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
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.