels each) in 10 people after stroke and 10 controls. Timing and amplitude of the response were estimated for each channel of the grids. Intraclass Correlation Coefficient (ICC) and normalized Standard Error of Measurement (SEM%) were calculated for each channel individually (single-channel configuration) and on the median of each grid (all-channels configuration). Both timing (single-channel: ICC=0.75-0.96, SEM%=5.0-9.1; all-channels: ICC=0.85-0.97; SEM%=3.5-6.2%) and amplitude (single-channel: ICC=0.60-0.91, SEM%=25.1-46.6; ICC=0.73-0.95, SEM%=19.3-42.1) showed good-to-excellent reliability. HDsEMG provides reliable estimates of EMG responses to perturbations both in individuals after stroke and in healthy controls; reliability was marginally better for the all-channels compared to the single-channel configuration.

  5. Electromyography (EMG) signal recognition using combined discrete wavelet transform based adaptive neuro-fuzzy inference systems (ANFIS)

    NASA Astrophysics Data System (ADS)

    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.

  6. Outlier detection in high-density surface electromyographic signals.

    PubMed

    Marateb, Hamid R; Rojas-Martínez, Monica; Mansourian, Marjan; Merletti, Roberto; Villanueva, Miguel A Mañanas

    2012-01-01

    Recently developed techniques allow the analysis of surface EMG in multiple locations over the skin surface (high-density surface electromyography, HDsEMG). The detected signal includes information from a greater proportion of the muscle of interest than conventional clinical EMG. However, recording with many electrodes simultaneously often implies bad-contacts, which introduce large power-line interference in the corresponding channels, and short-circuits that cause near-zero single differential signals when using gel. Such signals are called 'outliers' in data mining. In this work, outlier detection (focusing on bad contacts) is discussed for monopolar HDsEMG signals and a new method is proposed to identify 'bad' channels. The overall performance of this method was tested using the agreement rate against three experts' opinions. Three other outlier detection methods were used for comparison. The training and test sets for such methods were selected from HDsEMG signals recorded in Triceps and Biceps Brachii in the upper arm and Brachioradialis, Anconeus, and Pronator Teres in the forearm. The sensitivity and specificity of this algorithm were, respectively, 96.9 ± 6.2 and 96.4 ± 2.5 in percent in the test set (signals registered with twenty 2D electrode arrays corresponding to a total of 2322 channels), showing that this method is promising.

  7. Reconstructing surface EMG from scalp EEG during myoelectric control of a closed looped prosthetic device.

    PubMed

    Paek, Andrew Y; Brown, Jeremy D; Gillespie, R Brent; O'Malley, Marcia K; Shewokis, Patricia A; Contreras-Vidal, Jose L

    2013-01-01

    In this study, seven able-bodied human subjects controlled a robotic gripper with surface electromyography (sEMG) activity from the biceps. While subjects controlled the gripper, they felt the forces measured by the robotic gripper through an exoskeleton fitted on their non-dominant left arm. Subjects were instructed to identify objects with the force feedback provided by the exoskeleton. While subjects operated the robotic gripper, scalp electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) were recorded. We developed neural decoders that used scalp EEG to reconstruct the sEMG used to control the robotic gripper. The neural decoders used a genetic algorithm embedded in a linear model with memory to reconstruct the sEMG from a plurality of EEG channels. The performance of the decoders, measured with Pearson correlation coefficients (median r-value = 0.59, maximum r-value = 0.91) was found to be comparable to previous studies that reconstructed sEMG linear envelopes from neural activity recorded with invasive techniques. These results show the feasibility of developing EEG-based neural interfaces that in turn could be used to control a robotic device.

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

    PubMed

    Geethanjali, P; Ray, K K

    2011-09-01

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

  9. Surface Electromyography Signal Processing and Classification Techniques

    PubMed Central

    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

  10. The influence of wrist posture on the time and frequency EMG signal measures of forearm muscles.

    PubMed

    Roman-Liu, Danuta; Bartuzi, Paweł

    2013-03-01

    This study investigates how altering wrist posture influences the relationship between the time and frequency measures of the electromyography (EMG) signal of extensor digitorum communis (EDC) and flexor carpi ulnaris (FCU). Thirteen participants exerted handgrip force related to maximum voluntary contraction (MVC) in four tests: 20%MVC and 50%MVC in neutral wrist posture and 20%MVC in full wrist flexion and extension. EMG measurements from EDC and FCU were used to calculate normalized values of amplitude (nRMS) and mean and median frequency of the power spectrum (nMPF, nMF). During muscle shortening (wrist flexion for FCU and wrist extension for EDC) nRMS was approximately twofold higher than in neutral posture for FCU and fourfold for EDC. All measures obtained at 20%MVC in neutral posture were significantly different from 20%MVC in wrist flexion for FCU and 20%MVC in wrist extension for EDC (p<0.05). Differences between 50%MVC and 20%MVC at neutral posture (nRMS) were significant for both muscles, although in nMPF and nMF for EDC only. Muscle shortening changed the pattern of statistical significance when the time and frequency domain measures were compared, whereas muscle lengthening did not. It can be concluded that muscle shortening caused by altering wrist posture influences the relationship between the time and frequency measures in both muscles. This suggests that in studies using EMG in different wrist postures, changes in the relationship between the time and the frequency measures should be considered.

  11. Real-time muscle state estimation from EMG signals during isometric contractions using Kalman filters.

    PubMed

    Menegaldo, Luciano L

    2017-08-01

    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.

  12. The effect of single-pulse transcranial magnetic stimulation and peripheral nerve stimulation on complexity of EMG signal: fractal analysis.

    PubMed

    Cukic, M; Oommen, J; Mutavdzic, D; Jorgovanovic, N; Ljubisavljevic, M

    2013-07-01

    The aim of this study was to examine whether single-pulse transcranial magnetic stimulation (spTMS) affects the pattern of corticospinal activity once voluntary drive has been restored after spTMS-induced EMG silence. We used fractal dimension (FD) to explore the 'complexity' of the electromyography (EMG) signal, and median frequency of the spectra (MDF) to examine changes in EMG spectral characteristics. FD and MDF of the raw EMG epochs immediately before were compared with those obtained from epochs after the EMG silence. Changes in FD and MDF after spTMS were examined with three levels of muscle contraction corresponding to weak (20-40%), moderate (40-60%) and strong (60-80% of maximal voluntary contraction) and three intensities of stimulation set at 10, 20 and 30% above the resting motor threshold. FD was calculated using the Higuchi fractal dimension algorithm. Finally, to discern the origin of FD changes between the CNS and muscle, we compared the effects of spTMS with the effects of peripheral nerve stimulation (PNS) on FD and MDF. The results show that spTMS induced significant decrease in both FD and MDF of EMG signal after stimulation. PNS did not have any significant effects on FD nor MDF. Changes in TMS intensity did not have any significant effect on FD or MDF after stimulation nor had the strength of muscle contraction. However, increase in contraction strength decreased FD before stimulation but only between weak and moderate contraction. The results suggest that the effects of spTMS on corticospinal activity, underlying voluntary motor output, outlast the TMS stimulus. It appears that the complexity of the EMG signal is reduced after spTMS, suggesting that TMS alters the dynamics of the ongoing corticospinal activity most likely temporarily synchronizing the neural network activity. Further studies are needed to confirm whether observed changes after TMS occur at the cortical level.

  13. EMG signal morphology and kinematic parameters in essential tremor and Parkinson's disease patients.

    PubMed

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

    2014-04-01

    The aim of this work was to differentiate patients with essential tremor from patients with Parkinson's disease. Electromyographic data from biceps brachii muscles and kinematic data from arms during isometric tension of the arms were measured from 17 patients with essential tremor, 35 patients with Parkinson's disease and 40 healthy controls. The EMG signals were divided to smaller segments from which histograms were calculated. The histogram shape was analysed with a feature dimension reduction method, the principal component analysis, and the shape parameters were used to differentiate between different subject groups. Three parameters, RMS-amplitude, sample entropy and peak frequency were determined from the kinematic measurements of the arms. The height and the side differences of the histogram were the most effective for differentiating between essential tremor and Parkinson's disease groups. The histogram parameters of patients with essential tremor were more similar to patients with Parkinson's disease than healthy controls. With this method it was possible to discriminate 13/17 patients with essential tremor from 26/35 patients with Parkinson's disease and 14/17 patients with essential tremor from 29/40 healthy controls. The kinematic parameters of patients with essential tremor were closer to parameters of patients with Parkinson's disease compared to healthy controls. Combining EMG and kinematic analysis did not increase discrimination efficiency but provided more reliability to the discrimination of subject groups.

  14. Biomechanical correlates of surface electromyography signals obtained during swallowing by healthy adults.

    PubMed

    Crary, Michael A; Carnaby Mann, Giselle D; Groher, Michael E

    2006-02-01

    The purpose of this study was to describe biomechanical correlates of the surface electromyographic signal obtained during swallowing by healthy adult volunteers. Seventeen healthy adults were evaluated with simultaneous videofluoroscopy and surface electromyography (sEMG) while swallowing 5 mL of liquid barium sulfate. Three biomechanical swallowing events were analyzed: hyoid elevation, pharyngeal constriction, and opening-closing of the pharyngoesophageal segment. For each biomechanical event and from the sEMG signal, the authors identified onset, peak, and offset time points. From these points, duration measures were calculated. Means and 95% confidence intervals were calculated for each measure. Subsequently, correlations were evaluated between timing aspects of the sEMG traces and each biomechanical event. Swallow onset in the sEMG signal preceded the onset of all biomechanical events. All biomechanical events demonstrated a strong correspondence to the sEMG signal. The strongest relationship was between hyoid elevation-anterior displacement and the sEMG signal. These results suggest that the sEMG signal is a useful indicator of major biomechanical events in the swallow. Future studies should address the impact of age and disease processes, as well as bolus characteristics, on the biomechanical correlates of sEMG signals obtained during swallowing.

  15. EMG responses to maintain stance during multidirectional surface translations

    NASA Technical Reports Server (NTRS)

    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

  16. EMG responses to maintain stance during multidirectional surface translations

    NASA Technical Reports Server (NTRS)

    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

  17. Anatomic basis for individuated surface EMG and homogeneous electrostimulation with neuroprostheses of the extensor digitorum communis.

    PubMed

    Leijnse, J N A L; Carter, S; Gupta, A; McCabe, S

    2008-07-01

    The extensor digitorum communis (ED) is generally regarded as a fairly undiversified muscle that gives extensor tendons to all fingers. Some fine wire electromyographic (EMG) investigations have been carried out to study individuation of the muscle parts to the different fingers. However, individuated surface EMG of the ED has not been investigated. This study analyses the anatomy of the ED muscle parts to the different fingers in detail and proposes optimal locations for surface or indwelling electrodes for individuated EMG and for electrostimulation with neuroprostheses. The dissections show that the ED arises from extensive origin tendons (OT), which originate at the lateral epicondyle and reach far in the forearm. The ED OT is V-shaped with shorter central tendon fibers but with a long radial and an even longer ulnar slip. The ED parts to the individual fingers consistently arise from distinct OT locations: the ED3 (medius) arises proximally, the ED2 (index) from the radial slip distal to ED3, the ED4 (ring finger) from the ulnar slip distal to ED3, and the ED5 (to ring/little finger) from the ulnar slip distal to ED4. This lengthwise widely spaced arrangement of ED parts compensates to some degree for the narrow ED width and suggests that ED parts should be individually assessable by indwelling and even by surface EMG electrodes, albeit in the latter case with variable mutual cross-talk. Conversely, the anatomic spacing of ED parts warrants that electromyographic stimulation with neuroprostheses by a single implanted electrode cannot likely homogeneously activate all ED parts.

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

    PubMed

    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%.

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

    NASA Astrophysics Data System (ADS)

    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.

  20. Surface EMG of the masticatory muscles (Part 3): Impact of changes to the dynamic occlusion.

    PubMed

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

    2013-01-01

    The third part of this literature review on the clinical relevance of surface electromyography (EMG) of the masticatory muscles summarizes the results of clinical studies in patients with temporomandibular disorders (TMD), preferably randomized controlled trials, examining the impact of changes to the dynamic occlusion. Clenching in left and right laterotrusive positions results in decrease in EMG activity of masseter and temporalis muscles on both working and non-working side. Masseter muscle exhibits largely uniform bilateral activity in laterotrusive positions, independent of canine guidance or group function with and without non-working side contacts. There is a dominance of temporalis muscle activity on the working side and, in case of posterior contacts and balancing contacts, temporalis muscle activity increases and changes from an unilateral to a symmetrical pattern.

  1. The effects of elevated body temperature on the complexity of the diaphragm EMG signals during maturation.

    PubMed

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

    2009-04-01

    In this paper, we examine the effect of elevated body temperature on the complexity of the diaphragm electromyography (EMGdia), the output of the respiratory neural network--using the approximate entropy method. The diaphragm EMG, EEG, EOG as well as other physiological signals (tracheal pressure, blood pressure and respiratory volume) in chronically instrumented rats were recorded at two postnatal ages: 25-35 days age (juvenile, n = 5) and 36-44 days age (early adult, n = 6) groups during control (36-37 degrees C), mild elevated body temperature (38 degrees C) and severe elevated body temperature (39-40 degrees C). Three to five trials of the recordings were performed at normal body temperature before raising the animal's core temperature by 1-4 degrees C with an electric heating pad. At the elevated temperature, another 3-5 trials were performed. Finally, the animal was cooled to the original temperature, and trials were again repeated. Complexity values of the diaphragm EMG signal were estimated and evaluated using the approximate entropy method (ApEn) over the ten consecutive breaths. Our results suggested that the mean approximate entropy values for the juvenile age group were 1.01 +/- 0.01 (standard error) during control, 0.91 +/- 0.02 during mild elevated body temperature and 0.81 +/- 0.02 during severe elevated body temperature. For the early adult age group, these values were 0.94 +/- 0.01 during control, 0.93 +/- 0.01 during mild elevated body temperature and 0.92 +/- 0.01 during severe elevated body temperature. Our results show that the complexity values and the durations of the diaphragm EMG (EMGdia) were significantly decreased when the elevated body temperature was shifted from control or mild to severe body temperature (p < 0.05) for the juvenile age group. However, for the early adult age group, an increase in body temperature slightly reduced the complexity measures and the duration of the EMGdia. But, these changes were not statistically

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

    PubMed

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

    2013-01-01

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

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

    PubMed Central

    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. PMID:28744189

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

    PubMed

    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.

  5. Comparison of algorithms to quantify muscle fatigue in upper limb muscles based on sEMG signals.

    PubMed

    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.

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

    PubMed

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

    2017-08-31

    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

  7. Robust decomposition of single-channel intramuscular EMG signals at low force levels

    NASA Astrophysics Data System (ADS)

    Marateb, Hamid R.; Muceli, Silvia; McGill, Kevin C.; Merletti, Roberto; Farina, Dario

    2011-10-01

    This paper presents a density-based method to automatically decompose single-channel intramuscular electromyogram (EMG) signals into their component motor unit action potential (MUAP) trains. In contrast to most previous decomposition methods, which require pre-setting and (or) tuning of multiple parameters, the proposed method takes advantage of the data-dependent strategies in the pattern recognition procedures. In this method, outliers (superpositions) are excluded prior to classification and MUAP templates are identified by an adaptive density-based clustering procedure. MUAP trains are then identified by a novel density-based classifier that incorporates MUAP shape and discharge time information. MUAP trains are merged by a fuzzy system that incorporates expert human knowledge. Finally, superimpositions are resolved to fill the gaps in the MUAP trains. The proposed decomposition algorithm has been experimentally tested on signals from low-force (<=30% maximal) isometric contractions of the vastus medialis obliquus, vastus lateralis, biceps femoris long-head and tibialis anterior muscles. Comparison with expert manual decomposition that had been verified using a rigorous statistical analysis showed that the algorithm identified 80% of the total 229 motor unit trains with an accuracy greater than 90%. The algorithm is robust and accurate, and therefore it is a promising new tool for decomposing single-channel multi-unit signals.

  8. Simultaneous powerline interference and baseline wander removal from ECG and EMG signals by sinusoidal modeling.

    PubMed

    Zivanovic, Miroslav; González-Izal, Miriam

    2013-10-01

    We present a compact approach to joint modeling of powerline interference (PLI) and baseline wonder (BW) for denoising of biopotential signals. Both PLI and BW are modeled by a set of harmonically related sinusoids modulated by low-order time polynomials. The sinusoids account on the harmonicity and mean instantaneous frequency of the PLI in the analysis window, while the polynomials capture the frequency and amplitude deviations from their nominal values and characterize the BW at the same time. The resulting model is linear-in-parameters and the solution to the corresponding linear system is estimated in a simple and efficient way through linear least-squares. The proposed modeling method was evaluated on real electrocardiographic (ECG) and electromyographic (EMG) signals against three reference methods for different analysis scenarios. The comparative study suggests that the proposed method outperforms the reference methods in terms of residual interference energy in the denoised biopotential signals. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

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

    PubMed

    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.

  10. EMG-torque Relation in Chronic Stroke: A Novel EMG Complexity Representation with A Linear Electrode Array.

    PubMed

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

    2016-11-08

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

  11. Short-latency changes in voice F0 and neck surface EMG induced by mechanical perturbations of the larynx during sustained vowel phonation.

    PubMed

    Sapir, S; Baker, K K; Larson, C R; Ramig, L O

    2000-02-01

    Nineteen healthy young adult males with normal voice and speech attempted to sustain the vowel /u/ at a constant pitch (target: 180 Hz) and a constant and comfortable loudness level while receiving a sudden mechanical perturbation to the larynx (thyroid prominence) via a servo-controlled probe. The probe moved toward or away from the larynx in a ramp-and-hold fashion (3.3-mm displacement, 0.7 N force, 20-ms rise time, 250-ms duration) as the subjects attempted to maintain a constant probe-larynx pressure. Eighty stimuli were applied in each direction, one stimulus per phonation. Pairs of surface electromyography (EMG) electrodes were attached to the skin of the anterior neck over laryngeal, infralaryngeal, and supralaryngeal areas. The rectified EMG signals, the voltage analog of the voice fundamental frequency (VAF0), and the voltage analog of the probe displacement were digitized and signal-averaged relative to the onset of the stimulus. Sudden perturbation of the larynx induced an instantaneous decrease or increase in VAF0, depending on the direction of the probe's movement, and a short-latency increase in the EMG (30-35 ms) and VAF0 (55-65 ms). We argue that the instantaneous VAF0 change was related to a mechanical effect, and the short-latency VAF0 and EMG changes to reflexogenic effects-the latter most likely associated with both intrinsic and extrinsic laryngeal sensorimotor mechanisms. Further physiological studies are needed to elucidate the sources of the VAF0 and EMG responses. Once elucidated, the present method may provide a powerful noninvasive tool for studying laryngeal neurophysiology. The theoretical and clinical implications of the present findings are addressed.

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

    PubMed

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

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

    PubMed

    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

  16. Alteration of Surface EMG amplitude levels of five major trunk muscles by defined electrode location displacement.

    PubMed

    Huebner, Agnes; Faenger, Bernd; Schenk, Philipp; Scholle, Hans-Christoph; Anders, Christoph

    2015-04-01

    Exact electrode positioning is vital for obtaining reliable results in Surface EMG. This study aimed at systematically assessing the influence of defined electrode shifts on measured Surface EMG amplitudes of trunk muscles in a group of 15 middle aged healthy male subjects. The following leftsided muscles were investigated: rectus abdominis muscle, internal and external oblique abdominal muscles, lumbar multifidus muscle, and longissimus muscle. In addition to the recommended electrode positions, extra electrodes were placed parallel to these and along muscle fiber direction. Measurements were performed under isometric conditions in upright body position. Gradually changing, but defined loads were applied considering subject's upper body weight. For the abdominal muscles amplitude differences varied considerably depending on load level, magnitude, and direction. For both back muscles amplitudes dropped consistently but rather little for parallel electrode displacements. However, for the longissimus muscle a caudal electrode shift resulted in an amplitude increase of similar extent and independent from load level. Influence of electrode position variations can be proven for all trunk muscles but are more evident in abdominal than back muscles. Those muscle-specific effects confirm the necessity for an exact definition of electrode positioning to allow comparisons between individual subjects, groups of subjects, and studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Possible mechanisms of muscle cramp from temporal and spatial surface EMG characteristics.

    PubMed

    Roeleveld, K; van Engelen, B G; Stegeman, D F

    2000-05-01

    In this study, the initiation and development of muscle cramp are investigated. For this, we used a 64-channel surface electromyogram (EMG) to study the triceps surae muscle during both cramp and maximal voluntary contraction (MVC) in four cramp-prone subjects and during cramp only in another four cramp-prone subjects. The results show that cramp presents itself as a contraction of a slowly moving fraction of muscle fibers, indicating that either the spatial arrangement of the motoneurons and muscle fibers is highly related or that cramp spreads at a level close to the muscle. Spectral analyses of the EMG and peak-triggered average potentials show the presence of extremely short potentials during cramp compared with during MVC. These results can also be interpreted in two ways. Either the motoneurons fire with enlarged synchronization during MVC compared with cramp, or smaller units than motor units are active, indicating that cramp is initiated close to or even at the muscle fiber level. Further research is needed to draw final conclusions.

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

    PubMed Central

    Moncayo, Roy; Moncayo, Helga

    2009-01-01

    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 muscle tests. Sedation

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

    PubMed

    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

  20. Analysis of EMG and acceleration signals for quantifying the effects of deep brain stimulation in Parkinson's disease.

    PubMed

    Rissanen, Saara M; Kankaanpää, Markku; Tarvainen, Mika P; Novak, Vera; Novak, Peter; Hu, Kun; Manor, Brad; Airaksinen, Olavi; Karjalainen, Pasi A

    2011-09-01

    Deep brain stimulation (DBS) is effective in reducing motor symptoms in Parkinson's disease (PD). However, objective methods for quantifying its efficacy are lacking. We present a principal component (PC)-based tracking method for quantifying the effects of DBS in PD by using electromyography (EMG) and acceleration measurements. Ten parameters capturing PD characteristic signal features were initially extracted from isometric EMG and acceleration recordings. Using a PC approach, the original parameters were transformed into a smaller number of PCs. Finally, the effects of DBS were quantified by examining the PCs in a low-dimensional feature space. The EMG and acceleration data from 13 PD patients with DBS ON and OFF, and 13 healthy age-matched controls were used for analysis. Clinical evaluation of patients showed that their motor symptoms were effectively reduced with DBS. The analysis results showed that the signal characteristics of 12 patients were more similar to those of the healthy controls with DBS ON than with DBS OFF. These observations indicate that the PC-based tracking method can be used to objectively quantify the effects of DBS on the neuromuscular function of PD patients. Further studies are suggested to estimate the clinical sensitivity of the method to different types of PD.

  1. Analysis of EMG and Acceleration Signals for Quantifying the Effects of Deep Brain Stimulation in Parkinson’s Disease

    PubMed Central

    Kankaanpää, Markku; Tarvainen, Mika P.; Novak, Vera; Novak, Peter; Hu, Kun; Manor, Brad; Airaksinen, Olavi; Karjalainen, Pasi A.

    2013-01-01

    Deep brain stimulation (DBS) is effective in reducing motor symptoms in Parkinson’s disease (PD). However, objective methods for quantifying its efficacy are lacking. We present a principal component (PC) -based tracking method for quantifying the effects of DBS in PD by using EMG and acceleration measurements. Ten parameters capturing PD characteristic signal features were initially extracted from isometric EMG and acceleration recordings. Using a PC approach, the original parameters were transformed into a smaller number of PCs. Finally, the effects of DBS were quantified by examining the PCs in a low-dimensional feature space. The EMG and acceleration data from 13 PD patients with DBS on and off, and 13 healthy age-matched controls were used for analysis. Clinical evaluation of patients showed that their motor symptoms were effectively reduced with DBS. The analysis results showed that the signal characteristics of 12 patients were more similar to those of the healthy controls with DBS on than with DBS off. These observations indicate that the PC-based tracking method can be used to objectively quantify the effects of DBS on the neuromuscular function of PD patients. Further studies are suggested to estimate the clinical sensitivity of the method to different types of PD. PMID:21672674

  2. Assessment of Abdominal Muscle's Maximal Force of Contraction Using Surface EMG in Inguinal Hernia Patients

    PubMed Central

    Sreenath, G. S.; Subramanian, Senthil Kumar

    2016-01-01

    Introduction Reduction in abdominal muscle’s strength has been implicated in the development of inguinal hernia. Patients with inguinal hernia on one side are shown to be at higher risk of developing inguinal hernia on the other side. Aim To assess the abdominal muscle strength in inguinal hernia subjects using surface Electromyography (EMG) and compare it with healthy controls. Materials and Methods This is a cross-sectional study involving only male subjects. Abdominal (Inguinal) hernia subjects without any known complications were recruited from surgery department and the accompanying healthy individuals were taken as control (Control, n=44, inguinal hernia subjects, n=43). The subjects were asked to perform maximal contraction for three seconds targeting external and internal oblique muscles of right and left sides separately. Motor unit potentials were recorded using surface EMG for individual muscles on both sides during maximal contraction. The maximum amplitude of the motor unit potentials obtained was considered as the strength of the respective muscle. Results In control group, there was no significant difference in strength of external and internal oblique muscles between the two sides. Strength of external and internal oblique muscles of both herniated and unaffected side was reduced in inguinal hernia subjects as compared to healthy controls. Further, the muscle strength of herniated side was less as compared to unaffected side in the inguinal hernia subjects. Conclusion Abdominal muscle strength is reduced in hernia subjects and even the apparently normal side strength is less as compared to controls. This should be considered while performing corrective surgeries in inguinal hernia subjects. PMID:28208924

  3. Surface EMG power spectrum and intramuscular pH in human vastus lateralis muscle during dynamic exercise.

    PubMed

    Bouissou, P; Estrade, P Y; Goubel, F; Guezennec, C Y; Serrurier, B

    1989-09-01

    The relationship between intramuscular pH and the frequency components of the surface electromyographic (EMG) power spectrum from the vastus lateralis muscle was studied in eight healthy male subjects during brief dynamic exercise. The studies were carried out in placebo control and metabolic alkalosis induced by oral administration of NaHCO3. At the onset of exercise, blood pH was 0.08 units higher in alkalosis compared with placebo. Muscle lactate accumulation during exercise was higher in alkalosis (32 +/- 5 mmol/kg wet wt) than in placebo (17 +/- 4 mmol/kg wet wt), but no difference in intramuscular pH was found between the two conditions. The EMG power spectrum was shifted toward lower frequencies during fatigue in the control condition (10.1 +/- 0.9%), and these spectral shifts, evaluated from changes in the mean power frequency (MPF) of the EMG power spectrum, were further accentuated in alkalosis (19 +/- 2%). Although the changes in frequency components of EMG correlated with muscle lactate accumulation (r = 0.68, P less than 0.01), no direct relationship with muscle pH was observed. We conclude that alkalosis results in a greater reduction in MPF associated with a higher muscle lactate accumulation. However, the good correlation observed between the two variables is not likely causative, and a dissociation between intramuscular pH and the increase in the low-frequency content of EMG power spectrum appears during muscle fatigue.

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

    PubMed

    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.

  5. Changes in Impedance at the Electrode-Skin Interface of Surface EMG Electrodes During Long-Term EMG Recordings

    DTIC Science & Technology

    2001-10-25

    committee (Reference: Champagne - Ardenne Consultative Committee for the Protection of Subjects in Biomedical Research, 2 May 2000). All subjects who...partially supported by the Champagne - Ardenne Regional Council. REFERENCES [1] J. Duchêne and F. Goubel, “Surface electromyogram during voluntary

  6. An Investigative Redesign of the ECG and EMG Signal Conditioning Circuits for Two-fault Tolerance and Circuit Improvement

    NASA Technical Reports Server (NTRS)

    Obrien, Edward M.

