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

This paper was originally published in Biological Procedures Online (BPO) on March 23, 2006. It was brought to the attention of the journal and authors that reference 74 was incorrect. The original citation for reference 74, “Stanford V. Biosignals offer potential for direct interfaces and health monitoring. Pervasive Computing, IEEE 2004; 3(1):99–103.” should read “Costanza E, Inverso SA, Allen R. ‘Toward Subtle Intimate Interfaces for Mobile Devices Using an EMG Controller’ in Proc CHI2005, April 2005, Portland, OR, USA.”

[1]  M. Amin Time-Frequency Spectrum Analysis and Estimation for Nonstationary Random-Processes , 1992 .

[2]  J. Ushiba,et al.  Decomposition of electromyographic signal by principal component analysis of wavelet coefficients , 2003, IEEE EMBS Asian-Pacific Conference on Biomedical Engineering, 2003..

[3]  A.R. Ismail,et al.  Continuous wavelet transform application to EMG signals during human gait , 1998, Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers (Cat. No.98CH36284).

[4]  S. Reisman,et al.  Time frequency analysis of the electromyogram during fatigue , 1994, Proceedings of 1994 20th Annual Northeast Bioengineering Conference.

[5]  A. Willsky,et al.  Upper Extremity Limb Function Discrimination Using EMG Signal Analysis , 1983, IEEE Transactions on Biomedical Engineering.

[6]  Damjan Zazula,et al.  Decomposition of surface EMG signals using non-linear LMS optimisation of higher-order cumulants , 2002, Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002).

[7]  Jim Torresen,et al.  Two-Step Incremental Evolution of a Prosthetic Hand Controller Based on Digital Logic Gates , 2001, ICES.

[8]  G. Cheron,et al.  A dynamic neural network identification of electromyography and arm trajectory relationship during complex movements , 1996, IEEE Transactions on Biomedical Engineering.

[9]  Daniel Graupe,et al.  Identification of nonstationary models with application to myoelectric signals for controlling electrical stimulation of paraplegics , 1989, IEEE Trans. Acoust. Speech Signal Process..

[10]  L. Ljung,et al.  A Microprocessor System for Multifunctional Control of Upper-Limb Prostheses via Myoelectric Signal Identification , 1978 .

[11]  Jacques Duchêne,et al.  A model of EMG generation , 2000, IEEE Transactions on Biomedical Engineering.

[12]  M.R. Raghuveer,et al.  Bispectrum estimation: A digital signal processing framework , 1987, Proceedings of the IEEE.

[13]  Georgios B. Giannakis,et al.  HOS or SOS for parametric modeling? , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[14]  R. Shiavi,et al.  Clustering analysis and pattern discrimination of EMG linear envelopes , 1991, IEEE Transactions on Biomedical Engineering.

[15]  Patrick Flandrin,et al.  Wigner-Ville spectral analysis of nonstationary processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[16]  Richard G. Absher,et al.  A time-frequency approach to evaluate electromyographic recordings , 1992, [1992] Proceedings Fifth Annual IEEE Symposium on Computer-Based Medical Systems.

[17]  Vincent M. Stanford,et al.  Biosignals offer potential for direct interfaces and health monitoring , 2004, IEEE Pervasive Computing.

[18]  Toshiaki Sugimura,et al.  "Unvoiced speech recognition using EMG - mime speech recognition" , 2003, CHI Extended Abstracts.

[19]  D A Winter,et al.  Pathologic gait diagnosis with computer-averaged electromyographic profiles. , 1984, Archives of physical medicine and rehabilitation.

[20]  Patrick J. Loughlin,et al.  Methods and applications of time–frequency analysis , 2000 .

[21]  Shaojun Xiao,et al.  Estimation of motor unit firing statistics from surface EMG , 1998, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286).

[22]  Douglas L. Jones,et al.  Optimal kernels for nonstationary spectral estimation , 1995, IEEE Trans. Signal Process..

[23]  G. Hefftner,et al.  The electromyogram (EMG) as a control signal for functional neuromuscular stimulation. I. Autoregressive modeling as a means of EMG signature discrimination , 1988, IEEE Transactions on Biomedical Engineering.

[24]  Prashant Parikh A Theory of Communication , 2010 .

[25]  Dario Farina,et al.  Blind separation of linear instantaneous mixtures of nonstationary surface myoelectric signals , 2004, IEEE Transactions on Biomedical Engineering.

[26]  Daniel Graupe,et al.  Functional Separation of EMG Signals via ARMA Identification Methods for Prosthesis Control Purposes , 1975, IEEE Transactions on Systems, Man, and Cybernetics.

[27]  A. J. Thexton,et al.  A randomisation method for discriminating between signal and noise in recordings of rhythmic electromyographic activity , 1996, Journal of Neuroscience Methods.

[28]  Charles Jorgensen,et al.  Gestures as Input: Neuroelectric Joysticks and Keyboards , 2003, IEEE Pervasive Comput..

[29]  Boualem Boashash,et al.  A methodology for detection and classification of some underwater acoustic signals using time-frequency analysis techniques , 1990, IEEE Trans. Acoust. Speech Signal Process..

