Assessment of Muscle Fatigue Based on Motor Unit Firing, Muscular Vibration and Oxygenation via Hybrid Mini-Grid sEMG, MMG, and NIRS Sensing
Weichao Guo, Xinjun Sheng, Xiangyang Zhu
Abstract
It is vital to measure muscular fatigue for human-machine interaction (HMI) and avoiding muscle impairment. This paper presents a novel approach to comprehensively evaluate muscle fatigue through the fusion of mini-grid surface electromyography (sEMG), mechanomyography (MMG) and near-infrared spectroscopy (NIRS). A hybrid mini-grid sEMG, MMG and NIRS sensor system was developed, forming an instrument to measure motor unit action potential trains (MUAPt), low-frequency myofiber vibration and oxygen metabolism. Muscle fatigue induced experiment was performed via a sustained isometric contraction at 50% of maximal voluntary contraction (MVC) force with ten subjects. MUAPts were decomposed from the four-channel array of sEMG signals, and the firing rate of specific MUs was calculated to measure fatigue process. Furthermore, root mean square (RMS) and median frequency (MDF) of sEMG/MMG, blood volume (BV) and muscle oxygenation (△HbO<sub>2</sub>) extracted from NIRS, were proposed as fatigue metrics. The variation and correlation analysis among fatigue metrics provided a detailed and reliable physiological assessment on muscle fatigue, gaining a synthetical understanding of muscle fatigue mechanisms. The outcomes of this study have great potential applications in sports, clinical diagnosis and HMI.