Wearable sensor technology and medical robotics for fatigue assessment using electromyography signal processing

This study integrates Wearable sensor technology and medical robotics to propose a unilateral approach to assessing fatigue in passive lower limb exoskeleton users. Addressing the one-sidedness in evaluating the fatigue status of wearers of passive lower limb exoskeletons, a comprehensive exoskeleton efficacy evaluation method combining muscle fatigue threshold value Electromyographic Fatigue Threshold (EMGFT), biomechanical analysis, and subjective Rating of Perceived Exertion (sRPE) scale is proposed. Unlike traditional methods relying solely on surface electromyography (sEMG) or blood oxygen saturation measurement, the proposed method can effectively enhance the accuracy of passive lower limb exoskeletons efficacy evaluation. By capturing movements for gait comparison analysis, spatial position information and muscle force data are obtained, along with calculation of ankle joint stability. Subject's sEMG is pre-processed to calculate muscle fatigue baseline values; combined with sRPE scores and ankle joint deviation variance, EMGFT is subjected to subjective and objective validation. Results indicate that the proposed method effectively alleviates fatigue by 30.3%.