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Updated: Jul 17, 2026

Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test
Published on: July 27, 2015
Linear and non-linear features of surface EMG during fatigue and recovery period
Yang Hong-Chun1, Wang Du-Ming, Wang Jian
1Coll. of Psychology & Behavior Science, Zhejiang University, Hangzhou, China.
Abstract:
To investigate possible factors that affect the sEMG signal features, we analyzed the sEMG signals in bicep bracii (BB) muscle during fatiguing isometric flexions and recovery periods across a range of force levels. Twelve males performed isometric elbow flexions at 40%, 60%, 80% and 100% of their maximal voluntary contraction (MVC) with joint angle keeping at 90deg. And then they performed 3 seconds of MVC at the 2nd, 4th, 6th, 8th , 10th, 20th, 30th, 60th and 120th second respectively during recovery periods. SEMG signals in BB were analyzed using both linear and non-linear methods to get parameters such as average EMG (AEMG), mean power frequency (MPF), Lempel_Ziv complexity (C(n)) and determinism% (%DET). Non-linear parameter C(n) decreased whereas %DET increased during fatiguing flexions. There was no regularity in AEMG in recovery periods. MPF, C(n) and %DET recovered significantly only by seconds rest, and they regressed rapidly in the initial 10 seconds and then slowed down in the later. The rapid changes of SEMG linear and non-linear parameters in recovery periods suggested that central controlling factor may play a more important role in shaping sEMG signals.

