Neuromuscular fatigue analysis of soldiers using DWT based EMG and EEG data fusion during load carriage

Abstract

This research reports peripheral and central fatigue of soldiers during load carriage on a treadmill. Electromyography (EMG) was used to investigate peripheral fatigue of lower extremity muscles and electroencephalography (EEG) was used for central fatigue detection on frontal lobe of the brain. EMG data were processed using Db5 and Rbio3.1 discrete wavelet transforms with a six levels of decomposition and EEG data were iteratively transformed into multi-resolution subsets of coefficients using Db8 wavelet function to perform the power spectrum analysis of alpha, beta and theta waves. Peak alpha frequency (PAF) was also calculated for EEG signals. A majority of significant results (p < 0.05) from EMG signals were observed in the lower extremity muscles using Db5 wavelet function at all conditions. While, significant changes were only observed during unloaded conditions at the frontal cortex. Significant changes (p < 0.05) in the PAF was also detected at certain conditions in the pre-frontal and frontal cortex. A significant increase in heart rate and rating of perceived exertion values were seen at all conditions. Hence, peripheral fatigue was the cause of the exhaustion sustained by the soldiers during load carriage which sends signals to the brain for decision making as to stop the exercise.