The methods of EMG data processing


Abstract

The article presents both the methods of data processing of electromyography (EMG), and EMG signal analysis using the implemented piece of software. This application is used to load the EMG signal stored in a file with the .C3D extension. The analysis was conducted in terms of the highest muscles activaton during exercise recorded with Motion Capture technique.


Keywords

EMG; Motion Capture; File C3D

[1] Basmajian J. V., De Luca C. J.: Muscles Alive: Their Functions Revealed by Electromyography, 1985
[2] Guglielminotti P., Merletti R.: Effect of electrode location on surface myoelectric signal variables: a simulation study, 1992.
[3] Laterza F., Olmo G.: Analysis of EMG signals by means of the matched wavelet transform, 1997.
[4] Gabor D.: Theory of communication,1946.
[5] Ismail A.R., Asfour S.S.: Continuous wavelet transform application to EMG signals during human gait, 1998.
[6] Pattichis C.S., Pattichis M.S.: Time-scale analysis of motor unit action potentials, 1999.
[7] Kumar D.K., Pah N.D., Bradley A.: Wavelet analysis of surface electromyography to determine muscle fatigue, 2003.
[8] Piper H.: Electrophysillogie Muschliche Muskeln, 1912.
[9] Cohen L.: Time-frequency analysis. Englewood Cliffs, 1995.
[10] Syeed A.M, Jones D.L.: Optimal kernel for nonstationary spectral estimation, 1995.
[11] Ricamato A.L., Absher R.G., Moffroid M.T., Tranowski J.P.: A time-frequency approach to evaluate electromyographic recordings, 1992.
[12] Davies M.R., Reisman S.S.: Time frequency analysis of the electromyogram during fatigue, 1994.
[13] Amin M., Cohen L., Williams W.J.: Methods and Applications for Time Frequency Analysis,1993.
[14] Graupe D., Cline W.K.: Functional Separation of EMG signals via ARMA identification. 1975.
[15] Sherif M.H.: Stochastic Model of Myoelectric Signals for Movement Pattern Recognition in Upper Limb Prostheses, 1980.
[16] Doerschuk P.C., Gustafson D.E., Willsky A.S.: Upper extremity limb function discrimination using EMG signal analysis,1983.
[17] Zhou Y., Chellappa R., Bekey G.: Estimation of intramuscular EMG signals from surface EMG signal analysis,1986.
[18] Kiryu T., Saitoh Y., Ishioka K.: Investigation on parametric analysis of dynamic EMG signals by a muscle-structured simulation model, 1992.
[19] Rosenfalck P.: Intra- and extracellular potential fields of active nerve and muscle fibres. A physico-mathematical analysis of different models,1969.
[20] Nandedkar S.D., Stålberg E.: Simulation of single muscle fibre action potentials,1983.
[21] Nandedkar S.D, Barkhaus P.E.: Phase interaction in the compound muscle action potential: application to motor unit estimates, 1992.
[22] Englehart K.B., Parker P.A.: Single motor unit myoelectric signal analysis with nonstationary data,1994.
[23] Zhang Y.T, Herzog W., Liu M.M.: A mathematical model of myoelectric signals obtained during locomotion, 1995.
[24] Karlsson S., Nystrom L.: Real-time system for EMG signal analysis of static and dynamic contractions, 1995.
[25] https://www.c3d.org/
Download

Published : 2017-03-30


Serej, M., & Skublewska - Paszkowska , M. (2017). The methods of EMG data processing. Journal of Computer Sciences Institute, 3, 38-45. https://doi.org/10.35784/jcsi.591

Michał Serej  michalserej@gmail.com
Institute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland  Poland
Maria Skublewska - Paszkowska  
Institute of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland  Poland