    1991-01-01

    An investigation was undertaken to make the elctrocardiography (ECG) and the electromyography (EMG) signal conditioning circuits two-fault tolerant and to update the circuitry. The present signal conditioning circuits provide at least one level of subject protection against electrical shock hazard but at a level of 100 micro-A (for voltages of up to 200 V). However, it is necessary to provide catastrophic fault tolerance protection for the astronauts and to provide protection at a current level of less that 100 micro-A. For this study, protection at the 10 micro-A level was sought. This is the generally accepted value below which no possibility of microshock exists. Only the possibility of macroshock exists in the case of the signal conditioners. However, this extra amount of protection is desirable. The initial part deals with current limiter circuits followed by an investigation into the signal conditioner specifications and circuit design.

  7. Robust myoelectric signal detection based on stochastic resonance using multiple-surface-electrode array made of carbon nanotube composite paper

    NASA Astrophysics Data System (ADS)

    Shirata, Kento; Inden, Yuki; Kasai, Seiya; Oya, Takahide; Hagiwara, Yosuke; Kaeriyama, Shunichi; Nakamura, Hideyuki

    2016-04-01

    We investigated the robust detection of surface electromyogram (EMG) signals based on the stochastic resonance (SR) phenomenon, in which the response to weak signals is optimized by adding noise, combined with multiple surface electrodes. Flexible carbon nanotube composite paper (CNT-cp) was applied to the surface electrode, which showed good performance that is comparable to that of conventional Ag/AgCl electrodes. The SR-based EMG signal system integrating an 8-Schmitt-trigger network and the multiple-CNT-cp-electrode array successfully detected weak EMG signals even when the subject’s body is in the motion, which was difficult to achieve using the conventional technique. The feasibility of the SR-based EMG detection technique was confirmed by demonstrating its applicability to robot hand control.

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

    PubMed

    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.

  9. The extraction of neural information from the surface EMG for the control of upper-limb prostheses: emerging avenues and challenges.

    PubMed

    Farina, Dario; Jiang, Ning; Rehbaum, Hubertus; Holobar, Aleš; Graimann, Bernhard; Dietl, Hans; Aszmann, Oskar C

    2014-07-01

    Despite not recording directly from neural cells, the surface electromyogram (EMG) signal contains information on the neural drive to muscles, i.e., the spike trains of motor neurons. Using this property, myoelectric control consists of the recording of EMG signals for extracting control signals to command external devices, such as hand prostheses. In commercial control systems, the intensity of muscle activity is extracted from the EMG and used for single degrees of freedom activation (direct control). Over the past 60 years, academic research has progressed to more sophisticated approaches but, surprisingly, none of these academic achievements has been implemented in commercial systems so far. We provide an overview of both commercial and academic myoelectric control systems and we analyze their performance with respect to the characteristics of the ideal myocontroller. Classic and relatively novel academic methods are described, including techniques for simultaneous and proportional control of multiple degrees of freedom and the use of individual motor neuron spike trains for direct control. The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness. None of the systems so far proposed in the literature fulfills all the important criteria needed for widespread acceptance by the patients, i.e. intuitive, closed-loop, adaptive, and robust real-time ( 200 ms delay) control, minimal number of recording electrodes with low sensitivity to repositioning, minimal training, limited complexity and low consumption. Nonetheless, in recent years, important efforts have been invested in matching these criteria, with relevant steps forwards.

  10. Conditioning and sampling issues of EMG signals in motion recognition of multifunctional myoelectric prostheses.

    PubMed

    Li, Guanglin; Li, Yaonan; Yu, Long; Geng, Yanjuan

    2011-06-01

    Historically, the investigations of electromyography (EMG) pattern recognition-based classification of intentional movements for control of multifunctional prostheses have adopted the filter cut-off frequency and sampling rate that are commonly used in EMG research fields. In practical implementation of a multifunctional prosthesis control, it is desired to have a higher high-pass cut-off frequency to reduce more motion artifacts and to use a lower sampling rate to save the data processing time and memory of the prosthesis controller. However, it remains unclear whether a high high-pass cut-off frequency and a low-sampling rate still preserve sufficient neural control information for accurate classification of movements. In this study, we investigated the effects of high-pass cut-off frequency and sampling rate on accuracy in identifying 11 classes of arm and hand movements in both able-bodied subjects and arm amputees. Compared to a 5-Hz high-pass cut-off frequency, excluding the EMG components below 60 Hz decreased the average accuracy of 0.1% in classifying the 11 movements across able-bodied subjects and increased the average accuracy of 0.1 and 0.4% among the transradial (TR) and shoulder disarticulation (SD) amputees, respectively. Using a 500 Hz instead of a 1-kHz sampling rate, the average classification accuracy only dropped about 2.0% in arm amputees. The combination of sampling rate and high-pass cut-off frequency of 500 and 60 Hz only resulted in about 2.3% decrease in average accuracy for TR amputees and 0.4% decrease for SD amputees in comparison to the generally used values of 1 kHz and 5 Hz. These results suggest that the combination of sampling rate of 500 Hz and high-pass cut-off frequency of 60 Hz should be an optimal selection in EMG recordings for recognition of different arm movements without sacrificing too much of classification accuracy which can also remove most of motion artifacts and power-line interferences for improving the

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

    PubMed Central

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

    2015-01-01

    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. PMID:25551482

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

    PubMed

    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. Biomechanical Correlates of Surface Electromyography Signals Obtained during Swallowing by Healthy Adults

    ERIC Educational Resources Information Center

    Crary, Michael A.; Carnaby (Mann), Giselle D.; Groher, Michael E.

    2006-01-01

    Purpose: The purpose of this study was to describe biomechanical correlates of the surface electromyographic signal obtained during swallowing by healthy adult volunteers. Method: Seventeen healthy adults were evaluated with simultaneous videofluoroscopy and surface electromyography (sEMG) while swallowing 5 mL of liquid barium sulfate. Three…

  14. Biomechanical Correlates of Surface Electromyography Signals Obtained during Swallowing by Healthy Adults

    ERIC Educational Resources Information Center

    Crary, Michael A.; Carnaby (Mann), Giselle D.; Groher, Michael E.

    2006-01-01

    Purpose: The purpose of this study was to describe biomechanical correlates of the surface electromyographic signal obtained during swallowing by healthy adult volunteers. Method: Seventeen healthy adults were evaluated with simultaneous videofluoroscopy and surface electromyography (sEMG) while swallowing 5 mL of liquid barium sulfate. Three…

  15. Segmentation of ECG from Surface EMG Using DWT and EMD: A Comparison Study

    NASA Astrophysics Data System (ADS)

    Shahbakhti, Mohammad; Heydari, Elnaz; Luu, Gia Thien

    2014-10-01

    The electrocardiographic (ECG) signal is a major artifact during recording the surface electromyography (SEMG). Removal of this artifact is one of the important tasks before SEMG analysis for biomedical goals. In this paper, the application of discrete wavelet transform (DWT) and empirical mode decomposition (EMD) for elimination of ECG artifact from SEMG is investigated. The focus of this research is to reach the optimized number of decomposed levels using mean power frequency (MPF) by both techniques. In order to implement the proposed methods, ten simulated and three real ECG contaminated SEMG signals have been tested. Signal-to-noise ratio (SNR) and mean square error (MSE) between the filtered and the pure signals are applied as the performance indexes of this research. The obtained results suggest both techniques could remove ECG artifact from SEMG signals fair enough, however, DWT performs much better and faster in real data.

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

    PubMed

    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.

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

    PubMed Central

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

    2017-01-01

    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. PMID:28335394

  18. COMMUNICATION: The effects of elevated body temperature on the complexity of the diaphragm EMG signals during maturation

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    In this paper, we examine the effect of elevated body temperature on the complexity of the diaphragm electromyography (EMGdia), the output of the respiratory neural network--using the approximate entropy method. The diaphragm EMG, EEG, EOG as well as other physiological signals (tracheal pressure, blood pressure and respiratory volume) in chronically instrumented rats were recorded at two postnatal ages: 25-35 days age (juvenile, n = 5) and 36-44 days age (early adult, n = 6) groups during control (36-37 °C), mild elevated body temperature (38 °C) and severe elevated body temperature (39-40 °C). Three to five trials of the recordings were performed at normal body temperature before raising the animal's core temperature by 1-4 °C with an electric heating pad. At the elevated temperature, another 3-5 trials were performed. Finally, the animal was cooled to the original temperature, and trials were again repeated. Complexity values of the diaphragm EMG signal were estimated and evaluated using the approximate entropy method (ApEn) over the ten consecutive breaths. Our results suggested that the mean approximate entropy values for the juvenile age group were 1.01 ± 0.01 (standard error) during control, 0.91 ± 0.02 during mild elevated body temperature and 0.81 ± 0.02 during severe elevated body temperature. For the early adult age group, these values were 0.94 ± 0.01 during control, 0.93 ± 0.01 during mild elevated body temperature and 0.92 ± 0.01 during severe elevated body temperature. Our results show that the complexity values and the durations of the diaphragm EMG (EMGdia) were significantly decreased when the elevated body temperature was shifted from control or mild to severe body temperature (p < 0.05) for the juvenile age group. However, for the early adult age group, an increase in body temperature slightly reduced the complexity measures and the duration of the EMGdia. But, these changes were not statistically significant. These results furthermore

  19. Changes in surface EMG assessed by discrete wavelet transform during maximal isometric voluntary contractions following supramaximal cycling.

    PubMed

    Peñailillo, Luis; Silvestre, Rony; Nosaka, Kazunori

    2013-04-01

    To better understand characteristics of neuromuscular fatigue in supramaximal cycling exercise, this study examined changes in surface electromyography (sEMG) frequency during maximal voluntary isometric contractions (MVC) following a 30-s Wingate anaerobic test (WAnT) using discrete wavelet transform (DWT). The changes in sEMG were also compared between DWT and mean frequency (MNF) obtained by fast Fourier transform (FFT). 17 healthy men performed a WAnT with a 7.5 % of body mass load. Knee extensor MVC torque was measured before and 1, 3, 6, 9, 12 and 15 min following WAnT, and sEMG was recorded from vastus lateralis muscle during the torque measures. sEMG was analysed for (RMS), MNF by FFT and frequency domains of DWT (divided into six domains). MVC torque decreased 21-23 % at 3-15 min, RMS increased 26-34 % at 1-15 min, and MNF decreased 8-10 % from baseline (76.3 ± 3.2 Hz) at 1-3 min post-cycling (P < 0.05). The DWT frequency domains showed that the changes lasted longer than MNF such that the intensity increased at 12 and 15 min for domain 2 (125-250 Hz), all time points for domain 3 (62.5-125 Hz), and 1-6 min for domains 4 (31.2-62.5 Hz) and 5 (15.6-31.2 Hz). The magnitude of increase in the intensity at 1 min post-exercise (45-60 %) was largest for domains 3 and 5 (P < 0.05). A significant correlation was evident only between the magnitude of changes in the domain 5 and MNF (r = -0.56). It is concluded that DWT provides information on neuromuscular fatigue that is not detected by MNF derived from FFT.

  20. Surface electromyogram signal modelling.

    PubMed

    McGill, K C

    2004-07-01

    The paper reviews the fundamental components of stochastic and motor-unit-based models of the surface electromyogram (SEMG). Stochastic models used in ergonomics and kinesiology consider the SEMG to be a stochastic process whose amplitude is related to the level of muscle activation and whose power spectral density reflects muscle conduction velocity. Motor-unit-based models for describing the spatio-temporal distribution of individual motor-unit action potentials throughout the limb are quite robust, making it possible to extract precise information about motor-unit architecture from SEMG signals recorded by multi-electrode arrays. Motor-unit-based models have not yet been proven as successful, however, for extracting information about recruitment and firing rates throughout the full range of contraction. The relationship between SEMG and force during natural dynamic movements is much too complex to model in terms of single motor units.

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

    PubMed

    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. The effect of selective beta1-blockade on EMG signal characteristics during progressive endurance exercise.

    PubMed

    Hunter, Angus M; St Clair Gibson, Allan; Derman, Wayne E; Lambert, Michael; Dennis, Stephen C; Noakes, Timothy D

    2002-12-01

    This study analysed the effect of selective beta(1)-blockade on neuromuscular recruitment characteristics during progressive endurance exercise. Ten healthy subjects ingested a selective beta(1)-blocker, acebutolol (200 mg b.d.), for 7 days (for one of two cycling trials), with a 10-day wash-out period between trials. On the last day of acebutolol ingestion subjects performed three successive 15-min rides at 30%, 50% and 70% of their peak power output and then cycled at increasing (15 W min(-1)) work rates to exhaustion. Force output, heart rate, submaximal VO(2), rate of perceived exertion (RPE), electromyographic (EMG) data and blood lactate were captured during the cycling activity. Peak work rate [270 (111) W vs 197 (75) W, CON vs BETA, P <0.01], time to exhaustion [49.7 (23.2) min vs 40.3 (23.7) min, CON vs BETA, P <0.05] and heart rate [mean, for the full ride 135.5 (38.3) beats min(-1) vs 111.5 (30.0) beats min(-1) CON vs BETA, P <0.05] were significantly lower for the group who ingested beta(1)-blockade (BETA) compared to the control group (CON). Although not significant, submaximal VO(2)was reduced in BETA during the ride, while RPE was significantly higher during the ride for BETA (P <0.01). Mean integrated electromyography was higher in the BETA group although these differences were not significant. Mean power frequency values of the BETA group showed a significant (P <0.05) shift to the upper end of the spectrum in comparison to the control group. Lactate values [11.7 (3.5) mmol x l(-1) vs 7.1 (4.1) mmol x l(-1)CON vs BETA] were significantly lower (P <0.05) at exhaustion in BETA. Significant reductions in cycling performance were found when subjects ingested beta(1)-blockers. This study has shown significant shifts to the upper end of the EMG frequency spectrum after beta(1)-blocker ingestion, which could be caused by a change in neuromuscular recruitment strategy to compensate for the impaired submaximal exercise performance.

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

    PubMed

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

    2005-02-01

    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 (MU). The aim of this paper was to determine, with the aid of a HD-EMG grid, the relative importance of a number of electrode sensor configurations for optimizing muscle force estimation. Sensor configurations are distinguished in two categories. The first category concerns dimensions: the size of a single electrode and the inter electrode distance (IED). The second category concerns the sensor's spatial distribution: the total area from which signals are obtained (collection surface) and the number of electrodes per cm(2) (collection density). Eleven subjects performed isometric arm extensions at three elbow angles and three contraction levels. Surface-EMG from the triceps brachii muscle and the external force at the wrist were measured. Compared to a single conventional bipolar electrode pair, the force estimation quality improved by about 30% when using HD-EMG. Among the sensor configurations, the collection surface alone appeared to be responsible for the major part of the EMG based force estimation quality by improving it with 25%.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  8. Oscillations in motor unit discharge are reflected in the low-frequency component of rectified surface EMG and the rate of change in force.

    PubMed

    Yoshitake, Yasuhide; Shinohara, Minoru

    2013-11-01

    Common drive to a motor unit (MU) pool manifests as low-frequency oscillations in MU discharge rate, producing fluctuations in muscle force. The aim of the study was to examine the temporal correlation between instantaneous MU discharge rate and rectified EMG in low frequencies. Additionally, we attempted to examine whether there is a temporal correlation between the low-frequency oscillations in MU discharge rate and the first derivative of force (dF/dt). Healthy young subjects produced steady submaximal force with their right finger as a single task or while maintaining a pinch-grip force with the left hand as a dual task. Surface EMG and fine-wire MU potentials were recorded from the first dorsal interosseous muscle in the right hand. Surface EMG was band-pass filtered (5-1,000 Hz) and full-wave rectified. Rectified surface EMG and the instantaneous discharge rate of MUs were smoothed by a Hann-window of 400 ms duration (equivalent to 2 Hz low-pass filtering). In each of the identified MUs, the smoothed MU discharge rate was positively correlated with the rectified-and-smoothed EMG as confirmed by the distinct peak in cross-correlation function with greater values in the dual task compared with the single task. Additionally, the smoothed MU discharge rate was temporally correlated with dF/dt more than with force and with rectified-and-smoothed EMG. The results indicated that the low-frequency component of rectified surface EMG and the first derivative of force provide temporal information on the low-frequency oscillations in the MU discharge rate.

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

    PubMed

    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.

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

    PubMed

    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

    PubMed Central

    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. PMID:22163515

  12. Emg Amplitude Estimators Based on Probability Distribution for Muscle-Computer Interface

    NASA Astrophysics Data System (ADS)

    Phinyomark, Angkoon; Quaine, Franck; Laurillau, Yann; Thongpanja, Sirinee; Limsakul, Chusak; Phukpattaranont, Pornchai

    To develop an advanced muscle-computer interface (MCI) based on surface electromyography (EMG) signal, the amplitude estimations of muscle activities, i.e., root mean square (RMS) and mean absolute value (MAV) are widely used as a convenient and accurate input for a recognition system. Their classification performance is comparable to advanced and high computational time-scale methods, i.e., the wavelet transform. However, the signal-to-noise-ratio (SNR) performance of RMS and MAV depends on a probability density function (PDF) of EMG signals, i.e., Gaussian or Laplacian. The PDF of upper-limb motions associated with EMG signals is still not clear, especially for dynamic muscle contraction. In this paper, the EMG PDF is investigated based on surface EMG recorded during finger, hand, wrist and forearm motions. The results show that on average the experimental EMG PDF is closer to a Laplacian density, particularly for male subject and flexor muscle. For the amplitude estimation, MAV has a higher SNR, defined as the mean feature divided by its fluctuation, than RMS. Due to a same discrimination of RMS and MAV in feature space, MAV is recommended to be used as a suitable EMG amplitude estimator for EMG-based MCIs.

  13. [Pathophysiological analysis of dropped head syndrome caused by various diagnoses - based on surface EMG findings and responses to physiotherapy].

    PubMed

    Lin, Hsin-Ni; Nagaoka, Masanori; Hayashi, Yasuko; Yonezawa, Ikuho

    2013-01-01

    Dropped head syndrome is seen in various diseases. We investigated its pathophysiological mechanisms with physical and radiological examination, surface EMG and responses to physiotherapy. Subjects had dropped head as a complaint, but their primary diagnoses were various. We investigated 16 cases: 5 cases of Parkinson disease, 5 cases of multiple system atrophy predominant parkinsonism, 3 cases of cervical spondylosis and 3 cases with other diagnoses. We found that patients had common findings such as bulging of cervical muscles, and tonic EMG activities mainly in the extensors in the sitting and standing position, but in the flexors of the neck only in the supine position. Of the 16 cases, 14 were treated with physiotherapy to improve the alignment of the pelvis and whole vertebral column; 6 of the 14 cases (63%) showed remarkable improvement. We conclude that the primary reason of dropped head syndrome is unknown in Parkinson disease and cervical spondylosis, but also that many of the patients have secondary changes in alignment of the skeletomuscular system which could be treated with physiotherapy.

  14. Robust Features Of Surface Electromyography Signal

    NASA Astrophysics Data System (ADS)

    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

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

    PubMed

    Negro, Francesco; Keenan, Kevin; Farina, Dario

    2015-06-01

    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. 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. 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. This study clarifies the conditions when rectifying the surface EMG is appropriate for studying neural connectivity.

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

    NASA Astrophysics Data System (ADS)

    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.

  17. [Picking up and analysis of the surface myoelectric signals of respiratory muscule].

    PubMed

    Weng, J F; Long, S C

    2001-07-01

    In this paper, we introduce the technique used to obtain the surface diaphragmatic EMG and monitor respiratory activity. The signals are picked up from the ECG electrodes. By using an ECG masking system based on a digital processor, the dominant effect of the ECG (that is R-wave, P-wave and T-wave) was removed. Initial clinical measurements indicate this EMG method is more direct and effective than others for monitoring respiratory activity. It is hoped that this method can be used to monitor the development of respiratory function.

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

    PubMed Central

    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

  19. The simulation of click and double-click through EMG signals.

    PubMed

    Pinheiro, Carlos G; Andrade, Adriano O

    2012-01-01

    Patients with severe motor impairments, victims of stroke, amyotrophic lateral sclerosis and spinal cord injury are prevented from oral and gesture communication, demanding alternative channels and methods of communication, possibly using a computer. In order to obtain the complete emulation of a standard mouse, the single-click and double-click actions are desirable functionalities. In this study, the implementation of such actions is executed by the analysis of the electromyographic signal recorded from the Frontalis muscle. Muscle activity is discriminated from noise and this information is used to feed a state-machine that in turn decides which action is intended. The method uses an adaptive threshold, which offers freedom for the selection of the parameters of the system. The rate of successfully detected commands found was up to 100% for the single-click and 92% for the double-click. Even though good results were found for double-clicks, the experiment indicate muscle fatigue in the short term. The time response found was below 300 ms suggesting real-time implementation is feasible. Also, other devices can be operated with this approach, if it is accepted as a two symbols system generator.

  20. Comparison of surface electromyographic (sEMG) activity of submental muscles between the head lift and tongue press exercises as a therapeutic exercise for pharyngeal dysphagia.

    PubMed

    Yoshida, Mitsuyoshi; Groher, Michael E; Crary, Michael A; Mann, Giselle Carnaby; Akagawa, Yasumasa

    2007-06-01

    The present study compared surface electromyographic (sEMG) activity obtained from the submental muscle group for a tongue press and a head lift exercise as potential therapeutic exercises for dysphagic elderly. Fifty-three healthy volunteers with a mean age of 35.3 participated in this study. Subjects were required to perform an isometric task, pressing their tongue against the hard palate, and an isotonic task requiring sustained lingual force against the hard palate. Pressure sensors were used to measure the amount of lingual pressure against the hard palate. Submental sEMG data from these tasks were compared with those obtained from the isometric and isotonic aspects of a head lift exercise. No sEMG differences were identified between the isometric tongue press task and head lift exercise. Isotonic tongue press exercises resulted in significantly higher maximum and mean sEMG values compared with the isotonic head lift exercise (p < 0.05). The submental sEMG activity from the tongue press exercise was equal (isometric) to, or greater (isotonic) than comparable muscle activation obtained during the head lift exercise. The tongue press exercise may be less strenuous than the head lift exercise while achieving the same therapeutic effect.

  1. Analysis of muscle fiber conduction velocity enables reliable detection of surface EMG crosstalk during detection of nociceptive withdrawal reflexes.

    PubMed

    Jensen, Michael Brun; Manresa, José Alberto Biurrun; Frahm, Ken Steffen; Andersen, Ole Kæseler

    2013-03-26

    The nociceptive withdrawal reflex (NWR) is a polysynaptic spinal reflex that induces complex muscle synergies to withdraw a limb from a potential noxious stimulus. Several studies indicate that assessment of the NWR is a valuable objective tool in relation to investigation of various pain conditions. However, existing methodologies for NWR assessment evaluate standard surface electromyography (sEMG) measured over just one muscle and do not consider the possible interference of crosstalk originating from adjacent active muscles. The present study had two aims: firstly, to investigate to which extent the presence of crosstalk may affect NWR detection using a standardized scoring criterion (interval peak z-score) that has been validated without taking crosstalk into consideration. Secondly, to investigate whether estimation of muscle fiber conduction velocity can help identifying the propagating and non-propagating nature of genuine reflexes and crosstalk respectively, thus allowing a more valid assessment of the NWR. Evaluation of interval peak z-score did apparently allow reflex detection with high sensitivity and specificity (0.96), but only if the influence of crosstalk was ignored. Distinction between genuine reflexes and crosstalk revealed that evaluation of interval peak z-score incorporating a z-score threshold of 12 was associated with poor reflex detection specificity (0.26-0.62) due to the presence of crosstalk. Two different standardized methods for estimation of muscle fiber conduction velocity were employed to demonstrate that significantly different muscle fiber conduction velocities may be estimated during genuine reflexes and crosstalk, respectively. This discriminative feature was used to develop and evaluate a novel methodology for reflex detection from sEMG that is robust with respect to crosstalk. Application of this conduction velocity analysis (CVA) entailed reflex detection with excellent sensitivity (1.00 and 1.00) and specificity (1.00 and 0

  2. Analysis of muscle fiber conduction velocity enables reliable detection of surface EMG crosstalk during detection of nociceptive withdrawal reflexes

    PubMed Central

    2013-01-01

    Background The nociceptive withdrawal reflex (NWR) is a polysynaptic spinal reflex that induces complex muscle synergies to withdraw a limb from a potential noxious stimulus. Several studies indicate that assessment of the NWR is a valuable objective tool in relation to investigation of various pain conditions. However, existing methodologies for NWR assessment evaluate standard surface electromyography (sEMG) measured over just one muscle and do not consider the possible interference of crosstalk originating from adjacent active muscles. The present study had two aims: firstly, to investigate to which extent the presence of crosstalk may affect NWR detection using a standardized scoring criterion (interval peak z-score) that has been validated without taking crosstalk into consideration. Secondly, to investigate whether estimation of muscle fiber conduction velocity can help identifying the propagating and non-propagating nature of genuine reflexes and crosstalk respectively, thus allowing a more valid assessment of the NWR. Results Evaluation of interval peak z-score did apparently allow reflex detection with high sensitivity and specificity (0.96), but only if the influence of crosstalk was ignored. Distinction between genuine reflexes and crosstalk revealed that evaluation of interval peak z-score incorporating a z-score threshold of 12 was associated with poor reflex detection specificity (0.26-0.62) due to the presence of crosstalk. Two different standardized methods for estimation of muscle fiber conduction velocity were employed to demonstrate that significantly different muscle fiber conduction velocities may be estimated during genuine reflexes and crosstalk, respectively. This discriminative feature was used to develop and evaluate a novel methodology for reflex detection from sEMG that is robust with respect to crosstalk. Application of this conduction velocity analysis (CVA) entailed reflex detection with excellent sensitivity (1.00 and 1.00) and

  3. Short- and long-term changes in joint co-contraction associated with motor learning as revealed from surface EMG.

    PubMed

    Osu, Rieko; Franklin, David W; Kato, Hiroko; Gomi, Hiroaki; Domen, Kazuhisa; Yoshioka, Toshinori; Kawato, Mitsuo

    2002-08-01

    In the field of motor control, two hypotheses have been controversial: whether the brain acquires internal models that generate accurate motor commands, or whether the brain avoids this by using the viscoelasticity of musculoskeletal system. Recent observations on relatively low stiffness during trained movements support the existence of internal models. However, no study has revealed the decrease in viscoelasticity associated with learning that would imply improvement of internal models as well as synergy between the two hypothetical mechanisms. Previously observed decreases in electromyogram (EMG) might have other explanations, such as trajectory modifications that reduce joint torques. To circumvent such complications, we required strict trajectory control and examined only successful trials having identical trajectory and torque profiles. Subjects were asked to perform a hand movement in unison with a target moving along a specified and unusual trajectory, with shoulder and elbow in the horizontal plane at the shoulder level. To evaluate joint viscoelasticity during the learning of this movement, we proposed an index of muscle co-contraction around the joint (IMCJ). The IMCJ was defined as the summation of the absolute values of antagonistic muscle torques around the joint and computed from the linear relation between surface EMG and joint torque. The IMCJ during isometric contraction, as well as during movements, was confirmed to correlate well with joint stiffness estimated using the conventional method, i.e., applying mechanical perturbations. Accordingly, the IMCJ during the learning of the movement was computed for each joint of each trial using estimated EMG-torque relationship. At the same time, the performance error for each trial was specified as the root mean square of the distance between the target and hand at each time step over the entire trajectory. The time-series data of IMCJ and performance error were decomposed into long-term components that

  4. Parametric estimation of the continuous non-stationary spectrum and its dynamics in surface EMG studies.

    PubMed

    Korosec, D

    2000-09-01

    Frequency spectrum of surface electromyographic signals (SEMGs) exhibit a non-stationary nature even in the case of constant level isometric muscle contractions due to changes related to muscle fatigue processes. These changes can be evaluated by methods for estimation of time-varying (TV) spectrum. The most widely adopted non-parametric approach is a short time Fourier transform (STFT), from which changes of mean frequency (MF) as well as other parameters for qualitative description of spectrum variation can be calculated. Similar idea of a sliding-window generalisation can also be used in case of parametric spectrum analysis methods. We applied such approach to obtain TV linear models of SEMGs, although its large variance due to independence of estimations in consequent windows represents a major drawback. This variance causes unrealistic abrupt changes in the curve of overall spectrum dynamics, calculated either as the second derivative of the MF or, as we propose, autoregressive moving average (ARMA) distance between subsequent linear models forming the TV parametric spectrum. A smoother estimation is therefore sought and another method shows to be superior over a simple sliding window technique. It supposes that trajectories of TV linear model coefficients can be described as linear combinations of known basis functions. We demonstrate that the later method is very appropriate for description of slowly changing spectra of SEMGs and that dynamics measures obtained from such estimations can be used as an additional indication of the fatigue process.

