Application of mean and median frequency methods for identification of human joint angles using EMG signal

Abstract

The analysis of surface electromyography (EMG) signals is generally based on three major issues, i.e., the detection of muscle force, muscle geometry, and muscle fatigue. Recently, there are no any techniques that can analyse all the issues. Mean frequency (MNF) and median frequency (MDF) have been successfully applied to be used as muscle force and fatigue indices in previous studies. However, there is the lack of consensus upon the effect of muscle geometry on the basis of varying joint angles. In this paper, the modification of MNF and MDF using a min-max normalization technique was proposed to provide a consistent relationship between feature value and joint angle across subjects. The results show that MNF and MDF extracted from normalized EMG showed a stronger linear relationship with elbow joint angle compared to traditional MNF and MDF methods. Modified MNF and MDF features increased with increasing elbow angle during isometric flexion. As a result of the proposed technique, modified MNF and MDF features could be used as a universal index to determine all the issues involving muscle fatigue, muscle force, and also muscle geometry.