Analysis of Muscle's Electrical Activity During Dynamic Fatiguing Exercise Using Visibility Graph and Degree Statistics

Abstract

In this work, an attempt is made to analyses sEMG signals in nonfatigue and fatigue condition using the degree distribution of visibility graphs. The sEMG signals are recorded from the upper limb muscle namely the biceps brachii during dynamic contraction with a six-kilogram load. A total of 58 subjects volunteered for the study. The signals are preprocessed, and visibility graphs are constructed. The variation in the degree distribution is studied and characterized. The results indicate that the signals recorded are complex in nature. The degree distributions are distinct between nonfatigue and fatigue conditions. In fatigue, the percentage of higher degree nodes are more. Further, the decay rate of degree is larger in the case of nonfatigue indicating the signal is comparatively random. The statistical test indicates that the features extracted are significant with a P