Genetic Algorithm for electromyography (EMG) and human locomotion

Abstract

The biomechanical analysis assists to provide evidences in the performance of the system used for stroke rehabilitation of lower and upper limb of human body. This could be done by providing a better understanding of human lower extremities movement through implementation of electromyography (EMG). As human body is a complex biomechanical machine, conducting analysis using only EMG is not sufficient in representing muscle coordination pattern for functional task (i.e. walking). For that, Genetic Algorithm (GA) is implemented in the selection process of best-fit mathematical model and its parameters used in conversion of EMG signal into estimated torque. Several experiments are conducted to validate the proposed method. The field of management and rehabilitation of motor disability is identified as one important application area. Based on relevant literature, the present paper asserts that scientific analysis of human movement patterns can materially affect patient treatment. It provides evidence that patient management and rehabilitation processes in central neurological disorders can be improved through EMG techniques. The use of electromyography for clinical planning in the treatment process of patients helps providing future directions in research, development and applications of scientific analysis of human movement.