Sensitivity and stability analysis of sEMG indices in evaluating muscle fatigue of Rectus Femoris caused by all-out cycling exercise

Abstract

Objective: This experiment was designed to explore the optimum surface Electromyography (sEMG) indices in evaluating muscle fatigue of Rectus Femoris (RF) caused by all-out cycling exercise. Methods: eight professional cyclists participated in this study. Each subject performed 60-second all-out cycling exercise for one time and the sEMG of RF was recorded during the process. The braking torque imposed on cycling motion was 8% of each subject's weight. Combined with time-domain, flourier transform, wavelet packet transformation and nonlinear analysis method, RMS, MPF, MNF and nonlinear Lempel-Ziv complexity C(n) were calculated. Sensitivity and stability of each index in evaluating muscle fatigue of RF caused by all-out cycling exercise was compared and analyzed. Results: MPF?MNF and C(n) all decreased during muscle fatigue, having significant negative correlations with cycling exercise endurance time and significant positive correlations with pedaling rate and power output. MNF was found to have the highest fatigue sensitivity while RMS had the lowest fatigue sensitivity. The sensitivity of MPF and C(n) had no significant difference. As refer to stability, C(n) was the optimum index and MNF the second, followed by MPF and RMS. Conclusions: During all-out cycling exercise process, RF did vigorous dynamic contraction, making sEMG collected from the surface of RF nonlinear and non-stationary. The index of MNF based on wavelet packet transformation and the index of Lempel-Ziv complexity C(n) based on nonlinear analysis demonstrated high utility, suggesting the potential application of these methods as fatigue indices in evaluating muscle fatigue caused by all-out cycling exercise.