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

    PubMed

    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.

  6. Analysis of surface EMG activation in hand percussion playing depending on the grasping type and the tempo.

    PubMed

    Chong, Hyun Ju; Kim, Soo Ji; Lee, Eun Kyoung; Yoo, Ga Eul

    2015-08-01

    Although instrument playing-based training has been repeatedly reported to improve functional hand movements including grasping, the attempts to present quantitative information on physiological mechanism of grasping have been relatively insufficient to determine the type and the intensity of the exercises involved. This study aimed to examine the muscle activation during hand percussion playing depending on the grasping type and the playing tempo. A total of twelve healthy older adults with a mean age of 71.5 years participated in this study. Surface electrodes were placed on three grasping-related muscles: Flexor digitorum superficialis, extensor digitorum, and flexor pollicis brevis. Participants were instructed to play with the egg shaker, paddle drum mallet and clave involving different types of grasp at three different tempi (i.e., 80, 100, and 120 bpm) and sEMG data were collected during each playing. Significantly greater muscle activation was generated with the small sphere type of egg shaker, compared to the handle type of paddle drum mallet and the small cylinder type of clave. Playing at faster tempo also elicited significantly greater muscle activation than at slower tempo. With regard to the rise time of muscle activation, while tempo significantly affected the rise time, the time to peak muscle did not significantly change depending on the grasping type. This study confirmed that grasping pattern and the tempo of movement significantly influence the muscular activation of grasping involved in instrument playing. Based on these results, clinical implication for instrument selection and structured instrument playing would be suggested.

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

    PubMed

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

    2010-11-01

    The rectus abdominis (RA) and oblique external abdominal (OEA) muscles are both part of the construction of the equine trunk and thought to be essential for the function of the spine during locomotion. Although RA activity at trot has previously been investigated, the relationship between OEA and RA at walk and trot has not yet been described. To document abdominal muscle activities during walk and trot, and test the hypothesis that muscle activity at walk would be smaller than at trot. Six horses (8-20 years old, 450-700 kg) were used for surface electromyography (EMG) measurements, with EMG electrodes placed caudal to the sternum (RA) and at the level of the 16th rib (OEA). On all hooves, the withers and the sacrum reflective markers were placed to determine motion cycles. Normal distribution of data was tested using a Kolmogorov-Smirnov test and Student's t test was used to compare left-right and walk-trot differences (P < 0.05). Minimum, maximum and mean EMG values recorded at walk were significantly higher at trot than at walk in all horses for OEA and in 5/6 horses for RA. At walk, EMG activity ranged from 8-44 mV (RA) and 7-54 mV (OEA). At trot, EMG activity ranged from 18-150 mV (RA) and 27-239 mV (OEA). There were statistically significant differences between maximum activities of left and right OEA and RA muscles at walk in all horses, and in 4/6 horses at trot. Muscle activities of OEA and RA are smaller at walk than at trot. At walk, the OEA/RA ratio is lower than at trot. There are more significant correlations between muscle activities of both RA and OEA and limb movements at walk than at the trot. © 2010 EVJ Ltd.

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

    PubMed

    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.

  9. Designing a Low-noise, High-resolution, and Portable Four Channel Acquisition System for Recording Surface Electromyographic Signal

    PubMed Central

    Pashaei, Akbar; Yazdchi, Mohammad Reza; Marateb, Hamid Reza

    2015-01-01

    In current years, the application of biopotential signals has received a lot of attention in literature. One of these signals is an electromyogram (EMG) generated by active muscles. Surface EMG (sEMG) signal is recorded over the skin, as the representative of the muscle activity. Since its amplitude can be as low as 50 μV, it is sensitive to undesirable noise signals such as power-line interferences. This study aims at designing a battery-powered portable four-channel sEMG signal acquisition system. The performance of the proposed system was assessed in terms of the input voltage and current noise, noise distribution, synchronization and input noise level among different channels. The results indicated that the designed system had several inbuilt operational merits such as low referred to input noise (lower than 0.56 μV between 8 Hz and 1000 Hz), considerable elimination of power-line interference and satisfactory recorded signal quality in terms of signal-to-noise ratio. The muscle conduction velocity was also estimated using the proposed system on the brachial biceps muscle during isometric contraction. The estimated values were in then normal ranges. In addition, the system included a modular configuration to increase the number of recording channels up to 96. PMID:26951952

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

    PubMed

    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.

  11. Archery performance level and repeatability of event-related EMG.

    PubMed

    Soylu, A R; Ertan, H; Korkusuz, F

    2006-12-01

    The purpose of the current study was to compare the repeatability of electromyographic linear envelopes (LE) of archery groups. Surface electromyography (EMG) signals of musculus flexor digitorum superficialis (MFDS) and extensor digitorum (MED) of 23 participants (seven skilled, six beginner archers and ten non-archers) were recorded during archery shooting. Two-second periods (clicker falls at first second) of 12 shots' EMG data were recorded, full-wave rectified and filtered (60 ms moving-average filter) for each participant's drawing arm. Repeatability was investigated by using a statistical criterion, variance ratio (VR). Archers' performances were evaluated in terms of FITA scores. The results showed that FITA scores were significantly correlated to the VRs of MFDS and MED. EMG LEs were more repeatable among archers than non-archers. Therefore, we inferred that VRs of MFDS and MED might be important variables for (a) assessing shooting techniques, (b) evaluation of archers' progress, and (c) selection of talented archers.

  12. Epoch length to accurately estimate the amplitude of interference EMG is likely the result of unavoidable amplitude cancellation

    PubMed Central

    Keenan, Kevin G.; Valero-Cuevas, Francisco J.

    2008-01-01

    Researchers and clinicians routinely rely on interference electromyograms (EMGs) to estimate muscle forces and command signals in the neuromuscular system (e.g., amplitude, timing, and frequency content). The amplitude cancellation intrinsic to interference EMG, however, raises important questions about how to optimize these estimates. For example, what should the length of the epoch (time window) be to average an EMG signal to reliably estimate muscle forces and command signals? Shorter epochs are most practical, and significant reductions in epoch have been reported with high-pass filtering and whitening. Given that this processing attenuates power at frequencies of interest (< 250 Hz), however, it is unclear how it improves the extraction of physiologically-relevant information. We examined the influence of amplitude cancellation and high-pass filtering on the epoch necessary to accurately estimate the “true” average EMG amplitude calculated from a 28 s EMG trace (EMGref) during simulated constant isometric conditions. Monte Carlo iterations of a motor-unit model simulating 28 s of surface EMG produced 245 simulations under 2 conditions: with and without amplitude cancellation. For each simulation, we calculated the epoch necessary to generate average full-wave rectified EMG amplitudes that settled within 5% of EMGref. For the no-cancellation EMG, the necessary epochs were short (e.g., < 100 ms). For the more realistic interference EMG (i.e., cancellation condition), epochs shortened dramatically after using high-pass filter cutoffs above 250 Hz, producing epochs short enough to be practical (i.e., < 500 ms). We conclude that the need to use long epochs to accurately estimate EMG amplitude is likely the result of unavoidable amplitude cancellation, which helps to clarify why high-pass filtering (> 250 Hz) improves EMG estimates. PMID:19081815

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

    PubMed Central

    Wu, Changcheng; Zeng, Hong; Song, Aiguo; Xu, Baoguo

    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, the experimental platform, the acquisition of the sEMG, the feature extraction of the sEMG and the construction of GRNN are described. Then, the multi-channels of the sEMG when the hand is moving are captured by the EMG sensors attached on eight different positions of the arm skin surface. Meanwhile, a grip force sensor and a three dimension force sensor are adopted to measure the output force of the human's hand. The characteristic matrix of the sEMG and the force signals are used to construct the GRNN. The mean absolute value and the root mean square of the estimation errors, the correlation coefficients between the actual force and the estimated force are employed to assess the accuracy of the estimation. Analysis of variance (ANOVA) is also employed to test the difference of the force estimation. The experiments are implemented to verify the effectiveness of the proposed estimation method and the results show that the output force of the human's hand can be correctly estimated by using sEMG and GRNN method. PMID:28713231

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

    PubMed

    Wu, Changcheng; Zeng, Hong; Song, Aiguo; Xu, Baoguo

    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, the experimental platform, the acquisition of the sEMG, the feature extraction of the sEMG and the construction of GRNN are described. Then, the multi-channels of the sEMG when the hand is moving are captured by the EMG sensors attached on eight different positions of the arm skin surface. Meanwhile, a grip force sensor and a three dimension force sensor are adopted to measure the output force of the human's hand. The characteristic matrix of the sEMG and the force signals are used to construct the GRNN. The mean absolute value and the root mean square of the estimation errors, the correlation coefficients between the actual force and the estimated force are employed to assess the accuracy of the estimation. Analysis of variance (ANOVA) is also employed to test the difference of the force estimation. The experiments are implemented to verify the effectiveness of the proposed estimation method and the results show that the output force of the human's hand can be correctly estimated by using sEMG and GRNN method.

  15. Effect of oral administration of sodium bicarbonate on surface EMG activity during repeated cycling sprints.

    PubMed

    Matsuura, Ryouta; Arimitsu, Takuma; Kimura, Takehide; Yunoki, Takahiro; Yano, Tokuo

    2007-11-01

    The purpose of this study was to determine the effect of oral administration of sodium bicarbonate (NaHCO3) on surface electromyogram (SEMG) activity from the vastus lateralis (VL) during repeated cycling sprints (RCS). Subjects performed two RCS tests (ten 10-s sprints) interspersed with both 30-s and 360-s recovery periods 1 h after oral administration of either NaHCO3 (RCSAlk) or CaCO3 (RCSPla) in a random counterbalanced order. Recovery periods of 360 s were set before the 5th and 9th sprints. The rate of decrease in plasma HCO3- concentration during RCS was significantly greater in RCSAlk than in RCSPla, but the rates of decline in blood pH during the two RCS tests were similar. There was no difference between change in plasma lactate concentration in RCSAlk and that in RCSPla. Performance during RCSAlk was similar to that during RCSPla. There were no differences in oxygen uptake immediately before each cycling sprint (preVO2) and in SEMG activity between RCSAlk and RCSPla. In conclusion, oral administration of NaHCO3 did not affect SEMG activity from the VL. This suggests that the muscle recruitment strategy during RCS is not determined by only intramuscular pH.

  16. Novel parameters of surface EMG in patients with Parkinson's disease and healthy young and old controls.

    PubMed

    Meigal, A I; Rissanen, S; Tarvainen, M P; Karjalainen, P A; Iudina-Vassel, I A; Airaksinen, O; Kankaanpää, M

    2009-06-01

    The aim of this study was to evaluate a variety of traditional and novel surface electromyography (SEMG) characteristics of biceps brachii muscle in patients with Parkinson's disease (PD) and compare the results with the healthy old and young control subjects. Furthermore, the aim was to define the optimal biceps brachii loading level that would most likely differentiate patients from controls. The results indicated that such nonlinear SEMG parameters as %Recurrence, %Determinism and SEMG distribution kurtosis, correlation dimension and sample entropy were significantly different between the PD patients and healthy controls. These novel nonlinear parameters, unlike traditional spectral or amplitude parameters, correlated with the Unified Parkinson's Disease Rating Scale (UPDRS) and finger tapping scores. The most significant between group differences were found in the loading condition where no additional weights were applied in isometric elbow flexion. No major difference of SEMG characteristics was detected between old and young control subjects. In conclusion, the novel SEMG parameters can differentiate the patients with PD from healthy control subjects and these parameters may have potential in the assessment of the severity of PD.

  17. The Application of sEMG in Aging: A Mini Review.

    PubMed

    Boccia, Gennaro; Dardanello, Davide; Rosso, Valeri; Pizzigalli, Luisa; Rainoldi, Alberto

    2015-01-01

    The aim of this mini-review is to describe the potential application of surface electromyography (sEMG) techniques in aging studies. Aging is characterized by multiple changes of the musculoskeletal system physiology and function. This paper will examine some of the innovative methods used to monitor age-related alterations of the neuromuscular system from sEMG signals. A description of critical assumptions which underlie some of these approaches is emphasized. The first part focuses on the evolution of the recording techniques and describes some methodological issues. The second part focuses on how to use the following techniques to characterize aging: amplitude and spectral sEMG signal analysis, muscle fiber conduction velocity estimation, and myoelectric fatigue assessment. The last part describes a number of advanced sEMG approaches which seem promising in the geriatric population to estimate motor unit number, size, recruitment thresholds, and firing rates.

  18. Characteristics of EMG frequency bands in temporomandibullar disorders patients.

    PubMed

    Politti, Fabiano; Casellato, Claudia; Kalytczak, Marcelo Martins; Garcia, Marilia Barbosa Santos; Biasotto-Gonzalez, Daniela Aparecida

    2016-12-01

    The aim of the present study was to determine whether any specific frequency bands of surface electromyographic (sEMG) signals are more susceptible to alterations in patients with temporomandibular disorders (TMD), when compared with healthy subjects. Twenty-seven healthy adults (19 women and eight men; mean age: 23±6.68years) and 27 TMD patients (20 women and seven men; mean age: 24±5.89years) voluntarily participated in the experiment. sEMG data were recorded from the right and left masseter muscles (RM and LM) and the right and left anterior temporalis muscles (RT and LT) as the participants performed tests of chewing (CHW) and maximal clenching effort (MCE). Frequency domain analysis of the sEMG signal was used to analyze differences between TMD patients and healthy subjects in relation to the Power Spectral Density Function (PSDF). The analysis focused on the median frequency (MDF) of the sEMG signal and PSDF frequency bands after the EMG spectrum was divided into twenty-five frequency band of 20Hz each. The Mann-Whitney test was used to compare MDF between TMD patients and healthy subjects and the frequency bands were analyzed using three-way ANOVA with three factors: frequency band, muscle and group. The results of the analysis confirmed that the median frequency values in TMD patients were significantly higher (p<0.05) than those recorded for healthy subjects in the two experimental conditions (MCE and CHW), for all of the muscles assessed (RM, LM, RT and LT). In addition, frequency content between 20 and 100Hz of the normalized PSDF range was significantly lower (p<0.05) in TMD patients than in healthy. This study contributes to quantitatively identify TMD dysfunctions, by non-invasive sEMGs; this assessment is clinically important and still lacking nowadays. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Nonnegative matrix factorization for the identification of EMG finger movements: evaluation using matrix analysis.

    PubMed

    Naik, Ganesh R; Nguyen, Hung T

    2015-03-01

    Surface electromyography (sEMG) is widely used in evaluating the functional status of the hand to assist in hand gesture recognition, prosthetics and rehabilitation applications. The sEMG is a noninvasive, easy to record signal of superficial muscles from the skin surface. Considering the nonstationary characteristics of sEMG, recent feature selection of hand gesture recognition using sEMG signals necessitate designers to use nonnegative matrix factorization (NMF)-based methods. This method exploits both the additive and sparse nature of signals by extracting accurate and reliable measurements of sEMG features using a minimum number of sensors. The testing has been conducted for simple and complex finger flexions using several experiments with artificial neural network classification scheme. It is shown, both by simulation and experimental studies, that the proposed algorithm is able to classify ten finger flexions (five simple and five complex finger flexions) recorded from two sEMG sensors up to 92% (95% for simple and 87% for complex flexions) accuracy. The recognition performances of simple and complex finger flexions are also validated with NMF permutation matrix analysis.

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

    PubMed

    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.

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

    PubMed

    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.

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

    PubMed

    Ishii, Tomohiro; Narita, Noriyuki; Endo, Hiroshi

    2016-06-01

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

  3. Reducing electrocardiographic artifacts from electromyogram signals with independent component analysis.

    PubMed

    Costa Junior, J D; Ferreira, D D; Nadal, J; Miranda de Sa, A L

    2010-01-01

    The aim of this work was to reduce ECG artifacts from surface electromyogram (EMG) signals collected from lumbar muscles with the blind source separation technique based on independent component analysis (ICA). Using four EMG signals collected above erector spinal lumbar muscles from 27 subjects, the proposed method fail in separating the sources. However, when considering a single channel of EMG and the same one time-shifted by one sample, the FastICA allowed reducing the signal to ECG noise ratio.

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

    PubMed

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

    2007-11-01

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

  5. Development of new muscle contraction sensor to replace sEMG for using in muscles analysis fields.

    PubMed

    Zhang, D; Matsuoka, Y; Kong, W; Imtiaz, U; Bartolomeo, L; Cosentino, S; Zecca, M; Sessa, S; Ishii, H; Takanishi, A

    2014-01-01

    Nowadays, the technologies for detecting, processing and interpreting bioelectrical signals have improved tremendously. In particular, surface electromyography (sEMG) has gained momentum in a wide range of applications in various fields. However, sEMG sensing has several shortcomings, the most important being: measurements are heavily sensible to individual differences, sensors are difficult to position and very expensive. In this paper, the authors will present an innovative muscle contraction sensing device (MC sensor), aiming to replace sEMG sensing in the field of muscle movement analysis. Compared with sEMG, this sensor is easier to position, setup and use, less dependent from individual differences, and less expensive. Preliminary experiments, described in this paper, confirm that MC sensing is suitable for muscle contraction analysis, and compare the results of sEMG and MC sensor for the measurement of forearm muscle contraction.

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

    PubMed

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

    2016-10-25

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

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

    PubMed Central

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

    2016-01-01

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

  8. Spatial variability of muscle activity during human walking: the effects of different EMG normalization approaches.

    PubMed

    Cronin, N J; Kumpulainen, S; Joutjärvi, T; Finni, T; Piitulainen, H

    2015-08-06

    Human leg muscles are often activated inhomogeneously, e.g. in standing. This may also occur in complex tasks like walking. Thus, bipolar surface electromyography (sEMG) may not accurately represent whole muscle activity. This study used 64-electrode high-density sEMG (HD-sEMG) to examine spatial variability of lateral gastrocnemius (LG) muscle activity during the stance phase of walking, maximal voluntary contractions (MVCs) and maximal M-waves, and determined the effects of different normalization approaches on spatial and inter-participant variability. Plantar flexion MVC, maximal electrically elicited M-waves and walking at self-selected speed were recorded in eight healthy males aged 24-34. sEMG signals were assessed in four ways: unnormalized, and normalized to MVC, M-wave or peak sEMG during the stance phase of walking. During walking, LG activity varied spatially, and was largest in the distal and lateral regions. Spatial variability fluctuated throughout the stance phase. Normalizing walking EMG signals to the peak value during stance reduced spatial variability within LG on average by 70%, and inter-participant variability by 67%. Normalizing to MVC reduced spatial variability by 17% but increased inter-participant variability by 230%. Normalizing to M-wave produced the greatest spatial variability (45% greater than unnormalized EMG) and increased inter-participant variability by 70%. Unnormalized bipolar LG sEMG may provide misleading results about representative muscle activity in walking due to spatial variability. For the peak value and MVC approaches, different electrode locations likely have minor effects on normalized results, whereas electrode location should be carefully considered when normalizing walking sEMG data to maximal M-waves. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

  9. Generating Control Commands From Gestures Sensed by EMG

    NASA Technical Reports Server (NTRS)

    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

  10. Towards whole body fatigue assessment of human movement: a fatigue-tracking system based on combined sEMG and accelerometer signals.

    PubMed

    Dong, Haiwei; Ugalde, Izaskun; Figueroa, Nadia; El Saddik, Abdulmotaleb

    2014-01-27

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

  11. Appropriately placed surface EMG electrodes reflect deep muscle activity (psoas, quadratus lumborum, abdominal wall) in the lumbar spine.

    PubMed

    McGill, S; Juker, D; Kropf, P

    1996-11-01

    This study tested the possibility of obtaining the activity of deeper muscles in the torso-specifically psoas, quadratus lumborum, external oblique, internal oblique and transverse abdominis, using surface myoelectric electrodes. It was hypothesized that: (1) surface electrodes adequately represent the amplitude of deep muscles (specifically psoas, quadratus lumborum, external oblique, internal oblique, transverse abdominis); (2) a single surface electrode location would best represent the activation profiles of each deep muscle over a broad variety of tasks. We assumed that prediction of activation within 10% of maximum voluntary contraction (RMS difference between the surface and intramuscular channels), over the time history of the signal, was reasonable and acceptable to assist clinical interpretation of muscle activation amplitude, and ultimately for modeled estimates of muscle force. Surface electrodes were applied and intramuscular electrodes were inserted on the left side of the body in five men and three women who then performed a wide variety of flexor tasks (bent knee and straight leg situps and leg raises, curl ups), extensor tasks (including lifting barbells up to 70 kg), lateral bending tasks (standing lateral bend and horizontal lying side support), twisting tasks (standing and sitting), and internal/external hip rotation. Using the criteria of RMS difference and the coefficient of determination (R2) to compare surface with intramuscular myoelectric signals, the results indicated that selected surface electrodes adequately represent the amplitude of deep muscles-always within 15% RMS difference, or less with the exception of psoas where differences up to 20% were observed but only in certain maximum voluntary contraction efforts. It appears reasonable for spine modelers, and particularly clinicians, to assume well selected surface electrode locations provide a representation of these deeper muscles-as long as they recognize the magnitude of error for

  12. Improved discrete Fourier transform based spectral feature for surface electromyogram signal classification.

    PubMed

    He, Jiayuan; Zhang, Dingguo; Sheng, Xinjun; Meng, Jianjun; Zhu, Xiangyang

    2013-01-01

    An improved discrete Fourier transform (iDFT) is presented in this study as a novel feature for surface electromyogram (sEMG) pattern classification. It employs the principle that the spectrum of sEMG signals changes regarding different motions. iDFT feature focuses on global information of local bands to increase the inter-class distance. The experiment results showed that iDFT feature had a better separability than two other spectral features, auto regression (AR) and Power spectral density (PSD), both on experienced and inexperienced subjects. The optimal bandwidth is between 30 and 50 Hz and influence of division methods is not significant. With the low computation cost and property of insensitivity to sampling frequency, our proposed method provides a competitive choice for prosthetic control.

  13. EOG-sEMG Human Interface for Communication.

    PubMed

    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%.

  14. MVC techniques to normalize trunk muscle EMG in healthy women.

    PubMed

    Vera-Garcia, Francisco J; Moreside, Janice M; McGill, Stuart M

    2010-02-01

    Normalization of the surface electromyogram (EMG) addresses some of the inherent inter-subject and inter-muscular variability of this signal to enable comparison between muscles and people. The aim of this study was to evaluate the effectiveness of several maximal voluntary isometric contraction (MVC) strategies, and identify maximum electromyographic reference values used for normalizing trunk muscle activity. Eight healthy women performed 11 MVC techniques, including trials in which thorax motion was resisted, trials in which pelvis motion was resisted, shoulder rotation and adduction, and un-resisted MVC maneuvers (maximal abdominal hollowing and maximal abdominal bracing). EMG signals were bilaterally collected from upper and lower rectus abdominis, lateral and medial aspects of external oblique, internal oblique, latissimus dorsi, and erector spinae at T9 and L5. A 0.5s moving average window was used to calculate the maximum EMG amplitude of each muscle for each MVC technique. A great inter-subject variability between participants was observed as to which MVC strategy elicited the greatest muscular activity, especially for the oblique abdominals and latissimus dorsi. Since no single test was superior for obtaining maximum electrical activity, it appears that several upper and lower trunk MVC techniques should be performed for EMG normalization in healthy women.

  15. EOG-sEMG Human Interface for Communication

    PubMed Central

    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%. PMID:27418924

  16. EMG activity of the serratus anterior and trapezius muscles during the different phases of the push-up plus exercise on different support surfaces and different hand positions.

    PubMed

    Gioftsos, George; Arvanitidis, Michail; Tsimouris, Dimitrios; Kanellopoulos, Assimakis; Paras, George; Trigkas, Panagiotis; Sakellari, Vasiliki

    2016-07-01

    [Purpose] The appropriate exercise prescription is crucial for achieving scapular stability and providing successful rehabilitation, and the Push-up Plus (PuP) exercise has an important role in shoulder rehabilitation. Consequently, this study examined the effect of support surface stability, hand positioning, and phase of exercise, on the trapezius and serratus anterior muscle contractions as well as on the EMG ratio of the upper/lower trapezius. [Subjects and Methods] Thirteen healthy male volunteers participated in this study. The subjects performed the PuP exercise on stable and unstable supporting surfaces with three different hand orientations. During the PuP exercise, the muscle activities of the upper (UT) and lower (LT) trapezius, as well as the serratus anterior (SA) were measured and expressed as percentages of maximum voluntary isometric contraction (%MVIC). [Results] The EMG activities of UT and LT were statistically greater during the push-up phase compared to the plus phase of the exercise. The contrary was recorded for the activity of the SA. SA was affected by the support surface as well as by the hand positioning. [Conclusion] The results suggest that different phases of the PuP exercise require different muscle stability actions with corresponding activations of appropriate muscle fibers. A detailed prescription of the required phase of the exercise can more effectively activate the scapula-thoracic musculature.

