Assessment of human muscle fatigue from surface EMG signals recorded during isometric voluntary contractions by using a cosine modulated filter bank
Abstract
Human muscle fatigue involves both a decrease in the frequency and increase in the amplitude of a surface electromyographic (EMG) signal. Muscle fatigue is also related to a decrease of the force impeding to reach the same initial level of the maximum voluntary contraction (MVC). To determine muscle fatigue indices, a method is proposed by decomposing a surface EMG signal into 32-subbands. This decomposition was attained by using a cosine modulated filter bank. The surface EMG signals analyzed during this research were recorded during isometric voluntary contractions. Both the instantaneous mean frequency (IMF) and the instantaneous amplitude (IA) are estimated from the 32-subbands of the filter bank and are used as indicators of muscle fatigue. For evaluating the IMF and the IA estimated from the filter bank, two other standard techniques, the spectrogram and the smoothed pseudoWigner-Ville (SPWV) distribution, were also implemented. A regression-free area ratio, introduced first by Merletti, was adopted to compute an EMG index from both estimates the IMF and IA. These indices were then classified - by using a joint analysis of frequency and amplitude (JASA) - into one of the four muscle activity regions: muscle increase force, muscle recovery, muscle decrease force, and muscle fatigue. Surface EMG signals were recorded from 26 normal human subjects who exerted first 70% and then 100% of their MVC at intervals session of eight hours. It was found that EMG indices derived from the proposed filter bank are equivalent to those EMG indices derived from the spectrogram and the SPWV distribution. Furthermore, muscle fatigue indices derived from the filter bank indicated that they could be used as indices to determine human muscle fatigue. These results were confirmed by correlating the resulting muscle fatigue indices with perceived levels of discomfort reported by the subjects after performing an exertion of 70% MVC in hours two, four, and six.
Subject Area
Biomedical engineering|Kinesiology
Recommended Citation
Potes, Cristhian Mauricio, "Assessment of human muscle fatigue from surface EMG signals recorded during isometric voluntary contractions by using a cosine modulated filter bank" (2008). ETD Collection for University of Texas, El Paso. AAI1461163.
https://scholarworks.utep.edu/dissertations/AAI1461163