[30]  S Micera,et al.  Improving detection of muscle activation intervals. , 2001, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[31]  Walter Herzog,et al.  A mathematical model of myoelectric signals obtained during locomotion , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.

[32]  K. Ishioka,et al.  Investigation on parametric analysis of dynamic EMG signals by a muscle-structured simulation model , 1992, IEEE Transactions on Biomedical Engineering.

[33]  Daniel W. Stashuk,et al.  Physiologically based simulation of clinical EMG signals , 2005, IEEE Transactions on Biomedical Engineering.

[34]  Simon Ferguson,et al.  Grasp Recognition From Myoelectric Signals , 2002 .

[35]  R. Kleissen,et al.  Electromyography in the biomechanical analysis of human movement and its clinical application. , 1998, Gait & posture.

[36]  L. Hadjileontiadis,et al.  Bispectral analysis of surface EMG , 2000, 2000 10th Mediterranean Electrotechnical Conference. Information Technology and Electrotechnology for the Mediterranean Countries. Proceedings. MeleCon 2000 (Cat. No.00CH37099).

[37]  Gabriella Olmo,et al.  Analysis of EMG signals by means of the matched wavelet transform , 1997 .

[38]  Lora A Major,et al.  Simulations of motor unit number estimation techniques , 2005, Journal of neural engineering.

[39]  Rama Chellappa,et al.  Estimation of intramuscular EMG signals from surface EMG signal analysis , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[40]  A. Adler,et al.  An improved method for muscle activation detection during gait , 2004, Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513).

[41]  Carlo J. De Luca,et al.  The Use of Surface Electromyography in Biomechanics , 1997 .

[42]  William Z Rymer,et al.  Motor unit action potential number estimation in the surface electromyogram: wavelet matching method and its performance boundary , 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..

[43]  Dario Farina,et al.  A fast and reliable technique for muscle activity detection from surface EMG signals , 2003, IEEE Transactions on Biomedical Engineering.

[44]  M J Campbell,et al.  Electrophysiological estimation of the number of motor units within a human muscle , 1971, Journal of neurology, neurosurgery, and psychiatry.

[45]  J. Basmajian Muscles Alive—their functions revealed by electromyography , 1963 .

[46]  Kazuo Yana,et al.  Surface electromyogram recruitment analysis using higher order spectrum , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.

[47]  K Kanosue,et al.  The number of active motor units and their firing rates in voluntary contraction of human brachialis muscle. , 1979, The Japanese journal of physiology.

[48]  George S. Moschytz,et al.  A software package for the decomposition of long-term multichannel EMG signals using wavelet coefficients , 2003, IEEE Transactions on Biomedical Engineering.

[49]  C.S. Pattichis,et al.  Time-scale analysis of motor unit action potentials , 1999, IEEE Transactions on Biomedical Engineering.

[50]  C. L. Nikias,et al.  Signal processing with higher-order spectra , 1993, IEEE Signal Processing Magazine.

[51]  S. Karlsson,et al.  Real-time system for EMG signal analysis of static and dynamic contractions , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.

[52]  Hiroshi Yokoi,et al.  An evolvable hardware chip for prosthetic hand controller , 1999, Proceedings of the Seventh International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems.

[53]  Y.C. Park,et al.  An adaptive M-wave canceler for the EMG controlled functional electrical stimulator and its FPGA implementation , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[54]  A. Del Boca,et al.  Myoelectric signal recognition using fuzzy clustering and artificial neural networks in real time , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[55]  G. D. P. M. DipTP Introduction to Surface Electromyography , 1998 .

[56]  Wen-Yaw Chung,et al.  Analog integrated circuit design for the wireless bio-signal transmission system , 1999, AP-ASIC'99. First IEEE Asia Pacific Conference on ASICs (Cat. No.99EX360).

[57]  P.A. Parker,et al.  Single motor unit myoelectric signal analysis with nonstationary data , 1994, IEEE Transactions on Biomedical Engineering.

[58]  Jianjun Fang,et al.  Decomposition of EMG signal by wavelet spectrum matching , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[59]  R. Lorente de Nó,et al.  Analysis of the distribution of the action currents of nerve in volume conductors. , 1947, Studies from the Rockefeller institute for medical research. Reprints. Rockefeller Institute for Medical Research.

[60]  George S. Moschytz,et al.  Analysis of wavelet features for myoelectric signal classification , 1998, 1998 IEEE International Conference on Electronics, Circuits and Systems. Surfing the Waves of Science and Technology (Cat. No.98EX196).

[61]  S. D. Nandedkar,et al.  Phase interaction in the compound muscle action potential: application to motor unit estimates , 1992 .

[62]  Daniel W. Stashuk,et al.  Motor unit estimates based on the automated analysis of F-waves , 1992, 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[63]  Constantinos S. Pattichis,et al.  A new technique for the classification and decomposition of EMG signals , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[64]  F. K. Lam,et al.  Fuzzy EMG classification for prosthesis control. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.