  17. EMG activity of the serratus anterior and trapezius muscles during the different phases of the push-up plus exercise on different support surfaces and different hand positions

    PubMed Central

    Gioftsos, George; Arvanitidis, Michail; Tsimouris, Dimitrios; Kanellopoulos, Assimakis; Paras, George; Trigkas, Panagiotis; Sakellari, Vasiliki

    2016-01-01

    [Purpose] The appropriate exercise prescription is crucial for achieving scapular stability and providing successful rehabilitation, and the Push-up Plus (PuP) exercise has an important role in shoulder rehabilitation. Consequently, this study examined the effect of support surface stability, hand positioning, and phase of exercise, on the trapezius and serratus anterior muscle contractions as well as on the EMG ratio of the upper/lower trapezius. [Subjects and Methods] Thirteen healthy male volunteers participated in this study. The subjects performed the PuP exercise on stable and unstable supporting surfaces with three different hand orientations. During the PuP exercise, the muscle activities of the upper (UT) and lower (LT) trapezius, as well as the serratus anterior (SA) were measured and expressed as percentages of maximum voluntary isometric contraction (%MVIC). [Results] The EMG activities of UT and LT were statistically greater during the push-up phase compared to the plus phase of the exercise. The contrary was recorded for the activity of the SA. SA was affected by the support surface as well as by the hand positioning. [Conclusion] The results suggest that different phases of the PuP exercise require different muscle stability actions with corresponding activations of appropriate muscle fibers. A detailed prescription of the required phase of the exercise can more effectively activate the scapula-thoracic musculature. PMID:27512278

  18. Further evaluation of an EMG technique for assessment of the deep cervical flexor muscles.

    PubMed

    Falla, D; Jull, G; O'Leary, S; Dall'Alba, P

    2006-12-01

    A novel surface electromyographic (EMG) technique was recently described for the detection of deep cervical flexor muscle activity. Further investigation of this technique is warranted to ensure EMG activity from neighbouring muscles is not markedly influencing the signals recorded. This study compared deep cervical flexor (DCF) muscle activity with the activity of surrounding neck and jaw muscles during various anatomical movements of the neck and jaw in 10 volunteer subjects. DCF EMG activity was recorded with custom electrodes inserted via the nose and fixed by suction to the posterior mucosa of the oropharynx. Surface electrodes were placed over the sternocleidomastoid, anterior scalene, masseter and suprahyoid muscles. Positioned in supine, subjects performed isometric cranio-cervical flexion, cervical flexion, right and left cervical rotation, jaw clench and resisted jaw opening. Across all movements examined, EMG amplitude of the DCF muscles was greatest during neck movements that would require activity of the DCF muscles, particularly during cranio-cervical flexion, their primary anatomical action. The actions of jaw clench and resisted jaw opening demonstrated significantly less DCF EMG activity than the cranio-cervical flexion action (p<0.05). Across all other movements, the neighbouring neck and jaw muscles demonstrated greatest EMG amplitude during their respective primary anatomical actions, which occurred in the absence of increased EMG amplitude recorded from the DCF muscles. The finding of substantial EMG activity of the DCF muscles only during neck actions that would require their activity, particularly cranio-cervical flexion, and not during actions involving the jaw, provide further assurance that the majority of myoelectric signals detected from the nasopharyngeal electrode are from the DCF muscles.

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

    PubMed

    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.

  20. EMG Feature Assessment for Myoelectric Pattern Recognition and Channel Selection: A Study with Incomplete Spinal Cord Injury

    PubMed Central

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

    PubMed

    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.

  2. Eliminating ultrasonic interference from respiratory muscle EMG.

    PubMed

    Platt, R S; Kieser, T M; Easton, P A

    1998-05-01

    Fine wire recordings of the respiratory muscle electromyogram are often employed to represent muscle activity, and recently ultrasound-sonomicrometry has become a common method of measuring length of respiratory muscles in both acute and chronic preparations. Although recording both EMG and sonomicrometry simultaneously has become standard practice, there has not been any consideration of the potential confounding influence of ultrasound noise upon the recorded EMG spectrum. Activation of the sonomicrometry-ultrasound tranducer introduces a high frequency, high amplitude voltage pulse plus harmonics, which can contaminate the EMG spectrum directly, as well as through aliasing when EMG is sampled directly digitally. We describe the use of a new, combined, wing stabilized sonomicrometry- and EMG measurement transducer to characterize exactly the influence of ultrasound upon the crural diaphragm EMG spectrum, and the development of digital filtering techniques which effectively eliminate the ultrasound interference. Two alternative methods of avoiding ultrasound-EMG interference are also considered. The isolation and elimination of ultrasound-sonomicrometry signal interference may be important in studies where EMG and length are measured together.

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

    PubMed

    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 (P<0.05) for both isometric control and wrist extension. The results suggest that SMG signal has great potential as an alternative to EMG for prosthetic control.

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

    PubMed

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

    2015-12-01

    The objective was to investigate the influence of surface electromyography (sEMG) processing methods on the quantification of muscle activity during whole-body vibration (WBV) exercises. sEMG activity was recorded while the participants performed squats on the platform with and without WBV. The spikes observed in the sEMG spectrum at the vibration frequency and its harmonics were deleted using state-of-the-art methods, i.e. (1) a band-stop filter, (2) a band-pass filter, and (3) spectral linear interpolation. The same filtering methods were applied on the sEMG during the no-vibration trial. The linear interpolation method showed the highest intraclass correlation coefficients (no vibration: 0.999, WBV: 0.757-0.979) with the comparison measure (unfiltered sEMG during the no-vibration trial), followed by the band-stop filter (no vibration: 0.929-0.975, WBV: 0.661-0.938). While both methods introduced a systematic bias (P < 0.001), the error increased with increasing mean values to a higher degree for the band-stop filter. After adjusting the sEMG(RMS) during WBV for the bias, the performance of the interpolation method and the band-stop filter was comparable. The band-pass filter was in poor agreement with the other methods (ICC: 0.207-0.697), unless the sEMG(RMS) was corrected for the bias (ICC ⩾ 0.931, %LOA ⩽ 32.3). In conclusion, spectral linear interpolation or a band-stop filter centered at the vibration frequency and its multiple harmonics should be applied to delete the artifacts in the sEMG signals during WBV. With the use of a band-stop filter it is recommended to correct the sEMG(RMS) for the bias as this procedure improved its performance.

  5. The influence of occlusion on jaw and neck muscle activity: a surface EMG study in healthy young adults.

    PubMed

    Ferrario, V F; Tartaglia, G M; Galletta, A; Grassi, G P; Sforza, C

    2006-05-01

    The electromyographic (EMG) characteristics of masseter, temporalis and sternocleidomastoid (SCM) muscles during maximum voluntary teeth clench were assessed in 27 male and 35 female healthy young adults. Subjects were divided into two groups: (i) 'complete' Angle Class I (bilateral, symmetric canine and molar Class I relationships), and (ii) 'partial' Angle Class I (one to three canine/molar Class I relationships, the remaining relationships were Class II or Class III). On average, standardized muscular symmetry ranged 80.7-87.9%. During maximum voluntary teeth clench, average co-contraction of SCM muscle was 13.7-23.5% of its maximum contraction. On average, all torque coefficients (potential lateral displacing component) were >90%, while all antero-posterior coefficients (relative activities of masseter and temporalis muscles) were >85%. The average integrated areas of the masseter and temporalis EMG potentials over time ranged 87.4-106.8 muV/muV s%. Standardized contractile muscular activities did not differ between 'complete' and 'partial' Angle Class I, and between sexes (two-way analysis of variance). A trend toward a larger intragroup variability in EMG indices was observed in the subjects with 'partial' Angle Class I than in those with 'complete' Angle Class I (significant difference for the temporalis muscle symmetry, P = 0.013, analysis of variance). In conclusion, the presence of a complete or partial Angle occlusal Class I did not seem to influence the standardized contractile activities of masseter, temporalis and SCM muscles during a maximum voluntary clench. Subjects with a 'complete' Angle Class I were somewhat a more homogenous group than subjects with 'partial' Angle Class I.

  6. Baseline Adaptive Wavelet Thresholding Technique for sEMG Denoising

    NASA Astrophysics Data System (ADS)

    Bartolomeo, L.; Zecca, M.; Sessa, S.; Lin, Z.; Mukaeda, Y.; Ishii, H.; Takanishi, Atsuo

    2011-06-01

    The surface Electromyography (sEMG) signal is affected by different sources of noises: current technology is considerably robust to the interferences of the power line or the cable motion artifacts, but still there are many limitations with the baseline and the movement artifact noise. In particular, these sources have frequency spectra that include also the low-frequency components of the sEMG frequency spectrum; therefore, a standard all-bandwidth filtering could alter important information. The Wavelet denoising method has been demonstrated to be a powerful solution in processing white Gaussian noise in biological signals. In this paper we introduce a new technique for the denoising of the sEMG signal: by using the baseline of the signal before the task, we estimate the thresholds to apply to the Wavelet thresholding procedure. The experiments have been performed on ten healthy subjects, by placing the electrodes on the Extensor Carpi Ulnaris and Triceps Brachii on right upper and lower arms, and performing a flexion and extension of the right wrist. An Inertial Measurement Unit, developed in our group, has been used to recognize the movements of the hands to segment the exercise and the pre-task baseline. Finally, we show better performances of the proposed method in term of noise cancellation and distortion of the signal, quantified by a new suggested indicator of denoising quality, compared to the standard Donoho technique.

  7. Perineal surface electromyography does not typically demonstrate expected relaxation during normal voiding.

    PubMed

    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

    2011-11-01

    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. 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. 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. 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. Copyright © 2011 Wiley Periodicals, Inc.

  8. Design, development and testing of a low-cost sEMG system and its use in recording muscle activity in human gait.

    PubMed

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

    2014-05-07

    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.

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

    PubMed Central

    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

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

    NASA Astrophysics Data System (ADS)

    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.

  11. Rechargeable wireless EMG sensor for prosthetic control.

    PubMed

    Lichter, P A; Lange, E H; Riehle, T H; Anderson, S M; Hedin, D S

    2010-01-01

    Surface electrodes in modern myoelectric prosthetics are often embedded in the prosthesis socket and make contact with the skin. These electrodes detect and amplify muscle action potentials from voluntary contractions of the muscle in the residual limb and are used to control the prosthetic's movement and function. There are a number of performance-related deficiencies associated with external electrodes including the maintenance of sufficient electromyogram (EMG) signal amplitude, extraneous noise acquisition, and proper electrode interface maintenance that are expected to be improved or eliminated using the proposed implanted sensors. This research seeks to investigate the design components for replacing external electrodes with fully-implantable myoelectric sensors that include a wireless interface to the prosthetic limbs. This implanted technology will allow prosthetic limb manufacturers to provide products with increased performance, capability, and patient-comfort. The EMG signals from the intramuscular recording electrode are amplified and wirelessly transmitted to a receiver in the prosthetic limb. Power to the implant is maintained using a rechargeable battery and an inductive energy transfer link from the prosthetic. A full experimental system was developed to demonstrate that a wireless biopotential sensor can be designed that meets the requirements of size, power, and performance for implantation.

  12. Continuous motion decoding from EMG using independent component analysis and adaptive model training.

    PubMed

    Zhang, Qin; Xiong, Caihua; Chen, Wenbin

    2014-01-01

    Surface Electromyography (EMG) is popularly used to decode human motion intention for robot movement control. Traditional motion decoding method uses pattern recognition to provide binary control command which can only move the robot as predefined limited patterns. In this work, we proposed a motion decoding method which can accurately estimate 3-dimensional (3-D) continuous upper limb motion only from multi-channel EMG signals. In order to prevent the muscle activities from motion artifacts and muscle crosstalk which especially obviously exist in upper limb motion, the independent component analysis (ICA) was applied to extract the independent source EMG signals. The motion data was also transferred from 4-manifold to 2-manifold by the principle component analysis (PCA). A hidden Markov model (HMM) was proposed to decode the motion from the EMG signals after the model trained by an adaptive model identification process. Experimental data were used to train the decoding model and validate the motion decoding performance. By comparing the decoded motion with the measured motion, it is found that the proposed motion decoding strategy was feasible to decode 3-D continuous motion from EMG signals.

  13. Characterization of the motor units of the external anal sphincter in pregnant women with multichannel surface EMG.

    PubMed

    Cescon, Corrado; Raimondi, Eleonora Ester; Začesta, Vita; Drusany-Starič, Kristina; Martsidis, Konstantinos; Merletti, R

    2014-08-01

    Locating the innervation zones (IZs) of the external anal sphincter (EAS) is helpful to obstetricians to identify areas particularly vulnerable to episiotomy in pregnant women. The aim was to investigate the motor unit (MU) properties of the EAS during voluntary contractions. Electromyographic signals were detected, from 478 pregnant women, by means of an intra-anal cylindrical probe carrying a circumferential array of 16 electrodes. The signals were decomposed into the constituent MU action potential trains and 5,947 templates were extracted and analyzed in order to identify the IZ position. MUs innervated at one end are concentrated in the dorsal portion of the sphincter, while MUs innervated in the middle are distributed symmetrically in the left and right portions of the EAS. The angular propagation velocity was estimated for each MU resulting in 260 ± 45 rad/s, corresponding to 1.8 m/s on the probe surface and to about 4 m/s at a radial depth of 10 mm from the probe surface. A novel method for identification and classification of MUs of the EAS is proposed and applied to a large-scale study. It is possible to distinguish MUs of the EAS in a minimally invasive way and identify their IZs. This information should be used to plan episiotomies and minimize risks of EAS denervation.

  14. Motor modules of human locomotion: influence of EMG averaging, concatenation, and number of step cycles

    PubMed Central

    Oliveira, Anderson S.; Gizzi, Leonardo; Farina, Dario; Kersting, Uwe G.

    2014-01-01

    Locomotion can be investigated by factorization of electromyographic (EMG) signals, e.g., with non-negative matrix factorization (NMF). This approach is a convenient concise representation of muscle activities as distributed in motor modules, activated in specific gait phases. For applying NMF, the EMG signals are analyzed either as single trials, or as averaged EMG, or as concatenated EMG (data structure). The aim of this study is to investigate the influence of the data structure on the extracted motor modules. Twelve healthy men walked at their preferred speed on a treadmill while surface EMG signals were recorded for 60s from 10 lower limb muscles. Motor modules representing relative weightings of synergistic muscle activations were extracted by NMF from 40 step cycles separately (EMGSNG), from averaging 2, 3, 5, 10, 20, and 40 consecutive cycles (EMGAVR), and from the concatenation of the same sets of consecutive cycles (EMGCNC). Five motor modules were sufficient to reconstruct the original EMG datasets (reconstruction quality >90%), regardless of the type of data structure used. However, EMGCNC was associated with a slightly reduced reconstruction quality with respect to EMGAVR. Most motor modules were similar when extracted from different data structures (similarity >0.85). However, the quality of the reconstructed 40-step EMGCNC datasets when using the muscle weightings from EMGAVR was low (reconstruction quality ~40%). On the other hand, the use of weightings from EMGCNC for reconstructing this long period of locomotion provided higher quality, especially using 20 concatenated steps (reconstruction quality ~80%). Although EMGSNG and EMGAVR showed a higher reconstruction quality for short signal intervals, these data structures did not account for step-to-step variability. The results of this study provide practical guidelines on the methodological aspects of synergistic muscle activation extraction from EMG during locomotion. PMID:24904375

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

    PubMed

    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.

  16. Estimation of Optimal Measurement Position of Human Forearm EMG Signal by Discriminant Analysis Based on Wilks' lambda

    NASA Astrophysics Data System (ADS)

    Kiso, Atsushi; Taniguchi, Yu; Seki, Hirokazu

    This paper describes the estimation of the optimal measurement position by discriminant analysis based on Wilks' lambda for myoelectric hand control. In previous studies, for motion discrimination, the myoelectric signals were measured at the same positions. However, the optimal measurement positions of the myoelectric signals for motion discrimination differ depending on the remaining muscles of amputees. Therefore, the purpose of this study is to estimate the optimal and fewer measurement positions for precise motion discrimination of a human forearm. This study proposes a method for estimating the optimal measurement positions by discriminant analysis based on Wilks' lambda, using the myoelectric signals measured at multiple positions. The results of some experiments on the myoelectric hand simulator show the effectiveness of the proposed optimal measurement position estimation method.

  17. Wideband EMG telemetry system

    NASA Technical Reports Server (NTRS)

    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.

  18. Wideband EMG telemetry system

    NASA Technical Reports Server (NTRS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

  1. Muscular fatigue detection using sEMG in dynamic contractions.

    PubMed

    Bueno, Diana R; Lizano, J M; Montano, L

    2015-08-01

    In this work we have studied different indicators of muscle fatigue from the electrical signal produced by the muscles when contract (sEMG or EMG: surface electromyography): Mean Frequency of the power spectrum (MNF), Median Frequency (Fmed), Dimitrov Spectral Index (FInsm5), Root Mean Square (RMS), and Zerocrossing (ZC). The most reliable features are selected to develop a detection algorithm that estimates muscle fatigue. The approach used in the algorithm is probabilistic and is based on the technique of Gaussian Mixture Model (GMM). The system is divided into two stages: training and validation. During training, the algorithm learns the distribution of data regarding fatigue evolution; after that, the algorithm is validated with data that have not been used to train. Therefore, two experimental sessions have been performed with 6 healthy subjects for biceps.

  2. Surface Laplacian of central scalp electrical signals is insensitive to muscle contamination.

    PubMed

    Fitzgibbon, Sean P; Lewis, Trent W; Powers, David M W; Whitham, Emma W; Willoughby, John O; Pope, Kenneth J

    2013-01-01

    The objective of this paper was to investigate the effects of surface Laplacian processing on gross and persistent electromyographic (EMG) contamination of electroencephalographic (EEG) signals in electrical scalp recordings. We made scalp recordings during passive and active tasks, on awake subjects in the absence and in the presence of complete neuromuscular blockade. Three scalp surface Laplacian estimators were compared to left ear and common average reference (CAR). Contamination was quantified by comparing power after paralysis (brain signal, B) with power before paralysis (brain plus muscle signal, B+M). Brain:Muscle (B:M) ratios for the methods were calculated using B and differences in power after paralysis to represent muscle (M). There were very small power differences after paralysis up to 600 Hz using surface Laplacian transforms (B:M > 6 above 30 Hz in central scalp leads). Scalp surface Laplacian transforms reduce muscle power in central and pericentral leads to less than one sixth of the brain signal, two to three times better signal detection than CAR. Scalp surface Laplacian transformations provide robust estimates for detecting high-frequency (gamma) activity, for assessing electrophysiological correlates of disease, and also for providing a measure of brain electrical activity for use as a standard in the development of brain/muscle signal separation methods.

  3. Differences in age-related fiber atrophy between vastii muscles of active subjects: a multichannel surface EMG study.

    PubMed

    Boccia, Gennaro; Dardanello, Davide; Coratella, Giuseppe; Rinaldo, Nicoletta; Schena, Federico; Rainoldi, Alberto

    2015-07-01

    The aim of the study was to non-invasively determine if vastus lateralis (VL) and vastus medialis obliquus (VM) muscles are equally affected by age-related fiber atrophy. Multichannel surface electromyography was used since it allows to estimate muscle fiber conduction velocity (CV), which has been demonstrated to be related to the size of recruited muscle fibers. Twelve active elderly men (age 69   ±   4 years) and 12 active young men (age 23   ±   2 years) performed isometric knee extension at 30%, 50%, and 70% of maximal voluntary contraction. Electromyographic signals were recorded from VL and VM muscles of the dominant limb using arrays with eight electrodes and CVs were estimated for each contraction. CV estimates showed a different behavior in the two muscles: in VL at 50% and 70% of maximum voluntary contraction they were greater in young than in elderly; whereas such a difference was not observed in VM. This finding suggest that in active elderly VM seems to be less affected by the age-related fibers atrophy than VL. Hence, the common choice of studying VL as a muscle representative of the whole quadriceps could generate misleading findings. Indeed, it seemed that the sarcopenic ageing effects might be heterogeneous within quadriceps muscle.

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

    PubMed Central

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

    2015-01-01

    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 < 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. Key points The spikes observed in the sEMG spectrum during WBV exercises contain motion artifacts and possibly reflex activity The motion artifacts are more pronounced in the first spike than the following spikes in the sEMG spectrum Reflex activity during WBV exercises is enhanced with an additional load of approximately 50% of the body mass PMID:25729290

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

    PubMed

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

    2017-01-01

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

  6. Syllable-based speech recognition using EMG.

    PubMed

    Lopez-Larraz, Eduardo; Mozos, Oscar M; Antelis, Javier M; Minguez, Javier

    2010-01-01

    This paper presents a silent-speech interface based on electromyographic (EMG) signals recorded in the facial muscles. The distinctive feature of this system is that it is based on the recognition of syllables instead of phonemes or words, which is a compromise between both approaches with advantages as (a) clear delimitation and identification inside a word, and (b) reduced set of classification groups. This system transforms the EMG signals into robust-in-time feature vectors and uses them to train a boosting classifier. Experimental results demonstrated the effectiveness of our approach in three subjects, providing a mean classification rate of almost 70% (among 30 syllables).

  7. EMG power spectrum patterns of anterior temporal and masseter muscles in children and adults.

    PubMed

    Yuen, S W; Hwang, J C; Poon, P W

    1989-05-01

    The power spectrum of electromyograms (EMG) has been demonstrated to vary with muscles having different muscle fiber type compositions. This study investigated the variations in EMG power spectrum patterns of the masticatory muscles with age and gender by comparison of the mean power frequency (MPF) of the anterior temporal and masseter muscles in children and adults. Surface EMG signals were sampled bilaterally from the muscles when the subjects were performing maximum voluntary isometric clenches at maximal intercuspal position. The results indicated that MPF values were age-dependent (p less than 0.001), and sexual dimorphism was evident (p less than 0.001), with lower MPF values in male and adult muscles. While male adults had the lowest and female children had the highest MPF values, female adults had MPF values closer to values obtained from male children. These differences or similarities could be attributed to the degree of differentiation of the muscles during growth and development of the craniofacial morphology.

  8. Gesture Based Control and EMG Decomposition

    NASA Technical Reports Server (NTRS)

    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.

  9. Surface reflections of Pioneer Venus probe signals

    NASA Technical Reports Server (NTRS)

    Croft, T. A.

    1980-01-01

    As the four Pioneer Venus probes fell within the atmosphere toward the surface of Venus, each of them transmitted a radio signal directly to earth. Because of the relatively broad antenna beamwidth of these small probes, some of the transmitted power went down to the surface of Venus. This paper reports the discovery that the radio signals scattered off the surface are not only detectable but that their characteristics can be determined with a surprising degree of certainty. From these characteristics one can determine parameters of the Venusian atmospheric winds and of the surface that promise to be useful. Most of the scattered energy is that which originally radiated from the probes in a near-horizontal direction; the downward-directed radiation is detectable but much weaker. Refraction in the atmosphere of Venus clearly plays a significant role in establishing both the strength of scatter and its Doppler shift.

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

    PubMed

    Heintz, Sofia; Gutierrez-Farewik, Elena M

    2007-07-01

    Individual muscle forces evaluated from experimental motion analysis may be useful in mathematical simulation, but require additional musculoskeletal and mathematical modelling. A numerical method of static optimization was used in this study to evaluate muscular forces during gait. The numerical algorithm used was built on the basis of traditional optimization techniques, i.e., constrained minimization technique using the Lagrange multiplier method to solve for constraints. Measuring exact muscle forces during gait analysis is not currently possible. The developed optimization method calculates optimal forces during gait, given a specific performance criterion, using kinematics and kinetics from gait analysis together with muscle architectural data. Experimental methods to validate mathematical methods to calculate forces are limited. Electromyography (EMG) is frequently used as a tool to determine muscle activation in experimental studies on human motion. A method of estimating force from the EMG signal, the EMG-to-force approach, was recently developed by Bogey et al. [Bogey RA, Perry J, Gitter AJ. An EMG-to-force processing approach for determining ankle muscle forcs during normal human gait. IEEE Trans Neural Syst Rehabil Eng 2005;13:302-10] and is based on normalization of activation during a maximum voluntary contraction to documented maximal muscle strength. This method was adapted in this study as a tool with which to compare static optimization during a gait cycle. Muscle forces from static optimization and from EMG-to-force muscle forces show reasonably good correlation in the plantarflexor and dorsiflexor muscles, but less correlation in the knee flexor and extensor muscles. Additional comparison of the mathematical muscle forces from static optimization to documented averaged EMG data reveals good overall correlation to patterns of evaluated muscular activation. This indicates that on an individual level, muscular force patterns from mathematical

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

    PubMed Central

    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

  12. 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.

    PubMed

    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 (P<0.05) different between groups (participants with pain/MTrP: -0.32±1.2 cm at 15% MVC and -0.35±0.9 cm at 60% MVC relative to the ALS; asymptomatic participants: 1.0±1.3 cm at 15% MVC and 1.3±1.1 cm relative to the ALS). However, no correlation was observed between the position of the MTrP and peak EMG 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.

  13. Synchronous EMG activity in the Piper frequency band reveals the corticospinal demand of walking tasks

    PubMed Central

    Clark, David J.; Kautz, Steven A.; Bauer, Andrew R.; Chen, Yen-Ting; Christou, Evangelos A.

    2013-01-01

    Evidence indicates that the frequency-domain characteristics of surface electromyogram (EMG) signals are modulated according to the contributing sources of neural drive. Modulation of inter-muscular EMG synchrony within the Piper frequency band (30–60Hz) during movement tasks has been linked to drive from the corticospinal tract. However, it is not known whether EMG synchrony is sufficiently sensitive to detect task-dependent differences in the corticospinal contribution to leg muscle activation during walking. We investigated this question in seventeen healthy older men and women. It was hypothesized that, relative to typical steady state walking, Piper band EMG synchrony of the triceps surae muscle group would be reduced for dual-task walking (because of competition for cortical resources), similar for fast walking (because walking speed is directed by an intermediate locomotor pathway rather than by the corticospinal tract), and increased when taking a long step (because voluntary gait pattern modifications are directed by the corticospinal tract). Each of these hypotheses was confirmed. These findings support the use of frequency-domain analysis of EMG in future investigations into the corticospinal contribution to control of healthy and disordered human walking. PMID:23740367

  14. Finite State Machine with Adaptive Electromyogram (EMG) Feature Extraction to Drive Meal Assistance Robot

    NASA Astrophysics Data System (ADS)

    Zhang, Xiu; Wang, Xingyu; Wang, Bei; Sugi, Takenao; Nakamura, Masatoshi

    Surface electromyogram (EMG) from elbow, wrist and hand has been widely used as an input of multifunction prostheses for many years. However, for patients with high-level limb deficiencies, muscle activities in upper-limbs are not strong enough to be used as control signals. In this paper, EMG from lower-limbs is acquired and applied to drive a meal assistance robot. An onset detection method with adaptive threshold based on EMG power is proposed to recognize different muscle contractions. Predefined control commands are output by finite state machine (FSM), and applied to operate the robot. The performance of EMG control is compared with joystick control by both objective and subjective indices. The results show that FSM provides the user with an easy-performing control strategy, which successfully operates robots with complicated control commands by limited muscle motions. The high accuracy and comfortableness of the EMG-control meal assistance robot make it feasible for users with upper limbs motor disabilities.

  15. Frequency analyses of EMG power spectra of anterior temporal and masseter muscles in children and adults.

    PubMed

    Takarada, T; Larrinaga, G A; Nishida, F; Nishino, M

    1990-01-01

    To study the functional change of masticatory muscles during growth and development, frequency analyses of surface electromyogram (EMG) power spectra were carried out. The subjects were six children (five males and one female), aged 4.5 +/- 0.2 years, having full deciduous dentition (Hellman's dental age IIA) and six adults (four males and two females), aged 27.7 +/- 3.8 years, having full permanent dentition. EMG signals were recorded bilaterally by using bipolar silver-surface electrodes from the anterior temporal and masseter muscles while the subjects were chewing gum and while performing maximum clenching in the intercuspal position. A fast Fourier transform algorithm was used to obtain the power-spectral density function and the power spectra of the EMG signals. Since the total power value from 62.5 to 1000 Hz was 100 percent, the frequencies at 25, 50, 75, and 90 percent of the cumulative power were calculated. The results showed that the frequencies at every percent of the cumulative power were age-dependent and that the EMG power spectra patterns in adult muscles were shifted to significantly lower frequencies than those in child muscles. The shift was probably caused by differences in the proportion of fiber type and fiber size between muscles of children and adults.

