DECODING OF SIMPLE HAND MOVEMENTS BY FRACTAL ANALYSIS OF ELECTROMYOGRAPHY (EMG) SIGNAL

Abstract

Analysis of body movement is the most important aspect of rehabilitation science. Hand movement as one of the major movements of humans has aroused the attention of many researchers. For this purpose, decoding of movements by analysis of the related bio signals is very important. In this research, complexity analysis of Electromyography (EMG) signal that was recorded due to simple hand movements is done. For this purpose, we employ fractal dimension as the indicator of complexity of signal in this research. The EMG signal was recorded from subjects while they did six simple hand movements and accordingly we applied fractal analysis on the signal. The result of our analysis showed that the EMG signal has the greatest and lowest fractal dimension in case of lateral (for holding thin, flat objects) and hook (for supporting a heavy load) hand movements. The capability seen in this research can be applied to the analysis of other types of bio signals in order to investigate the reaction of humans to different types of stimuli.