Novel time-frequency approach for muscle fatigue detection based on sEMG

• Published in: 2012 IEEE Biomedical Circuits and Systems Conference (BioCAS) pp. 364 - 367
• Main Authors: Fengjun Bai, Lubecki, T. M., Chee-Meng Chew, Chee-Leong Teo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2012
• Subjects: Continuous wavelet transforms; Dynamics; Fatigue; Force; Muscles; Time frequency analysis
• ISBN: 1467322911; 9781467322911
• ISSN: 2163-4025; 2766-4465
• DOI: 10.1109/BioCAS.2012.6418421

Muscle fatigue is the decrease in its ability to generate a target force. In this paper, a novel muscle fatigue detection algorithm based on sEMG signal is developed. Short-time Fourier transform (STFT) and continuous wavelet transform (CWT) are used to extract features of sEMG signal (mean frequency and signal power). Further signal power and the estimated power relative changes are calculated to derive the fatigue evaluation and generate the general fatigue levels. sEMG signals generated from subjects' Biceps Brachii muscles under different muscle contraction trials were used to evaluate the feasibility and effectiveness of the proposed fatigue detection methods. Results from STFT and CWT are compared. The results also show that the proposed method is reliable in the analysis of muscle fatigue during isometric and dynamic contractions and quantifying the discrete muscle fatigue levels.