  16. Relationship between the MRI and EMG measurements.

    PubMed

    Kubota, J; Ono, T; Araki, M; Tawara, N; Torii, S; Okuwaki, T; Fukubayashi, T

    2009-07-01

    The purpose of this study was to investigate the effect of intensive eccentric exercise on hamstring muscles by using magnetic resonance imaging (MRI) and to elucidate the relationships between the changes in the electromyographic (EMG) parameters and in the transverse relaxation time (T2) of the hamstring muscles. Seven male volunteers performed eccentric knee flexion exercise, and the EMG activity of the hamstring muscles was simultaneously measured. Before and immediately after the exercise, the maximum isometric knee flexion torque was measured and MR images of the hamstring muscles were obtained. For all hamstring muscles, the EMG activity of the fifth set was significantly lower than that of the first set. For each subject, a significant correlation was detected between the percentage change in the value of the post-exercise T2 value and those of EMG signals during the exercise only for the semitendinosus (ST) muscle and not for the biceps femoris (BF) and the semimembranosus (SM) muscles. These results suggested that the EMG-activity reductions in the BF, ST, and SM muscles were due to neuromuscular fatigue, and moreover the reduction in the ST muscle was due to a failure in the E-C coupling, which was caused by excessive muscle-fiber damage.

  17. Enhanced Propagating Surface Plasmon Signal Detection

    SciTech Connect

    Gong, Y.; 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. sEMG Sensor Using Polypyrrole-Coated Nonwoven Fabric Sheet for Practical Control of Prosthetic Hand

    PubMed Central

    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

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

    PubMed

    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.

  20. Characterizing EMG data using machine-learning tools.

    PubMed

    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.

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

    PubMed

    Marco, Gazzoni; Alberto, Botter; Taian, Vieira

    2017-05-01

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

  2. High-density surface EMG decomposition allows for recording of motor unit discharge from proximal and distal flexion synergy muscles simultaneously in individuals with stroke.

    PubMed

    Miller, Laura C; Thompson, Christopher K; Negro, Francesco; Heckman, C J; Farina, Dario; Dewald, Julius P A

    2014-01-01

    Analysis of motor unit discharge can provide insight into the neural control of movement in healthy and pathological states, but it is typically completed in one muscle at a time. For some research investigations, it would be advantageous to study motor unit discharge from multiple muscles simultaneously. One such example is investigation of the flexion synergy, an abnormal muscle co-activation pattern in post-stroke individuals in which activation of shoulder abductors is involuntarily coupled with that of elbow and finger flexors. However, limitations in available technology have hindered the ability to efficiently extract motor unit discharge from multiple muscles simultaneously. In this study, we propose the use of high-density surface EMG decomposition from proximal and distal flexion synergy muscles (deltoid, biceps, wrist/finger flexors) in combination with an isometric joint torque recording device in individuals with chronic stroke. This innovative approach provides the ability to efficiently analyze both motor units and joint torques that have been simultaneously recorded from the shoulder, elbow, and fingers. In preliminary experiments, 3 stroke and 5 control participants generated shoulder abduction, elbow flexion, and finger flexion torques at 10, 20, 30 and 40% of maximum torque. Motor unit spike trains could be extracted from all muscles at each torque level. Mean motor unit firing rates were significantly lower in the stroke group than in the control group for all three muscles. Within the stroke group, wrist/finger flexor motor units had the lowest coefficient of variation. Additionally, modulation of mean firing rates across torque levels was significantly impaired in all three paretic muscles. The implications of these findings and overall impact of this approach are discussed.

  3. Dynamic tension EMG to characterize the effects of DBS treatment of advanced Parkinson's disease.

    PubMed

    Ruonala, V; Pekkonen, E; Rissanen, S; Airaksinen, O; Miroshnichenko, G; Kankaanpää, M; Karjalainen, P

    2014-01-01

    Deep brain stimulation (DBS) is an effective treatment method for motor symptoms of advanced Parkinson's disease. DBS-electrode is implanted to subthalamic nucleus to give precisely allocated electrical stimuli to brain. The optimal stimulus type has to be adjusted individually. Disease severity, main symptoms and biological factors play a role in correctly setting up the device. Currently there are no objective methods to assess the efficacy of DBS, hence the adjustment is based solely on clinical assessment. In optimal case an objectively measurable feature would point the right settings of DBS. Surface electromyographic and kinematic measurements have been used in Parkinson's disease research. As Parkinson's disease symptoms are known to change the EMG signal properties, these methods could be helpful aid in the clinical adjustment of DBS. In this study, 13 patients with advanced Parkinson's disease who received DBS treatment were measured. The patients were measured with seven different settings of the DBS in clinical range including changes in stimulation amplitude, frequency and pulse width. The EMG analysis was based on parameters that characterize EMG signal morphology. Correlation dimension and recurrence rate made the most significant difference in relation to optimal settings. In conclusion, EMG analysis is able to detect differences between the DBS setups, and can help in finding the correct parameters.

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

    PubMed

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

    2017-09-13

    Conditional trans-rectal stimulation of the pudendal nerve could provide a viable solution to treat hyperreflexive bladder in spinal cord injury. A set threshold of the amplitude estimate of the external anal sphincter surface electromyography (sEMG) may be used as the trigger signal. The efficacy of such a device should be tested in a large scale clinical trial. As such a probe should remain in situ for several hours while patients attend to their daily routine, the recording electrodes should be designed to be large enough to maintain good contact while observing design constraints. The objective of this study was to arrive at a design for intra-anal sEMG recording electrodes for the subsequent clinical trials while deriving the possible recording and processing parameters. Approach: Having in mind existing solutions and based on theoretical and anatomical considerations, a set of four multi-electrode probes were designed and developed. These were tested in a healthy subject and the measured sEMG traces were recorded and appropriately processed. Main results: It was shown that while comparatively large electrodes record sEMG traces that are not sufficiently correlated with the external anal sphincter contractions, smaller electrodes may not maintain a stable electrode tissue contact. It was shown that 3 mm wide and 1 cm long electrodes with 5 mm inter-electrode spacing, in agreement with Nyquist sampling, placed 1 cm from the orifice may intra-anally record a sEMG trace sufficiently correlated with external anal sphincter activity. Significance: The outcome of this study can be used in any biofeedback, treatment or diagnostic application where the activity of the external anal sphincter sEMG should be detected for an extended period of time. . © 2017 Institute of Physics and Engineering in Medicine.

  5. Local Wavelet-Based Filtering of Electromyographic Signals to Eliminate the Electrocardiographic-Induced Artifacts in Patients with Spinal Cord Injury

    PubMed Central

    Nitzken, Matthew; Bajaj, Nihit; Aslan, Sevda; Gimel’farb, Georgy; Ovechkin, Alexander

    2013-01-01

    Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorders associated with motor control deficits. However, EMG potentials recorded from these muscles are often contaminated with heart-induced electrocardiographic (ECG) signals. Elimination of these artifacts plays a critical role in the precise measure of the respiratory muscle electrical activity. This study was undertaken to find an optimal approach to eliminate the ECG artifacts from EMG recordings. Conventional global filtering can be used to decrease the ECG-induced artifact. However, this method can alter the EMG signal and changes physiologically relevant information. We hypothesize that, unlike global filtering, localized removal of ECG artifacts will not change the original EMG signals. We develop an approach to remove the ECG artifacts without altering the amplitude and frequency components of the EMG signal by using an externally recorded ECG signal as a mask to locate areas of the ECG spikes within EMG data. These segments containing ECG spikes were decomposed into 128 sub-wavelets by a custom-scaled Morlet Wavelet Transform. The ECG-related sub-wavelets at the ECG spike location were removed and a de-noised EMG signal was reconstructed. Validity of the proposed method was proven using mathematical simulated synthetic signals and EMG obtained from SCI patients. We compare the Root-mean Square Error and the Relative Change in Variance between this method, global, notch and adaptive filters. The results show that the localized wavelet-based filtering has the benefit of not introducing error in the native EMG signal and accurately removing ECG artifacts from EMG signals

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  7. Variation in EMG activity: a hierarchical approach

    PubMed Central

    German, Rebecca Z.; Crompton, A. W.; Thexton, A. J.

    2008-01-01

    Recordings of naturally occurring Electromyographic (EMG) signals are variable. One of the first formal and successful attempts to quantify variation in EMG signals was Shaffer and Lauder's (1985) study examining several levels of variation but not within muscle. The goal of the current study was to quantify the variation that exists at different levels, using more detailed measures of EMG activity than did Shaffer and Lauder (1985). The importance of accounting for different levels of variation in an EMG study is both biological and statistical. Signal variation within the same muscle for a stereotyped action suggests that each recording represents a sample drawn from a pool of a large number of motor units that, while biologically functioning in an integrated fashion, showed statistical variation. Different levels of variation for different muscles could be related to different functions or different tasks of those muscles. The statistical impact of unaccounted or inappropriately analyzed variation can lead to false rejection (type I error) or false acceptance (type II error) of the null hypothesis. Type II errors occur because such variation will accrue to the error, reducing power, and producing an artificially low F-value. Type I errors are associated with pseudoreplication, in which the replicated units are not truly independent, thereby leading to inflated degrees of freedom, and an underestimate of the error mean square. To address these problems, we used a repeated measures, nested multifactor model to measure the relative contribution of different hierarchical levels of variation to the total variation in EMG signals during swallowing. We found that variation at all levels, among electrodes in the same muscle, in sequences of the same animal, and among individuals and between differently named muscles, was significant. These findings suggest that a single intramuscular electrode, recording from a limited sample of the motor units, cannot be relied upon to

  8. Analysis of dynamic EMG and acceleration measurements in Parkinson's disease.

    PubMed

    Rissanen, Saara M; Kankaanpaa, Markku; Tarvainen, Mika P; Meigal, Alexander; Nuutinen, Juho; Tarkka, Ina M; Airaksinen, Olavi; Karjalainen, Pasi A

    2008-01-01

    In this paper, we bring out modern methods that are potential in analysing differences in the dynamic surface electromyographic (EMG) and acceleration measurements between patients with Parkinson's disease (PD) and healthy persons. These methods are the correlation dimension of EMG, the recurrence rate of EMG, the power of acceleration and the sample entropy of acceleration. In this study, these methods were used to extract features from surface EMG and acceleration recordings measured during elbow flexion and extension movements. The extracted features were used to form high-dimensional feature vectors and the dimensionality of these vectors was then reduced by using the principal component approach. Finally, the feature vectors were discriminated between subjects by using the principal components. The discrimination power of the presented approach was tested with EMG and acceleration data measured from 46 patients with PD (on-medication) and 59 healthy controls. Discrimination results showed that the present method was able to discriminate dynamic EMG and acceleration recordings between patients with PD and healthy controls. Therefore, dynamic surface EMG and acceleration measurements may have potential in the objective and quantitative assessment and diagnosis of PD.

  9. Re-examination of the surface EMG activity of the masseter muscle in young adults during chewing of two test foods.

    PubMed

    Karkazis, H C; Kossioni, A E

    1997-03-01

    The purpose of this study was to investigate the effect of the texture of food on the masseter EMG activity during chewing. Fresh raw carrots and non-adhesive chewing gums of similar size and weight were used as representing a hard and a soft food respectively. The mean values for the IEMG activity, the duration of the chewing cycle, the chewing rate and the relative contraction time during chewing were significantly higher for the carrots while no significant difference was found in the chewing burst duration between the two test foods. Finally a strong inverse correlation was found between chewing rate and cycle duration. It was concluded that the texture of food has an obvious effect on EMG activity during chewing and that adjustments to changes in food consistency are made mainly by altering the chewing rate, the duration of the chewing cycle and the IEMG activity.

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

    SciTech Connect

    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.

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

    NASA Astrophysics Data System (ADS)

    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

  12. Non-Linear EMG Parameters for Differential and Early Diagnostics of Parkinson's Disease.

    PubMed

    Meigal, Alexander Y; Rissanen, Saara M; Tarvainen, Mika P; Airaksinen, Olavi; Kankaanpää, Markku; Karjalainen, Pasi A

    2013-01-01

    The pre-clinical diagnostics is essential for management of Parkinson's disease (PD). Although PD has been studied intensively in the last decades, the pre-clinical indicators of that motor disorder have yet to be established. Several approaches were proposed but the definitive method is still lacking. Here we report on the non-linear characteristics of surface electromyogram (sEMG) and tremor acceleration as a possible diagnostic tool, and, in prospective, as a predictor for PD. Following this approach we calculated such non-linear parameters of sEMG and accelerometer signal as correlation dimension, entropy, and determinism. We found that the non-linear parameters allowed discriminating some 85% of healthy controls from PD patients. Thus, this approach offers considerable potential for developing sEMG-based method for pre-clinical diagnostics of PD. However, non-linear parameters proved to be more reliable for the shaking form of PD, while diagnostics of the rigid form of PD using EMG remains an open question.

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

    PubMed Central

    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

  14. Establishment of a recording method for surface electromyography in the iliopsoas muscle.

    PubMed

    Jiroumaru, Takumi; Kurihara, Toshiyuki; Isaka, Tadao

    2014-08-01

    We examined the availability and reliability of surface electromyography (EMG) signals from the iliopsoas muscle (IL). Using serial magnetic resonance images from fifty healthy young males, we evaluated whether the superficial region of IL was adequate for attaching surface EMG electrodes. Subsequently, we assessed EMG cross-talk from the sartorius muscle (SA)-the nearest to IL-using a selective cooling method in fourteen subjects. The skin above SA was cooled, and the median frequencies of EMG signals from IL and SA were determined. The maximum voluntary contraction during isometric hip flexion was measured before and after selective cooling, and surface EMG signals from SA and IL were measured. The superficial area of IL was adequately large (13.2±2.7cm(2)) for recording surface EMG in all fifty subjects. The maximum perimeter for the medial-lateral skin facing IL was noted at a level 3-5cm distal to the anterior superior iliac spine. Following cooling, the median frequency for SA decreased significantly (from 70.1 to 51.9Hz, p<0.001); however, that for IL did not alter significantly. These results demonstrated that EMG cross-talk from SA was negligible for surface EMG signals from IL during hip flexion.

  15. The EMG of conventional abdominal exercise and exercise with a semi-upright commercial device: comparative effects and technique considerations.

    PubMed

    Olson, M S; Esco, M R; Williford, H

    2008-03-01

    The purpose of this study was to measure and compare the muscle activity of the rectus abdominis (RA) and external obliques (EO) with conventional exercises and while using an upright commercial abdominal training device (the CoreMaster). It was hypothesized that the upright device would elicit higher electromyography (EMG) values compared to conventional abdominal exercises. Fifteen subjects (8 males, 7 females) participated in this study. Each subject performed 10 repetitions for 5 exercises: truck lift (TL); trunk rotation to opposite knee (TROK); trunk lift on the CoreMaster (TLCM); trunk rotation on the CoreMaster (TRCM); and trunk rotation with a leg lift on the CoreMaster (TRLLCM). Muscle activity was measured for the RA and EO using surface EMG. A Biopac system (Goleta, CA, USA) processed the EMG signals. A repeated measures analysis of variance (ANOVA) determined any difference in the root mean square values and Bonferroni comparisons were used to clarify the order of differences (P<0.05). For the RA, all exercises on the CoreMaster produced significantly higher EMG values compared to the conventional TL. For the EO, TRCM elicited the highest EMG values. However, no significant difference was found for EO between TROK and TRLLCM. The CoreMaster elicited a greater challenge to the RA. For the EO, the CoreMaster yielded optimal effects for exercises that required pronounced rotation.

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

    PubMed

    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.

  17. Empirical mode decomposition as a tool to remove the function electrical stimulation artifact from surface electromyograms: preliminary investigation.

    PubMed

    Pilkar, Rakesh B; Yarossi, Mathew; Forrest, Gail

    2012-01-01

    Rectification of surface EMGs during electrical stimulations (ES) is still a problem to be solved. The broad band frequency components of ES artifact overlap with the EMG spectrum, make this task challenging. In this study, we investigate the potential use of empirical mode decomposition (EMD) method to remove the stimulus artifact from surface EMGs collected during such applications. We hypothesize that the EMD algorithm provides a suitable platform for decomposing the EMG signal into physically meaningful intrinsic modes which can be used to isolate ES artifact. Basic EMD is tested on two signals - ES induced EMG and EMG of voluntary contractions added with simulated ES signal. The algorithm isolates the EMG from ES artifact with considerable success. Further, the EMD method along with the energy operator -TKEO gives even better representation of the EMG signal. However, some high frequency data was lost during reconstruction process. Hence, there is further need to investigate the relationship between the EMD parameters and stimulus artifact properties so that the algorithm can be optimized to reconstruct pure artifact free EMG signal with minimum lost of data.

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

    NASA Astrophysics Data System (ADS)

    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

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

    PubMed

    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.

  20. [Electromyographic (EMG) electrode impedance and EMG activity from anterior temporal muscle and masseter muscle].

    PubMed

    Takarada, T; Alvarado Larrinaga, G; Nishida, F; Nishino, M

    1989-01-01

    The value and change with time of the impedance of surface EMG electrodes and the effects of their difference between the bipolar electrodes on the electromyographic activity from the anterior temporal muscle and the masseter muscle in six adult male subjects with normal occlusion were studied. The results were as follows: 1. In the anterior temporal muscle, if the impedance of the electrode was under 20 k omega it was stable from just after the electrode disc was applied to the skin. In the masseter muscle, if the impedance was under 30 k omega it became stable within two minutes after the electrode was applied. 2. The difference of impedance between the bipolar EMG electrodes did not correlate with EMG activity.

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

    PubMed Central

    2013-01-01

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

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

    PubMed

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

    2014-08-14

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

  3. Linearity and reliability of the EMG amplitude versus dynamic torque relationships for the superficial quadriceps femoris muscles.

    PubMed

    Stock, M S; Beck, T W; DeFreitas, J M; Dillon, M A

    2010-03-01

    The purpose of the present investigation was to determine the linearity and reliability of the electromyographic (EMG) amplitude versus dynamic torque relationships for the vastus lateralis (VL), rectus femoris (RF), and vastus medialis (VM). Nine healthy men (mean +/- SD age = 25.3 +/- 4.7 years) and eleven healthy women (mean +/- SD age = 22.0 +/- 1.3 years) performed a series of randomly ordered, submaximal to maximal, concentric isokinetic muscle actions of the leg extensors at 30 degrees x s(1) on two occasions separated by at least 48 hours. During each muscle action, surface EMG signals were detected from the VL, RF and VM of the dominant thigh with bipolar surface electrode arrangements. The coefficients of determination for the EMG amplitude versus dynamic torque relationships ranged from r2 = 0.75-0.98 and 0.64-0.99 for the VL, r2 = 0.79-0.99 and 0.60-0.98 for the RFE and r2 = 0.44-0.98 and 0.51-0.98 for the VM for trials 1 and2, respectively. In some cases, the linear EMG amplitude versus torque slope coefficient for trial 1 was significantly different from that for trial 2 for the VL and RF, but not for the VM. The intraclass correlation coefficients for the linear EMG amplitude versus torque coefficients were 0.730 (VL), 0.709 (RF), and 0.888 (VM). These results indicated that the EMG amplitude versus dynamic torque relationships for the superficial quadriceps femoris muscles did not demonstrate enough linearity and reliability to be used for examining the contributions of neural versus hypertrophic factors to training-induced strength gains.

  4. The role of EMG awareness in EMG biofeedback learning.

    PubMed

    Segreto, J

    1995-06-01

    Underlying most research on biofeedback learning is a theoretical model of the processes involved. The current study tested a prediction from the Awareness Model: High initial EMG awareness should facilitate response control during EMG biofeedback training. Seventy-two undergraduates were assessed for forehead EMG awareness by asking them to produce target responses from 1.0 to 5.0 microV every 15 s for 16 trials. Based on this assessment, two groups (high and low awareness) were trained for 64 trials to produce these target levels with either EMG biofeedback, practice (no feedback), or noncontingent EMG feedback. A transfer task was identical to the initial assessment. During training, the biofeedback group deviated less from target than the practice and noncontingent groups. The biofeedback group was the only group to improve from initial EMG awareness activity. During transfer, only the low awareness biofeedback group remained below initial EMG awareness level. These findings can be interpreted in terms of the Two-Process Model.

  5. Daily behavior identification based on sEMG

    NASA Astrophysics Data System (ADS)

    Wang, Zhongwei; Shi, Yuliang

    2017-08-01

    This paper presents a daily behavior identification algorithm based on sEMG to improve the accuracy of behavior identification. In the preprocessing stage, the original sEMG signal is effectively denoised by the combination of EMD denoising and wavelet denoising. In the feature extraction stage, the characteristics of MAV and AR model are extracted by time-frequency domain to express the behavior patterns. In the behavior classification stage, 8 features from 4 sEMG channels of MAV and AR model are use an input neurons of the BP neural network to improve the accuracy of behavior classification identification. Through the learning of a large number of training samples, the accuracy of the behavioral identification on the test samples comes to 91.02% in the experiment, which indicates that the daily behavior identification based on sEMG is a valuable method.

  6. Real time simultaneous and proportional control of multiple degrees of freedom from surface EMG: Preliminary results on subjects with limb deficiency.

    PubMed

    Rehbaum, Hubertus; Jiang, Ning; Paredes, Liliana; Amsuess, Sebastian; Graimann, Bernhard; Farina, Dario

    2012-01-01

    We present the real time simultaneous and proportional control of two degrees of freedom (DoF), using surface electromyographic signals from the residual limbs of three subject with limb deficiency. Three subjects could control a virtual object in two dimensions using their residual muscle activities to achieve goal-oriented tasks. The subjects indicated that they found the control intuitive and useful. These results show that such a simultaneous and proportional control paradigm is a promising direction for multi-functional prosthetic control.

  7. The role of masseter muscle EMG during DISE to predict the effectiveness of MAD: preliminary results.

    PubMed

    Marchese, M R; Scarano, E; Rizzotto, G; Grippaudo, C; Paludetti, G

    2016-12-01

    The use of a mandibular advancement device (MAD) increases the activity of the temporo-mandibular (TM) complex and masseter (MM) muscles with the risk of reducing treatment compliance. Predictors of treatment outcome are of importance in selecting patients who might benefit from MAD without side effects. The role of mandibular advancement (MA) during drug-induced sleep endoscopy (DISE) is controversial. In three cases (BMI < 30) affected by non-severe OSAS (AHI < 30 e/h), we recorded the surface EMG signal of MM activity during DISE. At follow-up all cases improved the AHI, two cases that showed transient increase of MM activity did not suffer from changes of overjet and did not complain of discomfort with the use of MAD. The case that showed a continuing increase of MM activity reported TM discomfort without changes of dental occlusion. EMG of MM during DISE may contribute to ameliorate the selection of cases amenable to treatment with MAD.

  8. Evolved pseudo-wavelet function to optimally decompose sEMG for automated classification of localized muscle fatigue.

    PubMed

    Al-Mulla, Mohamed R; Sepulveda, Francisco; Colley, M

    2011-05-01

    The purpose of this study was to develop an algorithm for automated muscle fatigue detection in sports related scenarios. Surface electromyography (sEMG) of the biceps muscle was recorded from ten subjects performing semi-isometric (i.e., attempted isometric) contraction until fatigue. For training and testing purposes, the signals were labelled in two classes (Non-Fatigue and Fatigue), with the labelling being determined by a fuzzy classifier using elbow angle and its standard deviation as inputs. A genetic algorithm was used for evolving a pseudo-wavelet function for optimising the detection of muscle fatigue on any unseen sEMG signals. Tuning of the generalised evolved pseudo-wavelet function was based on the decomposition of twenty sEMG trials. After completing twenty independent pseudo-wavelet evolution runs, the best run was selected and then tested on ten previously unseen sEMG trials to measure the classification performance. Results show that an evolved pseudo-wavelet improved the classification of muscle fatigue between 7.31% and 13.15% when compared to other wavelet functions, giving an average correct classification of 88.41%.

  9. [Frequency analysis of the EMG power spectrum of the anterior temporal and masseter muscles in children and adults].

    PubMed

    Takarada, T; Alvarado Larrinaga, G; Nishida, F; Nishino, M

    1989-01-01

    For the investigation of the functional change of the masticatory muscles along with growth and development, the frequency analysis of the EMG power spectrum was carried out. The subjects were 6 children (5 males and 1 female) with full deciduous dentition (Hellman's dental age IIA) aged 4.5 +/- 0.2 years and 6 adults (4 males and 2 females) with full permanent dentition aged 27.7 +/- 3.8 years. EMG signals were recorded bilaterally by means of bipolar silver surface electrodes from the anterior temporal and masseter muscles when the subjects were chewing chewing gum or performing maximum clenches in the intercuspal position. A fast Fourier transform (FFT) algorithm was used to obtain the power spectrum of the EMG signal. As the total power value from 62.5 to 1000 Hz was 100 per cent, the mean frequencies at 25, 50, 75 and 90 per cent of the cumulative power were calculated. The results were as follows: 1. The mean frequencies at each ratio of the cumulative power were age-dependent and EMG power spectrum patterns significantly shifted to lower frequencies in the muscles of the adults. 2. No statistically significant differences between the chewing and clenching, the anterior temporal and masseter muscle and the left and right side were observed in each group.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

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

    2013-01-01

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

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

    NASA Technical Reports Server (NTRS)

    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.

  13. A sparse Bayesian learning based scheme for multi-movement recognition using sEMG.

    PubMed

    Ding, Shuai; Wang, Liang

    2016-03-01

    This paper proposed a feature extraction scheme based on sparse representation considering the non-stationary property of surface electromyography (sEMG). Sparse Bayesian learning was introduced to extract the feature with optimal class separability to improve recognition accuracy of multi-movement patterns. The extracted feature, sparse representation coefficients (SRC), represented time-varying characteristics of sEMG effectively because of the compressibility (or weak sparsity) of the signal in some transformed domains. We investigated the effect of the proposed feature by comparing with other fourteen individual features in offline recognition. The results demonstrated the proposed feature revealed important dynamic information in the sEMG signals. The multi-feature sets formed by the SRC and other single feature yielded more superior performance on recognition accuracy, compared with the single features. The best average recognition accuracy of 94.33% was gained by using SVM classifier with the multi-feature set combining the feature SRC, Williston amplitude (WAMP), wavelength (WL) and the coefficients of the fourth order autoregressive model (ARC4) via multiple kernel learning framework. The proposed feature extraction scheme (known as SRC + WAMP + WL + ARC4) is a promising method for multi-movement recognition with high accuracy.

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

    PubMed

    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.

  15. Influence of muscle fibre shortening on estimates of conduction velocity and spectral frequencies from surface electromyographic signals.

    PubMed

    Schulte, E; Farina, D; Merletti, R; Rau, G; Disselhorst-Klug, C

    2004-07-01

    The study of surface electromyographic (EMG) signals under dynamic contractions is becoming increasingly important. However, knowledge of the methodological issues that may affect such analysis is still limited. The aim of the study was to analyse the effect of fibre shortening on estimates of conduction velocity (CV) and mean power spectral frequency (MNF) from surface EMG signals. Single fibre action potentials were simulated, as detected by commonly used spatial filters, for different fibre lengths. No physiological modifications were included with changes in fibre length, and thus only geometrical artifacts related to fibre shortening were investigated. The simulation results showed that the dependence of CV and MNF on fibre shortening is affected by the fibre location, electrode position and the spatial filter applied. With shortening of up to 50% for a fibre of 50 mm semi-length, the variations in CV and MNF estimates with shortening in bipolar recordings were 0.5% (CV) and 0.7% (MNF) for superficial fibres, and 3.6% and 5.1% for deeper fibres. Using the longitudinal double differential filter, under the same conditions, the percent variation was 0% and 0.2%, and 24.7% and 15.8%, respectively. The main conclusions were, first, muscle fibre shortening can significantly affect estimates of CV and MNF, especially for short fibre lengths. However, for long (semi-length >50 mm) and superficial fibres, this effect is limited for shortenings of up to 50% of the initial fibre length. Secondly, CV and MNF are almost equally affected by changes in muscle length; and, thirdly, sensitivity to fibre shortening depends on the spatial filter applied for signal detection.

