| Aim: Using linear and non-linear signal analysis, detect the response of sEMG and EEG signal to biceps brachii fatiguing induced by sustained isometric non-MVC. Lay a foundation for effective and reliable fatigue evaluation system and for understanding fatigue mechanisms. Method:This study include two experiments. In experiment 1, 14 male undergraduates performed three different isometric fatiguing tasks with the elbow flexion muscles at 50%, 70% and 90% MVC, sEMG signals were collected from three different electrode locations in biceps brachii. In experiment 2, 10 male undergraduates performed two different isometric fatiguing tasks with the elbow flexion muscles at 5kg and 10kg, sEMG signals were collected in biceps brachii and synchronously EEG signals were collected from scalp. Then amplitude, spectral, Lempel-Ziv complexity C(n) and RQA(DET%) of sEMG and EEG were calculated. Result: (1) Both AEMG and DET% increase linearly while both MPF and C(n) decreased linearly during different isometric elbow flexion fatigue tasks. (2) Except AEMG, the slopes of MPF, C(n) and DET% showed no significant electrode location dependence but showed a significant load dependence. (3) The average of AEMG,MPF, C (n) and DET% showed significant electrode location dependence. The load dependence is only showed in average AEMG. The average of MPF, C(n) and DET% showed no significant load dependence. (4) Of EEG, the average AEEG increased while the average MPF and C(n) decreased in muscle fatigue. Moreove, this phenomenon are distributed evenly across the entire scalp, but load only influence AEEG, MPF and C(n) at Fz. Conclusion: Both MPF and C(n) of sEMG decreased linearly while DET% increase linearly during isometric exercise-induced local muscle fatigue. And the slopes of them showed significant load dependence. AEEG of EEG increased generally while MPF and C(n) increased generally during localmuscle fatigue. AEEG, MPF and C(n) at prefrontal area showed a load dependence.
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