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Reseach Article

Classification of Normal and Myopathy EMG Signals using BP Neural Network

by Mukesh Patidar, Nitin Jain, Ashish Parikh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 8
Year of Publication: 2013
Authors: Mukesh Patidar, Nitin Jain, Ashish Parikh
10.5120/11861-7645

Mukesh Patidar, Nitin Jain, Ashish Parikh . Classification of Normal and Myopathy EMG Signals using BP Neural Network. International Journal of Computer Applications. 69, 8 ( May 2013), 12-16. DOI=10.5120/11861-7645

@article{ 10.5120/11861-7645,
author = { Mukesh Patidar, Nitin Jain, Ashish Parikh },
title = { Classification of Normal and Myopathy EMG Signals using BP Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 8 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 12-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number8/11861-7645/ },
doi = { 10.5120/11861-7645 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:29:40.164008+05:30
%A Mukesh Patidar
%A Nitin Jain
%A Ashish Parikh
%T Classification of Normal and Myopathy EMG Signals using BP Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 8
%P 12-16
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Electromyography (EMG) signal is the muscle electrical activity. Electromyography is a technique for detecting and recording the electrical potential generated by muscle cells. This EMG signals are used in medical professionals to determine specific disorders. This paper basically deals with the analysis of different electromyography signals (NOR & MYO). In this paper, new method for classification of myopathy patient's and healthy subjects with the help of EMG signal by using back propagation neural network classifier are proposed. This methodology provided 96. 75 % accuracy in classification of Myopathy and normal EMG signals.

References
  1. S. Boisset, F Goubel, "Integrated electromygraphy activity and muscle work," J Applied Physiol, vol 35, pp. 695-702, 1972.
  2. R. Plonsey, "The active fiber in a volume conductor," IEEE Trans Biomed Eng, vol. 21, pp. 371-381, 1974.
  3. Carlo De Luca „Electromyography ?. Encyclopedia Of Medical Devices and Instrumentation (John G. Webster, Ed), John Wiley Publisher, 2006.
  4. M. A. Nussbaum, "Localized Muscle Fatigue" in Lecture Notes on Advanced Methods in Occupational Biomechanics,http://www. nussbaum. org. vt. edu/courses. htm, Last Access: Aug-2006.
  5. J. A. Gitter, and M. J. Czerniecki, "Fractal analysis of electromyographic interference pattern," Journal of neuroscience Methods, vol. 58, pp. 103-108, 1995.
  6. V. Gupta, S. Suryanarayanan, and N. P. Reddy,"Fractal analysis of surface EMG signals from the biceps," Intl. J. Medical informatics vol. 45, pp. 185-192, 1997
  7. X. Hu, Z. Wang, and X . Ren, "Classification of surface EMG signal with Fractal dimension," Journal of Zhejiang University Science, vol. 6 , no. 8, pp. 844-848, 2005.
  8. G. Golub and C. Van Loan, Matrix computation (2nd Ed. ) Baltimore, MD; John Hopkins, 1989.
  9. Kirk Baker "Singular Value Decomposition Tutorial" March 29, 2005 (Revised January 14, 2013).
  10. Trefethen, Lloyd N. ; Bau III, David. Numerical linear algebra. Philadelphia: Society for Industrial and Applied Mathematics. 1997 ISBN 978-0-89871-361-9.
  11. Stuart Russell and Peter Norvig. Artificial Intelligence A Modern Approach. p. 578. "The most popular method for learning in multilayer networks is called Back-propagation. It was first invented in 1969 by Bryson and Ho, but was largely ignored until the mid-1980s. "
  12. Arthur Earl Bryson, Yu-Chi Ho (1969). Applied optimal control: optimization, estimation, and control. Blaisdell Publishing Company or Xerox College Publishing. pp. 481.
  13. Abdulhamit Subasi, Mustafa Yilmaz, Hasan Riza Ozcalik, "Classification of EMG signals using wavelet neural network" , Journal of Neuroscience Methods 156 (2006). pp. 366.
Index Terms

Computer Science
Information Sciences

Keywords

Electromyography Backpropagation neural network Myopathy