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

    PubMed

    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.

  17. Application of singular spectrum-based change-point analysis to EMG-onset detection.

    PubMed

    Vaisman, Lev; Zariffa, José; Popovic, Milos R

    2010-08-01

    While many approaches have been proposed to identify the signal onset in EMG recordings, there is no standardized method for performing this task. Here, we propose to use a change-point detection procedure based on singular spectrum analysis to determine the onset of EMG signals. This method is suitable for automated real-time implementation, can be applied directly to the raw signal, and does not require any prior knowledge of the EMG signal's properties. The algorithm proposed by Moskvina and Zhigljavsky (2003) was applied to EMG segments recorded from wrist and trunk muscles. Wrist EMG data was collected from 9 Parkinson's disease patients with and without tremor, while trunk EMG data was collected from 13 healthy able-bodied individuals. Along with the change-point detection analysis, two threshold-based onset detection methods were applied, as well as visual estimates of the EMG onset by trained practitioners. In the case of wrist EMG data without tremor, the change-point analysis showed comparable or superior frequency and quality of detection results, as compared to other automatic detection methods. In the case of wrist EMG data with tremor and trunk EMG data, performance suffered because other changes occurring in these signals caused larger changes in the detection statistic than the changes caused by the initial muscle activation, suggesting that additional criteria are needed to identify the onset from the detection statistic other than its magnitude alone. Once this issue is resolved, change-point detection should provide an effective EMG-onset detection method suitable for automated real-time implementation.

  18. Blind separation of convolutive sEMG mixtures based on independent vector analysis

    NASA Astrophysics Data System (ADS)

    Wang, Xiaomei; Guo, Yina; Tian, Wenyan

    2015-12-01

    An independent vector analysis (IVA) method base on variable-step gradient algorithm is proposed in this paper. According to the sEMG physiological properties, the IVA model is applied to the frequency-domain separation of convolutive sEMG mixtures to extract motor unit action potentials information of sEMG signals. The decomposition capability of proposed method is compared to the one of independent component analysis (ICA), and experimental results show the variable-step gradient IVA method outperforms ICA in blind separation of convolutive sEMG mixtures.

  19. Influence of posture on the relation between surface electromyogram amplitude and back muscle moment: consequences for the use of surface electromyogram to measure back load.

    PubMed

    Mouton, L J; Hof, A L; de Jongh, H J; Eisma, W H

    1991-11-01

    The aim of the study was to analyse the effect of posture on the relation between EMG amplitude and moment of the back muscles in different subjects, in order to gain a better insight into the possibilities of EMG as a means of measuring individual back load. Eight healthy subjects participated in the experiments. Isometric back extensions were performed in three postures: upright standing, standing with the spine flexed, and upright sitting. In each posture the lumbar moments of three maximal voluntary contractions were measured and then exertions of 10 to 90% of maximal voluntary contraction (increments of 10) were performed. EMG signals from the back muscles were recorded with four pairs of surface electrodes located 3 cm and 6 cm lateral to the midline of the spine at the L3 level. EMG signals were full-wave rectified and averaged over 2 s intervals of constant moment. The results show that posture has a considerable influence on the relationship between EMG and the lumbar moment. Besides this, large individual differences and an influence of electrode position on the relationship were found. Therefore it is concluded that whenever EMG is to be used as a means to measure individual back load, a calibration of the EMG amplitude to lumbar moment ratio is necessary for each subject, each electrode position, and each posture. Interpretation of EMG amplitudes has to be done on an individual basis and taking influences of posture and electrode location on the EMG-lumbar moment relationship into account.

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

    DTIC Science & Technology

    2007-11-02

    Abstract- A control algorithm for using homogenic EMG to control external assisting torque is developed for improving the elbow capability of...sacrificing performance. Keywords - Elbow , EMG, assisting torque, stroke I. INTRODUCTION Hemiparesis, which means partial loss of muscle strength...system to increase the total torque capability of the elbow for this class of patients. The system was controlled by surface EMG of biceps and

  1. [sEMG Time-frequency analysis techniques for evaluation of muscle fatigue and it's application in ergonomic studies].

    PubMed

    Wang, Du-ming; Wang, Jian; Ge, Lie-zhong

    2003-10-01

    As a non-invasive on-line measurement, sEMG can reflect the status of muscle activity and muscle function accurately and objectively. Some sEMG Time-frequency analysis techniques, especially the JASA (joint analysis of EMG spectrum and amplitude) analysis, for evaluation of muscle fatigue in ergonomics and occupational field studies are introduced and evaluated in this paper. The sEMG signal analysis and the necessity for developing sEMG analysis techniques for field use in ergonomics are also briefly discussed.

  2. [Quantitative topographic characterization of the myoelectric activity distribution of the masseter muscle: mapping of spectral EMG parameters].

    PubMed

    Scholle, H C; Schumann, N P; Anders, C; Mey, E

    1992-09-01

    A new method for quantitative characterization of myoelectrical masseter activity distribution by mapping of spectral EMG-parameters is described. The surface electromyograms of M. masseter were monopolarly recorded (16 channels). On the basis of registered EMG intervals (512 ms) the spectral EMG power of several frequency bands was calculated (Fast Fourier Transformation). The spectral EMG parameters between the 16 electrode positions were estimated by linear interpolation (4-nearest neighbours algorithm). Afterwards the spectral EMG parameters were fitted in a grey-tone or colour scale with 10 intervals. The so obtained EMG activity maps ("EMG-Maps") permit a quantitative-topographic characterization of myoelectrical masseter activity during different functional load procedures. The frequency range which is to consider in masseter surface-EMG investigations encloses frequencies between 15 and 500 Hz. The topography of EMG activation pattern of M. masseter is only described in a comprehensive manner when the electrode array consists of 16 electrodes and more. During defined motor tasks like clenching with controlled forces the reproducibility of EMG-Maps which respect to the topography of EMG activity pattern is very high. The absolute values of spectral EMG power as well as power changes of selected band ranges during clenching correlate to the extent of chewing forces.

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

    PubMed Central

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

    2015-01-01

    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. PMID:26180124

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

    PubMed

    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.

  5. Re-evaluation of EMG-torque relation in chronic stroke using linear electrode array EMG recordings.

    PubMed

    Bhadane, Minal; Liu, Jie; Rymer, W Zev; Zhou, Ping; Li, Sheng

    2016-06-28

    The objective was to re-evaluate the controversial reports of EMG-torque relation between impaired and non-impaired sides using linear electrode array EMG recordings. Ten subjects with chronic stroke performed a series of submaximal isometric elbow flexion tasks. A 20-channel linear array was used to record surface EMG of the biceps brachii muscles from both impaired and non-impaired sides. M-wave recordings for bilateral biceps brachii muscles were also made. Distribution of the slope of the EMG-torque relations for the individual channels showed a quasi-symmetrical "M" shaped pattern. The lowest value corresponded to the innervation zone (IZ) location. The highest value from the slope curve for each side was selected for comparison to minimize the effect of electrode placement and IZ asymmetry. The slope was greater on the impaired side in 4 of 10 subjects. There were a weak correlation between slope ratio and strength ratio and a moderate to high correlation between slope ratio and M-wave ratio between two sides. These findings suggest that the EMG-torque relations are likely mediated and influenced by multiple factors. Our findings emphasize the importance of electrode placement and suggest the primary role of peripheral adaptive changes in the EMG-torque relations in chronic stroke.

  6. Re-evaluation of EMG-torque relation in chronic stroke using linear electrode array EMG recordings

    PubMed Central

    Bhadane, Minal; Liu, Jie; Rymer, W. Zev; Zhou, Ping; Li, Sheng

    2016-01-01

    The objective was to re-evaluate the controversial reports of EMG-torque relation between impaired and non-impaired sides using linear electrode array EMG recordings. Ten subjects with chronic stroke performed a series of submaximal isometric elbow flexion tasks. A 20-channel linear array was used to record surface EMG of the biceps brachii muscles from both impaired and non-impaired sides. M-wave recordings for bilateral biceps brachii muscles were also made. Distribution of the slope of the EMG-torque relations for the individual channels showed a quasi-symmetrical “M” shaped pattern. The lowest value corresponded to the innervation zone (IZ) location. The highest value from the slope curve for each side was selected for comparison to minimize the effect of electrode placement and IZ asymmetry. The slope was greater on the impaired side in 4 of 10 subjects. There were a weak correlation between slope ratio and strength ratio and a moderate to high correlation between slope ratio and M-wave ratio between two sides. These findings suggest that the EMG-torque relations are likely mediated and influenced by multiple factors. Our findings emphasize the importance of electrode placement and suggest the primary role of peripheral adaptive changes in the EMG-torque relations in chronic stroke. PMID:27349938

  7. A Spectral Analysis of Rotator Cuff Musculature Electromyographic Activity: Surface and Indwelling

    PubMed Central

    Tomlinson, Daniel P.; Vanadurongwan, Bavornrat; Lenhoff, Mark W.; Cordasco, Frank A.; Chehab, Eric L.; Adler, Ronald S.; Henn, R. Frank; Hillstrom, Howard J.

    2010-01-01

    Electromyography (EMG) of the shoulder girdle is commonly performed; however, EMG spectral properties of shoulder muscles have not been clearly defined. The purpose of this study was to determine the maximum power frequency, Nyquist rate, and minimum sampling rate for indwelling and surface EMG of the normal shoulder girdle musculature. EMG signals were recorded using indwelling electrodes for the rotator cuff muscles and surface electrodes for ten additional shoulder muscles in ten healthy volunteers. A fast Fourier transform was performed on the raw EMG signal collected during maximal isometric contractions to derive the power spectral density. The 95% power frequency was calculated during the ramp and plateau subphase of each contraction. Data were analyzed with analysis of variance (ANOVA) and paired t tests. Indwelling EMG signals had more than twice the frequency content of surface EMG signals (p < .001). Mean 95% power frequencies ranged from 495 to 560 Hz for indwelling electrodes and from 152 to 260 Hz for surface electrodes. Significant differences in the mean 95% power frequencies existed among muscles monitored with surface electrodes (p = .002), but not among muscles monitored with indwelling electrodes (p = .961). No significant differences in the 95% power frequencies existed among contraction subphases for any of the muscle–electrode combinations. Maximum Nyquist rate was 893 Hz for surface electrodes and 1,764 Hz for indwelling electrodes. Our results suggest that when recording EMG of shoulder muscles, the minimum sampling frequency is 1,340 Hz for surface electrodes and 2,650 Hz for indwelling electrodes. The minimum sampling recommendations are higher than the 1,000 Hz reported in many studies involving EMG of the shoulder. PMID:22294954

  8. The relation between the surface electromyogram and muscular force.

    PubMed Central

    Milner-Brown, H S; Stein, R B

    1975-01-01

    1. Motor units in the first dorsal interosseus muscle of normal human subjects were recorded by needle electrodes, together with the surface electromyogram (e.m.g.). The wave form contributed by each motor unit to the surface e.m.g. was determined by signal averaging. 2. The peak-to-peak amplitude of the wave form contributed to the surface e.m.g. by a motor unit increased approximately as the square root of the threshold force at which the unit was recruited. The peak-to-peak duration of the wave form was independent of the threshold force. 3. Large and small motor units are uniformly distributed throughout this muscle, and the muscle fibres making up a motor unit may be widely dispersed. 4. The rectified surface e.m.g. was computed as a function of force, based on the sample of motor units recorded. The largest contribution of motor unit recruitment occurs at low force levels, while the contribution of increased firing rate becomes more important at higher force levels. 5. Possible bases for the common experimental observation that the mean rectified surface e.m.g. varies linearly with the force generated by a muscle are discussed. E.m.g. potentials and contractile responses may both sum non-linearly at moderate to high force levels, but in such a way that the rectified surface e.m.g. is still approximately linearly related to the force produced by the muscle. PMID:1133787

  9. Terrain-Moisture Classification Using GPS Surface-Reflected Signals

    NASA Technical Reports Server (NTRS)

    Grant, Michael S.; Acton, Scott T.; Katzberg, Stephen J.

    2006-01-01

    In this study we present a novel method of land surface classification using surface-reflected GPS signals in combination with digital imagery. Two GPS-derived classification features are merged with visible image data to create terrain-moisture (TM) classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding the GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping.

  10. Generating strain signals under consideration of road surface profiles

    NASA Astrophysics Data System (ADS)

    Putra, T. E.; Abdullah, S.; Schramm, D.; Nuawi, M. Z.; Bruckmann, T.

    2015-08-01

    The current study aimed to develop the mechanism for generating strain signal utilising computer-based simulation. The strain data, caused by the acceleration, were undertaken from a fatigue data acquisition involving car movements. Using a mathematical model, the measured strain signals yielded to acceleration data used to describe the bumpiness of road surfaces. The acceleration signals were considered as an external disturbance on generating strain signals. Based on this comparison, both the actual and simulated strain data have similar pattern. The results are expected to provide new knowledge to generate a strain signal via a simulation.

  11. Are External Knee Load and EMG Measures Accurate Indicators of Internal Knee Contact Forces during Gait?

    PubMed Central

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

    2013-01-01

    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 EMG signals) would be clinically valuable. This study quantifies 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. PMID:23280647

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

    PubMed

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

    2016-08-02

    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.

  13. EMG (Electromyography) (For Parents)

    MedlinePlus

    ... causes the muscle to contract, or tighten. The muscle contraction itself produces electrical signals. For the purpose of ... three kinds of diseases that interfere with normal muscle contraction: diseases of the muscle itself (most commonly, muscular ...

  14. Design of a robust EMG sensing interface for pattern classification

    NASA Astrophysics Data System (ADS)

    Huang, He; Zhang, Fan; Sun, Yan L.; He, Haibo

    2010-10-01

    Electromyographic (EMG) pattern classification has been widely investigated for neural control of external devices in order to assist with movements of patients with motor deficits. Classification performance deteriorates due to inevitable disturbances to the sensor interface, which significantly challenges the clinical value of this technique. This study aimed to design a sensor fault detection (SFD) module in the sensor interface to provide reliable EMG pattern classification. This module monitored the recorded signals from individual EMG electrodes and performed a self-recovery strategy to recover the classification performance when one or more sensors were disturbed. To evaluate this design, we applied synthetic disturbances to EMG signals collected from leg muscles of able-bodied subjects and a subject with a transfemoral amputation and compared the accuracies for classifying transitions between different locomotion modes with and without the SFD module. The results showed that the SFD module maintained classification performance when one signal was distorted and recovered about 20% of classification accuracy when four signals were distorted simultaneously. The method was simple to implement. Additionally, these outcomes were observed for all subjects, including the leg amputee, which implies the promise of the designed sensor interface for providing a reliable neural-machine interface for artificial legs.

  15. Design of a robust EMG sensing interface for pattern classification.

    PubMed

    Huang, He; Zhang, Fan; Sun, Yan L; He, Haibo

    2010-10-01

    Electromyographic (EMG) pattern classification has been widely investigated for neural control of external devices in order to assist with movements of patients with motor deficits. Classification performance deteriorates due to inevitable disturbances to the sensor interface, which significantly challenges the clinical value of this technique. This study aimed to design a sensor fault detection (SFD) module in the sensor interface to provide reliable EMG pattern classification. This module monitored the recorded signals from individual EMG electrodes and performed a self-recovery strategy to recover the classification performance when one or more sensors were disturbed. To evaluate this design, we applied synthetic disturbances to EMG signals collected from leg muscles of able-bodied subjects and a subject with a transfemoral amputation and compared the accuracies for classifying transitions between different locomotion modes with and without the SFD module. The results showed that the SFD module maintained classification performance when one signal was distorted and recovered about 20% of classification accuracy when four signals were distorted simultaneously. The method was simple to implement. Additionally, these outcomes were observed for all subjects, including the leg amputee, which implies the promise of the designed sensor interface for providing a reliable neural-machine interface for artificial legs.

  16. Modulation of photoacoustic signal generation from metallic surfaces

    PubMed Central

    Mitcham, Trevor; Homan, Kimberly; Frey, Wolfgang; Chen, Yun-Sheng; Emelianov, Stanislav; Hazle, John

    2013-01-01

    Abstract. The ability to image metallic implants is important for medical applications ranging from diagnosis to therapy. Photoacoustic (PA) imaging has been recently pursued as a means to localize metallic implants in soft tissue. The work presented herein investigates different mechanisms to modulate the PA signal generated by macroscopic metallic surfaces. Wires of five different metals are tested to simulate medical implants/tools, while surface roughness is altered or physical vapor deposition (PVD) coatings are added to change the wires’ overall optical absorption. PA imaging data of the wires are acquired at 970 nm. Results indicate that PA signal generation predominately occurs in a wire’s metallic surface and not its aqueous surroundings. PA signal generation is similar for all metals tested, while addition of PVD coatings offers significant modulations (i.e., 4-dB enhancement and 26-dB reduction achieved) in PA signal generation. Results also suggest that PA signal increases with increasing surface roughness. Different coating and roughness schemes are then successfully utilized to generate spatial PA signal patterns. This work demonstrates the potential of surface modifications to enhance or reduce PA signal generation to permit improved PA imaging of implants/tools (i.e., providing location/orientation information) or to allow PA imaging of surrounding tissue. PMID:23652344

  17. Modulation of photoacoustic signal generation from metallic surfaces

    NASA Astrophysics Data System (ADS)

    Mitcham, Trevor; Homan, Kimberly; Frey, Wolfgang; Chen, Yun-Sheng; Emelianov, Stanislav; Hazle, John; Bouchard, Richard

    2013-05-01

    The ability to image metallic implants is important for medical applications ranging from diagnosis to therapy. Photoacoustic (PA) imaging has been recently pursued as a means to localize metallic implants in soft tissue. The work presented herein investigates different mechanisms to modulate the PA signal generated by macroscopic metallic surfaces. Wires of five different metals are tested to simulate medical implants/tools, while surface roughness is altered or physical vapor deposition (PVD) coatings are added to change the wires' overall optical absorption. PA imaging data of the wires are acquired at 970 nm. Results indicate that PA signal generation predominately occurs in a wire's metallic surface and not its aqueous surroundings. PA signal generation is similar for all metals tested, while addition of PVD coatings offers significant modulations (i.e., 4-dB enhancement and 26-dB reduction achieved) in PA signal generation. Results also suggest that PA signal increases with increasing surface roughness. Different coating and roughness schemes are then successfully utilized to generate spatial PA signal patterns. This work demonstrates the potential of surface modifications to enhance or reduce PA signal generation to permit improved PA imaging of implants/tools (i.e., providing location/orientation information) or to allow PA imaging of surrounding tissue.

  18. Monopolar electromyographic signals recorded by a current amplifier in air and under water without insulation.

    PubMed

    Whitting, John W; von Tscharner, Vinzenz

    2014-12-01

    It was recently proposed that one could use signal current instead of voltage to collect surface electromyography (EMG). With EMG-current, the electrodes remain at the ground potential, thereby eliminating lateral currents. The purpose of this study was to determine whether EMG-currents can be recorded in Tap and Salt water, as well as in air, without electrically shielding the electrodes. It was hypothesized that signals would display consistent information between experimental conditions regarding muscle responses to changes in contraction effort. EMG-currents were recorded from the flexor digitorum muscles as participant's squeezed a pre-inflated blood pressure cuff bladder in each experimental condition at standardized efforts. EMG-current measurements performed underwater showed no loss of signal amplitude when compared to measurements made in air, although some differences in amplitude and spectral components were observed between conditions. However, signal amplitudes and frequencies displayed consistent behavior across contraction effort levels, irrespective of the experimental condition. This new method demonstrates that information regarding muscle activity is comparable between wet and dry conditions when using EMG-current. Considering the difficulties imposed by the need to waterproof traditional bipolar EMG electrodes when underwater, this new methodology is tremendously promising for assessments of muscular function in aquatic environments.

  19. The influence of the type of contraction on the masseter muscle EMG power spectrum.

    PubMed

    Nadeau, S; Bilodeau, M; Delisle, A; Chmielewski, W; Arsenault, A B; Gravel, D

    1993-01-01

    Different behaviours of the EMG power spectrum across increasing force levels have been reported for the masseter muscle. A factor that could explain these different behaviours may be the type of contraction used, as was recently shown for certain upper limb muscles(5). The purpose of this study was to compare, between two types of isometric contractions, the behaviour of EMG power spectrum statistics (median frequency (MF) and mean power frequency (MPF)) obtained across increasing force levels. Ten women exerted, while biting in the intercuspal position, three 5 s ramp contractions that increased linearly from 0 to 100% of the maximal voluntary contraction (MVC). They also completed three step contractions (constant EMG amplitude) at each of the following levels: 20, 40, 60 and 80% MVC. EMG signals from the masseter muscle were recorded with miniature surface electrodes. The RMS, as well as the MPF and MF of the power spectrum were calculated at 20, 40, 60 and 80% MVC for each type of contraction. As expected, the RMS values showed similar increases with increasing levels of effort for both types of contractions. Different behaviours for both MPF (contraction(∗)force interaction, ANOVA, P<0.05) and MF (contraction(∗)force interaction, ANOVA, P>0.05) across increasing levels of effort were found between the two types of contraction. The use of step contractions gave rise to a decrease of both MPF and MF with increasing force, while the use of ramp contractions gave rise to an increase in both statistics up to at least 40% MVC followed by a decrease at higher force levels. These findings suggest that the type of contraction used does influence the behaviour of the spectral statistics across increasing force levels and that this could explain the differences obtained in previous studies for the masseter muscle. Copyright © 1993. Published by Elsevier Ltd.

  20. Digitally controlled feedback for DC offset cancellation in a wearable multichannel EMG platform.

    PubMed

    Tomasini, M; Benatti, S; Casamassima, F; Milosevic, B; Fateh, S; Farella, E; Benini, L

    2015-01-01

    Wearable systems capable to capture vital signs allow the development of advanced medical applications. One notable example is the use of surface electromyography (EMG) to gather muscle activation potentials, in principle an easy input for prosthesis control. However, the acquisition of such signals is affected by high variability and ground loop problems. Moreover, the input impedance influenced in time by motion and perspiration determines an offset, which can be orders of magnitude higher than the signal of interest. We propose a wearable device equipped with a digitally controlled Analog Front End (AFE) for biopotentials acquisition with zero-offset. The proposed AFE solution has an internal Digital to Analog Converter (DAC) used to adjust independently the reference of each channel removing any DC offset. The analog integrated circuit is coupled with a microcontroller, which periodically estimates the offset and implements a closed loop feedback on the analog part. The proposed approach was tested on EMG signals acquired from 4 subjects while performing different activities and shows that the system correctly acquires signals with no DC offset.

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

    PubMed Central

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

    2014-01-01

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

  2. Selective Linear-Regression Model for hand posture discrimination and grip force estimation using surface electromyogram signals.

    PubMed

    Yamanoi, Yusuke; Morishita, Soichiro; Kato, Ryu; Yokoi, Hiroshi

    2015-01-01

    This paper proposes the method of hand posture discrimination and grip force estimation by means of Selective Linear-Regression Model. Generally, myoelectric hands which discriminate hand posture and estimate grip force at the same time result in unsatisfying results because of complication of EMG signals. Therefore, most of myoelectric hands can control either the force or the posture. However, the proposed method is able to discriminate hand posture and to estimate grip force simultaneously while the accuracy results are achieved. In experiments, EMG signals were measured while hand posture and grip force were changing. As a result, it appears that EMG features increase monotonically with grip force. In addition, increasing forms of EMG features are different on each posture. Based on these experimental results, the authors propose the method for both discriminating hand posture and estimating grip force by means of several linear-regression models which utilize the relationship between the grip force and EMG features on each posture. To evaluate the effectiveness of this method, the failure rates of discrimination and the estimation errors of the proposed method were employed. The results indicate that failure rates and estimation errors are improved significantly.

  3. EMG-Based Neural Network Control of Transhumeral Prostheses

    PubMed Central

    Pulliam, Christopher L.; Lambrecht, Joris M.; Kirsch, Robert F.

    2013-01-01

    Upper-limb amputation can cause a great deal of functional impairment for patients, particularly for those with amputation at or above the elbow. Our long-term objective is to improve functional outcomes for patients with amputation by integrating a fully implanted electromyographic (EMG) recording system with a wireless telemetry system that communicates with the patient’s prosthesis. We believe that this should generate a scheme that will allow patients to robustly control multiple degrees of freedom simultaneously. The goal of this study is to evaluate the feasibility of predicting dynamic arm movements (both flexion/extension and pronation/supination) based on EMG signals from a set of muscles that would likely be intact in patients with transhumeral amputation. We recorded movement kinematics and EMG signals from seven muscles during a variety of movements with different complexities. Time-delayed artificial neural networks were then trained offline to predict the measured arm trajectories based on features extracted from the measured EMG signals. We evaluated the relative effectiveness of various muscle subsets. Predicted movement trajectories had average root-mean-square errors of approximately 15.7° and 24.9° and average R2 values of approximately 0.81 and 0.46 for elbow flexion/extension and forearm pronation/supination, respectively. PMID:21938659

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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

  6. Compression of surface myoelectric signals using MP3 encoding.

    PubMed

    Chan, Adrian D C

    2011-01-01

    The potential of MP3 compression of surface myoelectric signals is explored in this paper. MP3 compression is a perceptual-based encoder scheme, used traditionally to compress audio signals. The ubiquity of MP3 compression (e.g., portable consumer electronics and internet applications) makes it an attractive option for remote monitoring and telemedicine applications. The effects of muscle site and contraction type are examined at different MP3 encoding bitrates. Results demonstrate that MP3 compression is sensitive to the myoelectric signal bandwidth, with larger signal distortion associated with myoelectric signals that have higher bandwidths. Compared to other myoelectric signal compression techniques reported previously (embedded zero-tree wavelet compression and adaptive differential pulse code modulation), MP3 compression demonstrates superior performance (i.e., lower percent residual differences for the same compression ratios).

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

    PubMed

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

    2008-07-01

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

  8. Hybrid fusion of linear, non-linear and spectral models for the dynamic modeling of sEMG and skeletal muscle force: an application to upper extremity amputation.

    PubMed

    Potluri, Chandrasekhar; Anugolu, Madhavi; Schoen, Marco P; Subbaram Naidu, D; Urfer, Alex; Chiu, Steve

    2013-11-01

    Estimating skeletal muscle (finger) forces using surface Electromyography (sEMG) signals poses many challenges. In general, the sEMG measurements are based on single sensor data. In this paper, two novel hybrid fusion techniques for estimating the skeletal muscle force from the sEMG array sensors are proposed. The sEMG signals are pre-processed using five different filters: Butterworth, Chebychev Type II, Exponential, Half-Gaussian and Wavelet transforms. Dynamic models are extracted from the acquired data using Nonlinear Wiener Hammerstein (NLWH) models and Spectral Analysis Frequency Dependent Resolution (SPAFDR) models based system identification techniques. A detailed comparison is provided for the proposed filters and models using 18 healthy subjects. Wavelet transforms give higher mean correlation of 72.6 ± 1.7 (mean ± SD) and 70.4 ± 1.5 (mean ± SD) for NLWH and SPAFDR models, respectively, when compared to the other filters used in this work. Experimental verification of the fusion based hybrid models with wavelet transform shows a 96% mean correlation and 3.9% mean relative error with a standard deviation of ± 1.3 and ± 0.9 respectively between the overall hybrid fusion algorithm estimated and the actual force for 18 test subjects' k-fold cross validation data.

