부산대학교 도서관

Muscle fatigue, as a common physiological phenomenon, has attracted much attention in the fields of rehabilitation and athletic training. A wearable technology for monitoring the muscle fatigue anytime and anywhere is urgently needed. In this paper we apply Electrical impedance myography (EIM) technique, usually used for non-invasive detection of neuromuscular diseases with the four-electrode array, for evaluation of the local muscle fatigue status via the variation of electrical impedance. An equivalent multilayer inhomogeneous 3D finite element model of human arm was built in order to optimize the four-electrode configuration to improve EIM detection sensitivity. Current density in muscle layer and differential potential of induction electrodes were selected as the evaluation indexes for optimization. Then the in vivo experiments of dynamic contraction with different maximal voluntary contractions (MVC) were performed on the biceps brachii muscle of eight healthy volunteers. The results showed that muscle resistance ( $R$ ) decreased almost $8~\Omega $ from the completely relaxed muscle to exhaustion, which is the same trend as for the median frequency (MF) of measured surface electromyography (sEMG) signals. The model and experiments in this paper indicate the feasibility and efficiency of EIM for detection of muscle fatigue using wearable devices.