FRACTAL-BASED CLASSIFICATION OF ELECTROMYOGRAPHY (EMG) SIGNAL IN RESPONSE TO BASIC MOVEMENTS OF THE FINGERS

Abstract

Investigating human movements is the most important issue in rehabilitation science. Movements of fingers as one of the major movements of human has been considered by many scientists. Therefore, decoding of finger movements by analysis of related biosignal is very important to consider. In this research, we do the complexity analysis on the Electromyography (EMG) signal that was recorded due to basic movements of fingers. In fact, the EMG signal was classified in case of different movements of fingers by fractal analysis. The result of analysis showed that the EMG signal has the greatest and lowest fractal dimension (complexity) in case of thumb finger flexion and little finger extension. In further attempts, the fractal theory can be applied to investigate the influence of other types of stimulation on variations of the complexity of muscles’ reactions.