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

    PubMed Central

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

    2015-01-01

    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. PMID:25894941

  10. Rigorous a posteriori assessment of accuracy in EMG decomposition.

    PubMed

    McGill, Kevin C; Marateb, Hamid R

    2011-02-01

    If electromyography (EMG) decomposition is to be a useful tool for scientific investigation, it is essential to know that the results are accurate. Because of background noise, waveform variability, motor-unit action potential (MUAP) indistinguishability, and perplexing superpositions, accuracy assessment is not straightforward. This paper presents a rigorous statistical method for assessing decomposition accuracy based only on evidence from the signal itself. The method uses statistical decision theory in a Bayesian framework to integrate all the shape- and firing-time-related information in the signal to compute an objective a posteriori measure of confidence in the accuracy of each discharge in the decomposition. The assessment is based on the estimated statistical properties of the MUAPs and noise and takes into account the relative likelihood of every other possible decomposition. The method was tested on 3 pairs of real EMG signals containing 4-7 active MUAP trains per signal that had been decomposed by a human expert. It rated 97% of the identified MUAP discharges as accurate to within ± 0.5 ms with a confidence level of 99%, and detected six decomposition errors. Cross-checking between signal pairs verified all but two of these assertions. These results demonstrate that the approach is reliable and practical for real EMG signals.

  11. Accuracy of Sea Surface Topography with GPS Scattered Signals

    NASA Astrophysics Data System (ADS)

    Zuffada, C.; Zavorotny, V. U.; Lowe, S.

    2001-12-01

    The concept of using GPS reflected signals for ocean and land remote sensing is based on the use of one airborne (or space-based) GPS receiver working simultaneously with a constellation of several signal-transmitting GPS satellites. This would offer an advantage in terms of spatial coverage compared to a conventional monostatic radar system and possibly allow new scientific applications to be pursued. However, the limited power of GPS transmitters and a relatively low surface cross section would require either large receiving antennas or longer integration times to optimize the signal-to-noise ratio. Analogously to the case of a conventional radar altimeter, the reflected GPS signal acquired by the receiver is the average power versus time (a range measurement) and generally represents the contributions from surfaces which scatter incoherently. This waveform is derived as a function of viewing geometry, system parameters, surface roughness and dielectric properties of underlying covers. This work investigates the spatial-temporal coherence properties and statistics of the measured reflected GPS signal that describes variability from one sample to another. This information is needed to choose an optimal strategy for a successful signal processing. We examine the above-mentioned properties of the modeled received power as a function of surface state and scattering geometry. Its impact on the accuracy of sea surface topography, both from airborne and orbital platforms is addressed. A characterization of error and expected spatial resolution in relation to existing instruments is discussed. Furthermore, in examining the coherence time, we analyze the spectral behavior of the reflected signal versus sea state parameters, such as wind vector. In addition, we compare the predictions with data available from recent airplane measurements taken in the Pacific Ocean off the coast of Southern California obtaining preliminary validations of our models.

  12. Surface Wave Multipath Signals in Near-Field Microwave Imaging

    PubMed Central

    Meaney, Paul M.; Shubitidze, Fridon; Fanning, Margaret W.; Kmiec, Maciej; Epstein, Neil R.; Paulsen, Keith D.

    2012-01-01

    Microwave imaging techniques are prone to signal corruption from unwanted multipath signals. Near-field systems are especially vulnerable because signals can scatter and reflect from structural objects within or on the boundary of the imaging zone. These issues are further exacerbated when surface waves are generated with the potential of propagating along the transmitting and receiving antenna feed lines and other low-loss paths. In this paper, we analyze the contributions of multi-path signals arising from surface wave effects. Specifically, experiments were conducted with a near-field microwave imaging array positioned at variable heights from the floor of a coupling fluid tank. Antenna arrays with different feed line lengths in the fluid were also evaluated. The results show that surface waves corrupt the received signals over the longest transmission distances across the measurement array. However, the surface wave effects can be eliminated provided the feed line lengths are sufficiently long independently of the distance of the transmitting/receiving antenna tips from the imaging tank floor. Theoretical predictions confirm the experimental observations. PMID:22566992

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

    NASA Astrophysics Data System (ADS)

    Ren, Peng; Barreto, Armando; Adjouadi, Malek

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

  14. Surface roughness monitoring by singular spectrum analysis of vibration signals

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

    This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.

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

    PubMed

    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.

  16. 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.

    PubMed

    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 (P<.002). Lower trapezius activity was significantly higher with tape (P = .043). No significant differences were found between the tape and no tape for other muscles for the shelf task. During shoulder 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.

  17. An Experimental and Model Based Investigation of the Potential and Limitations of Surface EMG Spectral Analysis for Assessment of Motor Unit Recruitment Strategy

    DTIC Science & Technology

    2007-11-02

    Patla, “Models of recruitment and rate c oding organization in motor unit pools”, Journ. Neurophysiol., vol. 70, pp. 2470-2488, 1993 [7] E. Henneman ...corresponding to different ways for force generation b y recruitment and rate c oding) are simulated. A number of simulations are performed to study the e...signals detected experimentally during linearly increasing force c ontractions of t he biceps brachii muscle in 10 subjects. Results show that the

  18. A comparative study of electromyograms of the masseter, temporalis, and anterior digastric muscles obtained by surface and intramuscular electrodes: raw-EMG.

    PubMed

    Koole, P; de Jongh, H J; Boering, G

    1991-07-01

    Electromyographic activity was synchronously recorded by surface and intramuscular electrodes in the same muscle. The activity of the left masseter, left temporalis, and both bellies of the anterior digastric muscle was studied by this double registration technique. In rest position no electromyographic activity could be detected in any of the muscles by both techniques. Both techniques give comparable results in cyclic jaw movements. In isometric contractions, however, differences in the registered activity were observed between the surface electrode on the depressor group muscles and the intramuscularly recorded anterior digastric muscles. Silent periods evoked in the elevator muscles were of slightly longer duration when recorded by intramuscular electrodes than when recorded by surface electrodes. A protruded position of the mandible results in a silent period of longer duration than the position of the mandible in maximal occlusion during clenching for both techniques.

  19. EMGs Analysis of Lumbar, Pelvic and Leg Muscles in Leg Length Discrepancy Adolescents

    NASA Astrophysics Data System (ADS)

    Sotelo-Barroso, Fernando; Márquez-Gamiño, Sergio; Caudillo-Cisneros, Cipriana

    2004-09-01

    To evaluate differences in surface electromyography (EMGs) activity of lumbar, pelvic and leg muscles in adolescents with and without LLD. EMGs activity records were taken during rest and maximal isometric voluntary contractions (MIVC). Peak to peak amplitude (PPA), mean rectified voltage (MRV) and root mean square (RMS), were analyzed. Statistical differences between short and large sides of LLD adolescents, were found (p<0.05). Higher values occurred in shorter limb muscles. No significative differences were found between left and right legs of the control subjects. When EMGs values were compared between short and large sides of LLD subjects with ipsilateral sides of controls, selective, statistically different EMGs values were exhibited. It is suggested that adaptative behavior to secondary biomechanical and/or neural changes occurred, even when none clinical symptoms were reported. The observations were remarked by the absence of EMGs differences between right and left sides of control subjects.

  20. Changes in EMG coherence between long and short thumb abductor muscles during human development.

    PubMed

    Farmer, Simon F; Gibbs, John; Halliday, David M; Harrison, Linda M; James, Leon M; Mayston, Margaret J; Stephens, John A

    2007-03-01

    In adults, motoneurone pools of synergistic muscles that act around a common joint share a common presynaptic drive. Common drive can be revealed by both time domain and frequency domain analysis of EMG signals. Analysis in the frequency domain reveals significant coherence in the range 1-45 Hz, with maximal coherence in low (1-12 Hz) and high (16-32 Hz) ranges. The high-frequency range depends on cortical drive to motoneurones and is coherent with cortical oscillations at approximately 20 Hz frequencies. It is of interest to know whether oscillatory drive to human motoneurone pools changes with development. In the present study we examined age-related changes in coherence between rectified surface EMG signals recorded from the short and long thumb abductor muscles during steady isometric contraction obtained while subjects abducted the thumb against a manipulandum. We analysed EMG data from 36 subjects aged between 4 and 14 years, and 11 adult subjects aged between 22 and 59 years. Using the techniques of pooled coherence analysis and the chi(2) difference of coherence test we demonstrate that between the ages of 7 and 9 years, and 12 and 14 years, there are marked increases in the prevalence and magnitude of coherence at frequencies between 11 and 45 Hz. The data from subjects aged 12-14 years were similar to those obtained from adult controls. The most significant differences between younger children and the older age groups were detected at frequencies close to 20 Hz. We believe that these are the first reported results demonstrating significant late maturational changes in the approximately 20 Hz common oscillatory drive to human motoneurone pools.

  1. Body position effects on sternocleidomastoid and masseter EMG pattern activity in patients undergoing occlusal splint therapy.

    PubMed

    Ormeño, G; Miralles, R; Santander, H; Casassus, R; Ferrer, P; Palazzi, C; Moya, H

    1997-10-01

    This study was conducted in order to determine the effects of body position on electromyographic (EMG) activity of sternocleidomastoid and masseter muscles, in 15 patients with myogenic cranio-cervical-mandibular dysfunction undergoing occlusal splint therapy. EMG activity was recorded by placing surface electrodes on the sternocleidomastoid and masseter muscles (contralateral to the habitual sleeping side of each patient). EMG activity at rest and during swallowing of saliva and maximal voluntary clenching was recorded in the following body positions: standing, supine and lateral decubitus. In the sternocleidomastoid muscle significant higher EMG activities at rest and during swallowing were recorded in the lateral decubitus position, whereas during maximal voluntary clenching EMG activity did not change. In the masseter muscle significant higher EMG activity during maximal voluntary clenching in a standing position was observed, whereas EMG activity at rest and during swallowing did not change. The opposite pattern of EMG activity supports the idea that there may exist a differential modulation of the motor neuron pools of the sternocleidomastoid and masseter muscles, of peripheral and/or central origin. This suggests that the presence of parafunctional habits and body position could be closely correlated with the clinical symptomatology in these muscles in patients with myogenic craniomandibular dysfunction.

  2. Only scratching the cell surface: extracellular signals in cerebrum development.

    PubMed

    Hébert, Jean M

    2013-08-01

    Numerous roles have been identified for extracellular signals such as Fibroblast Growth Factors (FGFs), Transforming Growth Factor-βs (TGFβs), Wingless-Int proteins (WNTs), and Sonic Hedgehog (SHH) in assigning fates to cells during development of the cerebrum. However, several fundamental questions remain largely unexplored. First, how does the same extracellular signal instruct precursor cells in different locations or at different stages to adopt distinct fates? And second, how does a precursor cell integrate multiple signals to adopt a specific fate? Answers to these questions require knowing the mechanisms that underlie each cell type's competence to respond to certain extracellular signals. This brief review provides illustrative examples of potential mechanisms that begin to bridge the gap between cell surface and cell fate during cerebrum development.

  3. Reprogramming cellular signaling machinery using surface-modified carbon nanotubes.

    PubMed

    Zhang, Yi; Wu, Ling; Jiang, Cuijuan; Yan, Bing

    2015-03-16

    Nanoparticles, such as carbon nanotubes (CNTs), interact with cells and are easily internalized, causing various perturbations to cell functions. The mechanisms involved in such perturbations are investigated by a systematic approach that utilizes modified CNTs and various chemical-biological assays. Three modes of actions are (1) CNTs bind to different cell surface receptors and perturb different cell signaling pathways; (2) CNTs bind to a receptor with different affinity and, therefore, strengthen or weaken signals; (3) CNTs enter cells and bind to soluble signaling proteins involved in a signaling pathway. Understanding of such mechanisms not only clarifies how CNTs cause cytotoxicity but also demonstrates a useful method to modulate biological/toxicological activities of CNTs for their various industrial, biomedical, and consumer applications.

  4. Only scratching the cell surface; extracellular signals in cerebrum development

    PubMed Central

    Hébert, Jean M.

    2013-01-01

    Numerous roles have been identified for extracellular signals such as Fibroblast Growth Factors (FGFs), Transforming Growth Factor-βs (TGFβs), Wingless-Int proteins (WNTs), and Sonic Hedgehog (SHH) in assigning fates to cells during development of the cerebrum. However, several fundamental questions remain largely unexplored. First, how does the same extracellular signal instruct precursor cells in different locations or at different stages to adopt distinct fates? And second, how does a precursor cell integrate multiple signals to adopt a specific fate? Answers to these questions require knowing the mechanisms that underlie each cell type’s competence to respond to certain extracellular signals. This brief review provides illustrative examples of potential mechanisms that begin to bridge the gap between cell surface and cell fate during cerebrum development. PMID:23669550

  5. Iridescent flowers? Contribution of surface structures to optical signaling.

    PubMed

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

    2014-07-01

    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 overall floral coloration. We studied the reflection characteristics of flower petals of various plant species with an imaging scatterometer, which allows direct visualization of the angle dependence of the reflected light in the hemisphere above the petal. To separate the light reflected by the flower surface from the light backscattered by the components inside (e.g. the vacuoles), we also investigated surface casts. A survey among angiosperms revealed three different types of floral surface structure, each with distinct reflections. Petals with a smooth and very flat surface had mirror-like reflections and petal surfaces with cones yielded diffuse reflections. Petals with striations yielded diffraction patterns when single cells were illuminated. The iridescent signal, however, vanished when illumination similar to that found in natural conditions was applied. Pigmentary rather than structural coloration determines the optical appearance of flowers. Therefore, the hypothesized signaling by flowers with striated surfaces to attract potential pollinators presently seems untenable. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

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

    PubMed

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

    2015-10-01

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

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

    PubMed

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

    2017-09-17

    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, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  8. Evaluation of EMG processing techniques using Information Theory

    PubMed Central

    2010-01-01

    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. PMID:21073705

  9. Evaluation of EMG processing techniques using Information Theory.

    PubMed

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

    2010-11-12

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

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

    PubMed Central

    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.

    PubMed

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

    2017-01-01

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

  12. Occurrence of a rhythmic slower wave in EMG prior to a rapid voluntary movement.

    PubMed

    Tanii, K

    1984-05-01

    The aim of the present study was to investigate whether an EMG slower wave prior to a rapid straightening-up movement is associated with motor preparation to perform the movement. The straightening movement was performed at 6 load intensities and under 3 conditions: without any external load; with an additional load; lifting a load. The subject could freely begin the rapid movement from a moderate forward-bending position whenever he was fully ready for the beginning of the movement after he held the bent posture. Bipolar surface EMGs of the erector spinal muscles at the L1 and L4 level, the gluteus maximus muscle and the semitendinosus muscle were led by a pair of skin electrodes with a time constant of 0.03 sec. The signal from the hip goniometer was measured simultaneously to identify the period of the movement. A distinct relationship between the occurrence of the slower wave and both load intensities and conditions was not found. However, the rhythmic slower wave often occurred in the muscles 200-450 msec before the movement. The occurrence of the wave in the muscles was often simultaneous. The signal from the hip goniometer did not change with the occurrence of the slower wave. The amplitude of the slower wave increased frequently. The present results suggest that the slower wave may reflect a significant change of motoneuronal activity in connection with motor preparation to perform the movement.

  13. Measuring human locomotor control using EMG and EEG: Current knowledge, limitations and future considerations.

    PubMed

    Enders, Hendrik; Nigg, Benno M

    2016-01-01

    Electrical signals encoding different forms of information can be observed at multiple levels of the human nervous system. Typically, these signals have been recorded in a rather isolated fashion with little overlap between the static recordings of electroencephalography (EEG) commonly used in neuroscience and the typical surface electromyography (EMG) recordings used in biomechanics. However, within the last decade, there has been an emerging need to link the electrical activation patterns of brain areas during movement to the behavior of the musculoskeletal system. This review discusses some of the most recent studies using the EEG and/or EMG to study the neural control of movement and human locomotion as well as studies quantifying the connectivity between brain and muscles. The focus is on rhythmic locomotor-type activities; however, results are discussed within the framework of initial work that has been done in upper and lower limbs during static and dynamic contractions. Limitations and current challenges as well as the possibility and functional interpretation of studying the connectivity between the cortex and skeletal muscles using a measure of coherence are discussed. The manuscript is geared toward scientists interested in the application of EEG in the field of locomotion, sports and exercise.

  14. Innovative surface NMR signal processing to significantly improve data quality

    NASA Astrophysics Data System (ADS)

    Neyer, F. M.; Hertrich, M.; Greenhalgh, S. A.

    2010-12-01

    Surface Nuclear Magnetic Resonance (SNMR) is a relatively new geophysical technique primarily used for water detection in the shallow subsurface. Magnetic fields arising from current pulses in a surface loop antenna penetrate the subsurface and interact with the hydrogen protons of liquid water. Among the various geophysical methods, surface NMR is unique in that it is directly sensitive to water molecules. Hence it has the powerful potential to quantitatively map the water distribution with depth. The signal measurement relies on the principle of induction that creates a weak voltage in the range of nV to a few μV in the surface receiver loop. However, the record is obscured by (i) man-made, industrial, and cultural (harmonic) noise such as power-lines and railway tracks, (ii) spike events (incoherent noise), and (iii) atmospheric background noise (random). Extreme hardware requirements and the weakness of the signal cause the records to be heavily noise contaminated in general. As a consequence, efficient noise suppression techniques are required to extract the weak surface NMR signal, i.e. stacking, loop design, and digital post-processing. In this study, we present a state-of-the-art workflow for full time series NMR data processing. As a first step, random spike events are removed from all records. Reference channels are further used to create a shaping filter by which the noise component in signal record is largely reduced. In the latter stage, signal extraction is performed using digital quadrature detection with an additional phase correction. The filter design is based on a least-squares approach using different input channels. This multi-dimensional Wiener filter method allows for a multi-channel noise reduction. Today, state-of-the-art full bandwidth multi-channel recording systems offer the possibility to record four channels simultaneously. Therefore, it is possible to use up to three reference channels for noise attenuation. By analyzing the optimal

  15. Correlative Evaluation of Mental and Physical Workload of Laparoscopic Surgeons Based on Surface Electromyography and Eye-tracking Signals.

    PubMed

    Zhang, Jian-Yang; Liu, Sheng-Lin; Feng, Qing-Min; Gao, Jia-Qi; Zhang, Qiang

    2017-09-11

    Surgeons' mental and physical workloads are major focuses of operating room (OR) ergonomics, and studies on this topic have generally focused on either mental workload or physical workload, ignoring the interaction between them. Previous studies have shown that physically demanding work may affect mental performance and may be accompanied by impaired mental processing and decreased performance. In this study, 14 participants were recruited to perform laparoscopic cholecystectomy (LC) procedures in a virtual simulator. Surface electromyography (sEMG) signals of the bilateral trapezius, bicipital, brachioradialis and flexor carpi ulnaris (FCU) muscles and eye-tracking signals were acquired during the experiment. The results showed that the least square means of muscle activity during the LC phases of surgery in an all-participants mixed effects model were 0.79, 0.81, and 0.98, respectively. The observed muscle activities in the different phases exhibited some similarity, while marked differences were found between the forearm bilateral muscles. Regarding mental workload, significant differences were observed in pupil dilation between the three phases of laparoscopic surgery. The mental and physical workloads of laparoscopic surgeons do not appear to be generally correlated, although a few significant negative correlations were found. This result further indicates that mental fatigue does markedly interfere with surgeons' operating movements.

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

    PubMed

    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 < 0.01). 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 < 0.05), pectineus (p < 0.01) and gracilis (p < 0.01) but not adductor magnus. For force data, clinical test type was a significant factor (p < 0.01) with Hips 0 being significantly stronger than Hips 45, Hips 90 and Side lay. BMI (body mass index) was a significant factor (p < 0.01) for producing a higher force. All other factors had no significant effect on the force outputs. Hip adduction strength assessment is best measured at hips 0 (which produced most force) or 45° flexion (which generally gave the highest EMG output). Muscle EMG varied significantly with clinical test position. Athletes with previous groin injury had a significant fall in some EMG outputs. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. 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).

    PubMed

    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.

  18. Extracting signals robust to electrode number and shift for online simultaneous and proportional myoelectric control by factorization algorithms.

    PubMed

    Muceli, Silvia; Jiang, Ning; Farina, Dario

    2014-05-01

    Previous research proposed the extraction of myoelectric control signals by linear factorization of multi-channel electromyogram (EMG) recordings from forearm muscles. This paper further analyses the theoretical basis for dimensionality reduction in high-density EMG signals from forearm muscles. Moreover, it shows that the factorization of muscular activation patterns in weights and activation signals by non-negative matrix factorization (NMF) is robust with respect to the channel configuration from where the EMG signals are obtained. High-density surface EMG signals were recorded from the forearm muscles of six individuals. Weights and activation signals extracted offline from 10 channel configurations with varying channel numbers (6, 8, 16, 192 channels) were highly similar. Additionally, the method proved to be robust against electrode shifts in both transversal and longitudinal direction with respect to the muscle fibers. In a second experiment, six subjects directly used the activation signals extracted from high-density EMG for online goal-directed control tasks involving simultaneous and proportional control of two degrees-of-freedom of the wrist. The synergy weights for this control task were extracted from a reference configuration and activation signals were calculated online from the reference configuration as well as from the two shifted configurations, simulating electrode shift. Despite the electrode shift, the task completion rate, task completion time, and execution efficiency were generally not statistically different among electrode configurations. Online performances were also mostly similar when using either 6, 8, or 16 EMG channels. The robustness of the method to the number and location of channels, proved both offline and online, indicates that EMG signals recorded from forearm muscles can be approximated as linear instantaneous mixtures of activation signals and justifies the use of linear factorization algorithms for extracting, in a

  19. Shoulder muscles recruitment during a power backward giant swing on high bar: a wavelet-EMG-analysis.

    PubMed

    Frère, Julien; Göpfert, Beat; Slawinski, Jean; Tourny-Chollet, Claire

    2012-04-01

    This study aimed at determining the upper limb muscles coordination during a power backward giant swing (PBGS) and the recruitment pattern of motor units (MU) of co-activated muscles. The wavelet transformation (WT) was applied to the surface electromyographic (EMG) signal of eight shoulder muscles. Total gymnast's body energy and wavelet synergies extracted from the WT-EMG by using a non-negative matrix factorization were analyzed as a function of the body position angle of the gymnast. A cross-correlation analysis of the EMG patterns allowed determining two main groups of co-activated muscles. Two wavelet synergies representing the main spectral features (82% of the variance accounted for) discriminated the recruitment of MU. Although no task-group of MU was found among the muscles, it appeared that a higher proportion of fast MU was recruited within the muscles of the first group during the upper part of the PBGS. The last increase of total body energy before bar release was induced by the recruitment of the muscles of the second group but did not necessitate the recruitment of a higher proportion of fast MU. Such muscle coordination agreed with previous simulations of elements on high bar as well as the findings related to the recruitment of MU. Copyright © 2012 Elsevier B.V. All rights reserved.

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

    PubMed

    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.

  1. Low-Amplitude Craniofacial EMG Power Spectral Density and 3D Muscle Reconstruction from MRI

    PubMed Central

    Wiedemann, Lukas; Chaberova, Jana; Edmunds, Kyle; Einarsdóttir, Guðrún; Ramon, Ceon

    2015-01-01

    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. PMID:26913150

  2. Surface code—biophysical signals for apoptotic cell clearance

    NASA Astrophysics Data System (ADS)

    Biermann, Mona; Maueröder, Christian; Brauner, Jan M.; Chaurio, Ricardo; Janko, Christina; Herrmann, Martin; Muñoz, Luis E.

    2013-12-01

    Apoptotic cell death and the clearance of dying cells play an important and physiological role in embryonic development and normal tissue turnover. In contrast to necrosis, apoptosis proceeds in an anti-inflammatory manner. It is orchestrated by the timed release and/or exposure of so-called ‘find-me’, ‘eat me’ and ‘tolerate me’ signals. Mononuclear phagocytes are attracted by various ‘find-me’ signals, including proteins, nucleotides, and phospholipids released by the dying cell, whereas the involvement of granulocytes is prevented via ‘stay away’ signals. The exposure of anionic phospholipids like phosphatidylserine (PS) by apoptotic cells on the outer leaflet of the plasma membrane is one of the main ‘eat me’ signals. PS is recognized by a number of innate receptors as well as by soluble bridging molecules on the surface of phagocytes. Importantly, phagocytes are able to discriminate between viable and apoptotic cells both exposing PS. Due to cytoskeleton remodeling PS has a higher lateral mobility on the surfaces of apoptotic cells thereby promoting receptor clustering on the phagocyte. PS not only plays an important role in the engulfment process, but also acts as ‘tolerate me’ signal inducing the release of anti-inflammatory cytokines by phagocytes. An efficient and fast clearance of apoptotic cells is required to prevent secondary necrosis and leakage of intracellular danger signals into the surrounding tissue. Failure or prolongation of the clearance process leads to the release of intracellular antigens into the periphery provoking inflammation and development of systemic inflammatory autoimmune disease like systemic lupus erythematosus. Here we review the current findings concerning apoptosis-inducing pathways, important players of apoptotic cell recognition and clearance as well as the role of membrane remodeling in the engulfment of apoptotic cells by phagocytes.

  3. Interpretation of EMG changes with fatigue: facts, pitfalls, and fallacies.

    PubMed

    Dimitrova, N A; Dimitrov, G V

    2003-02-01

    Failure to maintain the required or expected force, defined as muscle fatigue, is accompanied by changes in muscle electrical activity. Although studied for a long time, reasons for EMG changes in time and frequency domain have not been clear until now. Many authors considered that theory predicted linear relation between the characteristic frequencies and muscle fibre propagation velocity (MFPV), irrespective of the fact that spectral characteristics can drop even without any changes in MFPV, or in proportion exceeding the MFPV changes. The amplitude changes seem to be more complicated and contradictory since data on increased, almost unchanged, and decreased amplitude characteristics of the EMG, M-wave or motor unit potential (MUP) during fatigue can be found in literature. Moreover, simultaneous decrease and increase in amplitude of MUP and M-wave, detected with indwelling and surface electrodes, were referred to as paradoxical. In spite of this, EMG amplitude characteristics are predominantly used when causes for fatigue are analysed. We aimed to demonstrate theoretical grounds for pitfalls and fallacies in analysis of experimental results if changes in intracellular action potential (IAP), i.e. in peripheral factors of muscle fatigue, were not taken into consideration. We based on convolution model of potentials produced by a motor unit and detected by a point or rectangular plate electrode in a homogeneous anisotropic infinite volume conductor. Presentation of MUP in the convolution form gave us a chance to consider power spectrum (PS) of MUP as a product of two terms. The first one, PS of the input signal, represented PS of the first temporal derivative of intracellular action potential (IAP). The second term, PS of the impulse response, took into account MFPV, differences in instants of activation of each fibre, MU anatomy, and MU position in the volume conductor in respect to the detecting electrode. PS presentation through product means that not only

  4. Surface electromyography for speech and swallowing systems: measurement, analysis, and interpretation.

    PubMed

    Stepp, Cara E

    2012-08-01

    Applying surface electromyography (sEMG) to the study of voice, speech, and swallowing is becoming increasingly popular. An improved understanding of sEMG and building a consensus as to appropriate methodology will improve future research and clinical applications. An updated review of the theory behind recording sEMG for the speech and swallowing systems is provided. Several factors that are known to affect the content of the sEMG signal are discussed, and practical guidelines for sEMG recording and analysis are presented, focusing on special considerations within the context of the speech and swallowing anatomy. Unique challenges are seen in application of sEMG to the speech and swallowing musculature owing to the small size of the muscles in relation to the sEMG detection volume and the present lack of knowledge about innervation zone locations. Despite the challenges discussed, application of sEMG to speech and swallowing has potential as a clinical and research tool when used correctly and is specifically suited to noninvasive clinical studies using between-condition or between-group comparisons for which detection of specific isolated muscle activities is not necessary.

