Affiliation:
1. Sport and Health Research Center, Physical Education Department, Tongji University, Shanghai, China
2. Physical Education and Sports Science Institute of Shanghai, Shanghai 200030, China
Abstract
The increased popularization of cycling has brought an increase in cycling-related injuries, which has been suggested to be associated with muscle fatigue. However, it still remains unclear on the utility of different EMG indices in muscle fatigue evaluation induced by cycling exercise. In this study, ten cyclist volunteers performed a 30-second all-out cycling exercise after a warm-up period. Surface electromyography (sEMG) from vastus lateralis muscle (VL) and power output and cadence were recorded and EMG RMS, MF and MPF based on Fourier Transform, MDF and MNF based on wavelet packet transformation, and C(n) based on Lempel–Ziv complexity algorithm were calculated. Utility of the indices was compared based on the grey rational grade of sEMG indices and power output and cadence. The results suggested that MNF derived from wavelet packet transformation was significantly higher than other EMG indices, indicating the potential application for fatigue evaluation induced by all-out cycling exercise.
Funder
Fundamental Research Funds for the Central Universities
Subject
General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine
Cited by
38 articles.
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