  5. Experimentally induced stress validated by EMG activity.

    PubMed

    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.

  6. Filter design for cancellation of baseline-fluctuation in needle EMG recordings.

    PubMed

    Rodríguez-Carreño, I; Malanda-Trigueros, A; Gila-Useros, L; Navallas-Irujo, J; Rodríguez-Falces, J

    2006-01-01

    Appropriate cancellation of the baseline fluctuation (BLF) is an important issue when recording EMG signals as it may degrade signal quality and distort qualitative and quantitative analysis. We present a novel filter-design approach for automatic cancellation of the BLF based on several signal processing techniques used sequentially. The methodology is to estimate the spectral content of the BLF, and then to use this estimation to design a high-pass FIR filter that cancel the BLF present in the signal. Two merit figures are devised for measuring the degree of BLF present in an EMG record. These figures are used to compare our method with the conventional approach, which naively considers the baseline course to be of constant (without any fluctuation) potential shift. Applications of the technique on real and simulated EMG signals show the superior performance of our approach in terms of both visual inspection and the merit figures.

  7. EMG prediction from motor cortical recordings via a nonnegative point-process filter.

    PubMed

    Nazarpour, Kianoush; Ethier, Christian; Paninski, Liam; Rebesco, James M; Miall, R Chris; Miller, Lee E

    2012-07-01

    A constrained point-process filtering mechanism for prediction of electromyogram (EMG) signals from multichannel neural spike recordings is proposed here. Filters from the Kalman family are inherently suboptimal in dealing with non-Gaussian observations, or a state evolution that deviates from the Gaussianity assumption. To address these limitations, we modeled the non-Gaussian neural spike train observations by using a generalized linear model that encapsulates covariates of neural activity, including the neurons' own spiking history, concurrent ensemble activity, and extrinsic covariates (EMG signals). In order to predict the envelopes of EMGs, we reformulated the Kalman filter in an optimization framework and utilized a nonnegativity constraint. This structure characterizes the nonlinear correspondence between neural activity and EMG signals reasonably. The EMGs were recorded from 12 forearm and hand muscles of a behaving monkey during a grip-force task. In the case of limited training data, the constrained point-process filter improved the prediction accuracy when compared to a conventional Wiener cascade filter (a linear causal filter followed by a static nonlinearity) for different bin sizes and delays between input spikes and EMG output. For longer training datasets, results of the proposed filter and that of the Wiener cascade filter were comparable.

  8. EMG feedback tasks reduce reflexive stiffness during force and position perturbations.

    PubMed

    Forbes, Patrick A; Happee, Riender; van der Helm, Frans C T; Schouten, Alfred C

    2011-08-01

    Force and position perturbations are widely applied to identify muscular and reflexive contributions to posture maintenance of the arm. Both task instruction (force vs. position) and the inherently linked perturbation type (i.e., force perturbations-position task and position perturbations-force tasks) affect these contributions and their mutual balance. The goal of this study is to explore the modulation of muscular and reflexive contributions in shoulder muscles using EMG biofeedback. The EMG biofeedback provides a harmonized task instruction to facilitate the investigation of perturbation type effects irrespective of task instruction. External continuous force and position perturbations with a bandwidth of 0.5-20 Hz were applied at the hand while subjects maintained prescribed constant levels of muscular co-activation using visual feedback of an EMG biofeedback signal. Joint admittance and reflexive impedance were identified in the frequency domain, and parametric identification separated intrinsic muscular and reflexive feedback properties. In tests with EMG biofeedback, perturbation type (position and force) had no effect on joint admittance and reflexive impedance, indicating task as the dominant factor. A reduction in muscular and reflexive stiffness was observed when performing the EMG biofeedback task relative to the position task. Reflexive position feedback was effectively suppressed during the equivalent EMG biofeedback task, while velocity and acceleration feedback were both decreased by approximately 37%. This indicates that force perturbations with position tasks are a more effective paradigm to investigate complete dynamic motor control of the arm, while EMG tasks tend to reduce the reflexive contribution.

  9. Is interindividual variability of EMG patterns in trained cyclists related to different muscle synergies?

    PubMed

    Hug, François; Turpin, Nicolas A; Guével, Arnaud; Dorel, Sylvain

    2010-06-01

    Our aim was to determine whether muscle synergies are similar across trained cyclists (and thus whether the same locomotor strategies for pedaling are used), despite interindividual variability of individual EMG patterns. Nine trained cyclists were tested during a constant-load pedaling exercise performed at 80% of maximal power. Surface EMG signals were measured in 10 lower limb muscles. A decomposition algorithm (nonnegative matrix factorization) was applied to a set of 40 consecutive pedaling cycles to differentiate muscle synergies. We selected the least number of synergies that provided 90% of the variance accounted for VAF. Using this criterion, three synergies were identified for all of the subjects, accounting for 93.5+/-2.0% of total VAF, with VAF for individual muscles ranging from 89.9+/-8.2% to 96.6+/-1.3%. Each of these synergies was quite similar across all subjects, with a high mean correlation coefficient for synergy activation coefficients (0.927+/-0.070, 0.930+/-0.052, and 0.877+/-0.110 for synergies 1-3, respectively) and muscle synergy vectors (0.873+/-0.120, 0.948+/-0.274, and 0.885+/-0.129 for synergies 1-3, respectively). Despite a large consistency across subjects in the weighting of several monoarticular muscles into muscle synergy vectors, we found larger interindividual variability for another monoarticular muscle (soleus) and for biarticular muscles (rectus femoris, gastrocnemius lateralis, biceps femoris, and semimembranosus). This study demonstrated that pedaling is accomplished by the combination of the similar three muscle synergies among trained cyclists. The interindividual variability of EMG patterns observed during pedaling does not represent differences in the locomotor strategy for pedaling.

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

    PubMed

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

    2016-06-01

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

  11. Neutrophil cell surface receptors and their intracellular signal transduction pathways☆

    PubMed Central

    Futosi, Krisztina; Fodor, Szabina; Mócsai, Attila

    2013-01-01

    Neutrophils play a critical role in the host defense against bacterial and fungal infections, but their inappropriate activation also contributes to tissue damage during autoimmune and inflammatory diseases. Neutrophils express a large number of cell surface receptors for the recognition of pathogen invasion and the inflammatory environment. Those include G-protein-coupled chemokine and chemoattractant receptors, Fc-receptors, adhesion receptors such as selectins/selectin ligands and integrins, various cytokine receptors, as well as innate immune receptors such as Toll-like receptors and C-type lectins. The various cell surface receptors trigger very diverse signal transduction pathways including activation of heterotrimeric and monomeric G-proteins, receptor-induced and store-operated Ca2 + signals, protein and lipid kinases, adapter proteins and cytoskeletal rearrangement. Here we provide an overview of the receptors involved in neutrophil activation and the intracellular signal transduction processes they trigger. This knowledge is crucial for understanding how neutrophils participate in antimicrobial host defense and inflammatory tissue damage and may also point to possible future targets of the pharmacological therapy of neutrophil-mediated autoimmune or inflammatory diseases. PMID:23994464

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

    PubMed

    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 < 0.05). Comparing the normalized EMG among the four QF synergists, a significantly lower normalized EMG was observed in the VI at 150° as compared with the other three QF muscles (P < 0.05). These results suggest that the EMG-force relationship of the four QF synergists shifted downward at an extended 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.

  13. Parkinson's disease rigidity: EMG in a small hand muscle at "rest".

    PubMed

    Cantello, R; Gianelli, M; Civardi, C; Mutani, R

    1995-10-01

    The presence of excessive EMG at "rest" might be an important factor in the genesis of Parkinson's disease (PD) rigidity, and we studied it in the first dorsal interosseous muscle (FDI) of 8 idiopathic PD patients. We had 8 age- and sex-matched normal controls. In the PD group, the average area of the surface EMG at "rest" correlated significantly with the clinical evaluation of rigidity and remained abnormally enhanced for 10-15 min after a command to "relax." Later, it tended to decline, but its entity was still much greater than in controls. The EMG "at rest" consisted of unwilled motor unit (MU) firing. A larger MU number was recruited in patients than in controls at "rest." MU rate coding was similar in both groups. Eventually, patients could get periods of EMG silence which, however, were interrupted by short EMG bursts, even if there was no muscle stretch. These bursts were interpreted as residual fragments of the original excessive EMG at "rest." MUs first recruited during such bursts showed high, but not total, overlapping with those first recruited by a gentle voluntary contraction or by a weak transcranial magnetic stimulus to motor cortex. We conclude that EMG activity at "rest" was made up of the discharge of low-threshold MUs, with a recruitment order similar to that resulting from descending cortico-spinal volleys. However, we cannot exclude other possible input sources to the alpha-motoneurones at "rest."

  14. EMG-based characterization of pathological tremor using the iterated Hilbert transform.

    PubMed

    Dideriksen, Jakob Lund; Gianfelici, Francesco; Maneski, Lana Z Popovic; Farina, Dario

    2011-10-01

    The identification and characterization of pathological tremor are necessary for the development of techniques for tremor suppression, for example, based on functional electrical stimulation. For this purpose, the amplitude and phase characteristics of the tremor signal should be estimated by effective detection techniques, either from the kinematics or from muscle recordings. This paper presents an approach for the estimation of the characteristics of pathological tremor from the surface electromyogram (EMG) signal based on the iterated Hilbert transform (IHT). It is shown that the IHT allows an asymptotically exact modeling of the tremor and the voluntary activity components in the surface EMG, and an effective demodulation of the pathological tremor parameters. The method was tested on signals generated by a recent model for tremor generation as well as experimentally recorded from patients affected by pathological tremor. The results showed the ability of the proposed approach to demodulate effectively the tremor amplitude (average correlation with imposed amplitude: R(2)=0.52), the frequency (root mean square error in frequency estimation: 2.6 Hz), and phase, as well as the degree of voluntary activity (correlation with simulated inertial load: R(2)=0.62). The application of the method to the experimental data indicated that the estimated tremor component closely resembles inertial measurements of limb movement (peak cross correlation across four patients: 0.62±0.15). Compared to the performance of empirical mode decomposition, the proposed method proved to be more accurate for tremor characterization without a priori knowledge of the tremor characteristics. This method can be used as a part of a control system in strategies for suppression of tremor.

  15. EMG activity during whole body vibration: motion artifacts or stretch reflexes?

    PubMed

    Ritzmann, Ramona; Kramer, Andreas; Gruber, Markus; Gollhofer, Albert; Taube, Wolfgang

    2010-09-01

    The validity of electromyographic (EMG) data recorded during whole body vibration (WBV) is controversial. Some authors ascribed a major part of the EMG signal to vibration-induced motion artifacts while others have interpreted the EMG signals as muscular activity caused at least partly by stretch reflexes. The aim of this study was to explore the origin of the EMG signal during WBV using several independent approaches. In ten participants, the latencies and spectrograms of stretch reflex responses evoked by passive dorsiflexions in an ankle ergometer were compared to those of the EMG activity of four leg muscles during WBV. Pressure application to the muscles was used to selectively reduce the stretch reflex, thus permitting to distinguish stretch reflexes from other signals. To monitor motion artifacts, dummy electrodes were placed close to the normal electrodes. Strong evidence for stretch reflexes was found: the latencies of the stretch reflex responses evoked by dorsiflexions were almost identical to the supposed stretch reflex responses during vibration (differences of less than 1 ms). Pressure application significantly reduced the amplitude of both the supposed stretch reflexes during vibration (by 61 +/- 17%, p < 0.001) and the stretch reflexes in the ankle ergometer (by 56 +/- 13%, p < 0.01). The dummy electrodes showed almost no activity during WBV (7 +/- 4% of the corresponding muscle's iEMG signal). The frequency analyses revealed no evidence of motion artifacts. The present results support the hypothesis of WBV-induced stretch reflexes. Contribution of motion artifacts to the overall EMG activity seems to be insignificant.

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

    PubMed

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

    2006-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    Zhang, Li; Song, Gaoqing

    2009-10-01

    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.

  20. Investigation of the HD-sEMG probability density function shapes with varying muscle force using data fusion and shape descriptors.

    PubMed

    Al Harrach, Mariam; Boudaoud, Sofiane; Carriou, Vincent; Laforet, Jeremy; Letocart, Adrien J; Grosset, Jean-François; Marin, Frédéric

    2017-08-01

    This work presents an evaluation of the High Density surface Electromyogram (HD-sEMG) Probability Density Function (PDF) shape variation according to contraction level. On that account, using PDF shape descriptors: High Order Statistics (HOS) and Shape Distances (SD), we try to address the absence of a consensus for the sEMG non-Gaussianity evolution with force variation. This is motivated by the fact that PDF shape information are relevant in physiological assessment of the muscle architecture and function, such as contraction level classification, in complement to classical amplitude parameters. Accordingly, both experimental and simulation studies are presented in this work. For data fusion, the watershed image processing technique was used. This technique allowed us to find the dominant PDF shape variation profiles from the 64 signals. The experimental protocol consisted of three isometric isotonic contractions of 30, 50 and 70% of the Maximum Voluntary Contraction (MVC). This protocol was performed by six subjects and recorded using an 8 × 8 HD-sEMG grid. For the simulation study, the muscle modeling was done using a fast computing cylindrical HD-sEMG generation model. This model was personalized by morphological parameters obtained by sonography. Moreover, a set of the model parameter configurations were compared as a focused sensitivity analysis of the PDF shape variation. Further, monopolar, bipolar and Laplacian electrode configurations were investigated in both experimental and simulation studies. Results indicated that sEMG PDF shape variations according to force increase are mainly dependent on the Motor Unit (MU) spatial recruitment strategy, the MU type distribution within the muscle, and the used electrode arrangement. Consequently, these statistics can give us an insight into non measurable parameters and specifications of the studied muscle primarily the MU type distribution. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Preliminary study of skeletal muscle with multi-signals during isometric contraction.

    PubMed

    Shi, Jun; Zheng, Yongping; Yan, Zhuangzhi; Huang, Qinghua

    2006-01-01

    Electromyography (EMG) has been widely used for the functional assessment of muscles. On the other hand, sonography has been commonly used to detect the morphological information of human muscles in both static and dynamic conditions. In this study, we demonstrated the feasibility to use the continuous signals about the architectural changes of muscles detected in real-time from ultrasound images to characterize muscles under isometric contraction. We named this signal as sonomyography (SMG). Synchronized ultrasound images and surface EMG (SEMG) signals were continuously collected from the right biceps brachii during the isometric contraction and subsequent relaxation periods together with the generated torque. The relationships among the SEMG, the muscle deformation SMG and the torque were investigated for the contraction phase. The results suggested that the SMG together with EMG signals may potentially provide a more comprehensive assessment for the muscle functions.

  2. Steering a tractor by means of an EMG-based human-machine interface.

    PubMed

    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.

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

    PubMed Central

    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

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

    PubMed

    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.

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

    PubMed

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

    2014-08-08

    Motor imagery (MI) performed in an upright stance promotes increases in postural sway without changes in usual amplitude measures of calf muscle EMG. However, postural muscle activity can also be determined from the temporal association between EMG and center of pressure (COP) displacements. In this study we investigated whether the MI modulation of postural sway is accompanied by changes in EMG-COP association. Surface EMG from the lateral gastrocnemius (LG) muscle and COP coordinates were collected from 12 subjects while they imagined themselves performing a rising on tiptoes movement via kinesthetic or visual imagery. As a control condition subjects were requested to imagine singing a song. The standard deviation of the forward-backward COP sway and the coefficient of variation of the EMG were calculated and compared across tasks. The degree of association between COP sways and LG activity was evaluated through a cross-correlation function. Kinesthetic imagery promoted a larger COP displacement than both visual and control imagery (p<0.02). No difference in EMG amplitude was observed across imagery tasks (p=0.08). Crucially, we found a stronger EMG-COP association during kinesthetic imagery compared to control imagery (p=0.02), whereas the EMG-COP association in visual imagery was not different from that observed during kinesthetic or control imagery (p>0.19). In conclusion, kinesthetic imagery resulted in a higher EMG-COP temporal association. Subliminal fringe mechanisms may account for the imagery effects on muscle activity and postural sway during upright stance. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

    PubMed Central

    Bevilaqua-Grossi, Débora; Monteiro-Pedro, Vanessa; de Vasconcelos, Rodrigo Antunes; Arakaki, Juliano Coelho; Bérzin, Fausto

    2006-01-01

    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 < 0.0007) and MVIC hip abduction at 0° of abduction for female subjects (p < 0.02196). There were no statistically significant differences in the VLL EMG activity among the three sets of exercises tested. 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

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

    NASA Astrophysics Data System (ADS)

    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

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

    PubMed

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

    2016-04-01

    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. 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. 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 enhanced to 85.8% and 90.9 bit

  9. Hand gesture recognition based on surface electromyography.

    PubMed

    Samadani, Ali-Akbar; Kulic, Dana

    2014-01-01

    Human hands are the most dexterous of human limbs and hand gestures play an important role in non-verbal communication. Underlying electromyograms associated with hand gestures provide a wealth of information based on which varying hand gestures can be recognized. This paper develops an inter-individual hand gesture recognition model based on Hidden Markov models that receives surface electromyography (sEMG) signals as inputs and predicts a corresponding hand gesture. The developed recognition model is tested with a dataset of 10 various hand gestures performed by 25 subjects in a leave-one-subject-out cross validation and an inter-individual recognition rate of 79% was achieved. The promising recognition rate demonstrates the efficacy of the proposed approach for discriminating between gesture-specific sEMG signals and could inform the design of sEMG-controlled prostheses and assistive devices.

  10. A Study of an EMG-Based Exoskeletal Robot for Human Shoulder Motion Support

    NASA Astrophysics Data System (ADS)

    Kiguchi, Kazuo; Iwami, Koya; Watanabe, Keigo; Fukuda, Toshio

    We have been developing exoskeletal robots in order to realize the human motion support (especially for physically weak people). In this paper, we propose a 2-DOF exoskeletal robot and its method of control to support the human shoulder motion. In this exoskeletal robot, the flexion-extension and abduction-adduction motions of the shoulder are supported by activating the arm holder of the robot, which is atached to the upper arm of the human subject, using wires driven by DC motors. A fuzzy-neuro controller is designed to control the robot according to the skin surface electromyogram(EMG) signals in which the intention of the human subject is reflected. The proposed controller controls the flexion-extension and abduction-adduction motion of the human subject. The effectiveness of the proposed exoskeletal robot has been evaluated experimentally.

  11. Power independent EMG based gesture recognition for robotics.

    PubMed

    Li, Ling; Looney, David; Park, Cheolsoo; Rehman, Naveed U; Mandic, Danilo P

    2011-01-01

    A novel method for detecting muscle contraction is presented. This method is further developed for identifying four different gestures to facilitate a hand gesture controlled robot system. It is achieved based on surface Electromyograph (EMG) measurements of groups of arm muscles. The cross-information is preserved through a simultaneous processing of EMG channels using a recent multivariate extension of Empirical Mode Decomposition (EMD). Next, phase synchrony measures are employed to make the system robust to different power levels due to electrode placements and impedances. The multiple pairwise muscle synchronies are used as features of a discrete gesture space comprising four gestures (flexion, extension, pronation, supination). Simulations on real-time robot control illustrate the enhanced accuracy and robustness of the proposed methodology.

  12. Electromyographic muscle EMG activity in mouth and nasal breathing children.

    PubMed

    Ribeiro, Eliane C; Marchiori, Susana C; da Silva, Ana Maria T

    2004-04-01

    Mouth breathing may cause changes in muscle activity, because an upper airway obstruction leads may cause a person to extend his/her head forward, demanding a higher inspiratory effort on the accessory muscles (sternocleidomastoids). This purpose of this study is to compare, using electromyography (EMG), the activity pattern the sternocleidomastoid and upper trapezius muscles in mouth breathing children and nasal breathing children. Forty-six children, ages 8-12 years, 33 male and 13 female were included. The selected children were divided into two groups: Group I consisted of 26 mouth breathing children, and Group II, 20 nasal breathing children. EMG recordings were made using surface electrodes bilaterally in the areas of the sternocleidomastoideus and upper trapezius muscles, while relaxed and during maximal voluntary contraction. The data were analyzed using the Kruskall-Wallis statistical test. The results indicated higher activity during relaxation and lower activity during maximal voluntary contraction in mouth breathers when compared to the nasal breathers. It is suggested that the activity pattern of the sternocleidomastoid and upper trapezius muscles differs between mouth breathing children and nasal breathing children. This may be attributed to changes in body posture which causes muscular imbalance. Because of the limitations of surface EMG, the results need to be confirmed by adding force measurements and repeating the experiments with matched subjects.

  13. [Newly devised subcutaneous needle electrodes for EMG recording].

    PubMed

    Okabe, Y; Koibuchi, H; Ai, M; Hibi, H; Haketa, T

    1991-09-01

    Subcutaneous needle electrodes made of stainless steel were newly devised for ease of handling and perfect insulation. This needle (phi 0.20 mm) is used for acupuncture. The electrodes had the capability to record the EMG activity easily from a certain muscle. Then, the EMG activities of the masseter muscle were recorded with both these needle electrodes and surface electrodes and the results were compared. 1. Insertion of the electrodes into the subcutaneous tissue was easily performed because of the application of the acupuncture needle and their lightness of 0.2g was effective in fixing the electrodes on the skin without causing any tension. 2. After the insertion of the needle electrodes, the impedance showed below 5 kohm immediately, and the EMG recordings during biting could be simply achieved with great stability. 3. The action potential from the needle electrodes was less than that from the surface ones. The former reacted more sensitively to the change in the distance between the electrodes, compared with the latter.

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

    PubMed

    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.

  15. Variability in surface ECG morphology: signal or noise?

    NASA Technical Reports Server (NTRS)

    Smith, J. M.; Rosenbaum, D. S.; Cohen, R. J.

    1988-01-01

    Using data collected from canine models of acute myocardial ischemia, we investigated two issues of major relevance to electrocardiographic signal averaging: ECG epoch alignment, and the spectral characteristics of the beat-to-beat variability in ECG morphology. With initial digitization rates of 1 kHz, an iterative a posteriori matched filtering alignment scheme, and linear interpolation, we demonstrated that there is sufficient information in the body surface ECG to merit alignment to a precision of 0.1 msecs. Applying this technique to align QRS complexes and atrial pacing artifacts independently, we demonstrated that the conduction delay from atrial stimulus to ventricular activation may be so variable as to preclude using atrial pacing as an alignment mechanism, and that this variability in conduction time be modulated at the frequency of respiration and at a much lower frequency (0.02-0.03Hz). Using a multidimensional spectral technique, we investigated the beat-to-beat variability in ECG morphology, demonstrating that the frequency spectrum of ECG morphological variation reveals a readily discernable modulation at the frequency of respiration. In addition, this technique detects a subtle beat-to-beat alternation in surface ECG morphology which accompanies transient coronary artery occlusion. We conclude that physiologically important information may be stored in the variability in the surface electrocardiogram, and that this information is lost by conventional averaging techniques.

  16. Correlation Between Eddy Current Signal Noise and Peened Surface Roughness

    SciTech Connect

    Wendt, S. E.; Hentscher, S. R.; Raithel, D. C.; Nakagawa, N.

    2007-03-21

    For advanced uses of eddy current (EC) NDE models in, e.g., model-assisted POD, there is a need to understand the origin of EC noise sources so that noise estimations can be made for a given set of inspection conditions, in addition to defect signal predictions. This paper focuses on the material-oriented noise sources that exhibit some universality when isolated from electrical and mechanical noises. Specifically, we report on experimental measurements that show explicit correlations between surface roughness and EC noise as seen in post-peen EC measurements of shot-peened roughness specimens. The samples are 3''-by-3'' Inconel 718 and Ti-6A1-4V blocks, pre-polished and shot-peened at Almen intensities ranging from a low of 4N to as high as 16A, created by smaller ({approx}350 {mu}m) and larger ({approx}1 mm) diameter zirconium oxide shots. Strong correlations are observed between the Almen intensities and the measured surface roughness. The EC noise correlates equally strongly with the Almen intensities for the superalloy specimens. The correlation for the Ti-alloy samples is only apparent at higher intensities, while being weak for lower intensities, indicating the grain noise dominance for smoother surfaces.

  17. Variability in surface ECG morphology: signal or noise?

    NASA Technical Reports Server (NTRS)

    Smith, J. M.; Rosenbaum, D. S.; Cohen, R. J.

    1988-01-01

    Using data collected from canine models of acute myocardial ischemia, we investigated two issues of major relevance to electrocardiographic signal averaging: ECG epoch alignment, and the spectral characteristics of the beat-to-beat variability in ECG morphology. With initial digitization rates of 1 kHz, an iterative a posteriori matched filtering alignment scheme, and linear interpolation, we demonstrated that there is sufficient information in the body surface ECG to merit alignment to a precision of 0.1 msecs. Applying this technique to align QRS complexes and atrial pacing artifacts independently, we demonstrated that the conduction delay from atrial stimulus to ventricular activation may be so variable as to preclude using atrial pacing as an alignment mechanism, and that this variability in conduction time be modulated at the frequency of respiration and at a much lower frequency (0.02-0.03Hz). Using a multidimensional spectral technique, we investigated the beat-to-beat variability in ECG morphology, demonstrating that the frequency spectrum of ECG morphological variation reveals a readily discernable modulation at the frequency of respiration. In addition, this technique detects a subtle beat-to-beat alternation in surface ECG morphology which accompanies transient coronary artery occlusion. We conclude that physiologically important information may be stored in the variability in the surface electrocardiogram, and that this information is lost by conventional averaging techniques.

  18. Specialized Nerve Tests: EMG, NCV and SSEP

    MedlinePlus

    ... Nerve Tests: EMG, NCV and SEEP Alternative Medicine Acupuncture Herbal Supplements Surgical Options Anterior Cervical Fusion Artifical ... are very thin, about the size of an acupuncture needle. The doctor will move the needle up ...

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

    PubMed

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

    2016-01-01

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

  20. The standard concentric needle cannula cannot replace the Macro EMG electrode.

    PubMed

    Sandberg, Arne

    2014-02-01

    To establish the usefulness of the single use and affordable standard concentric EMG electrode as a substitute for the expensive standard macro electrode. Macro EMG performed with macro electrode is compared with recordings from the uninsulated cannula of a standard EMG electrode at two different recording depths in the tibialis anterior muscle. This was performed both in muscles with signs of collateral reinnervation and without. The amplitude of the motor units recorded with the uninsulated concentric needle cannula were lower for the deeply recorded motor units compared to motor unit potential (MUP) amplitudes recorded with the standard macro electrode. The deeply recorded concentric needle (CN) cannula recorded MUPs amplitudes were also lower than superficially recorded CN cannula MUPs. The standard Macro EMG signals show no difference between deeply and superficially recorded motor units. The uninsulated cannula of the concentric needle electrode cannot replace the standard Macro EMG electrode due to technical reasons, probably from different effects of shunting of the bare cannula in deep vs. superficially recorded motor units. The standard CN electrode could not be used as substitute for the standard Macro EMG needle. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.