Mechanomyography-Based Closed-Loop Control of FES Enabling Prolonged Force Assistance by Monitoring Muscle Fatigue

Abstract

Functional Electrical Stimulation (FES) is a critical therapy for motor rehabilitation, yet the rapid onset of muscle fatigue severely limits its efficacy. This paper presents the design, implementation, and validation of a comprehensive, intelligent closed-loop FES system designed to provide effective force assistance by actively sensing FES-induced fatigue. The system integrates a pressure-based Mechanomyography (P_MMG) sensor for real-time feedback of muscle force capacity, a Kalman filter for robust signal estimation, and a fuzzy-logic-based Proportional-Integral-Derivative (PID) controller to modulate FES dynamically. The developed system was first validated in a comprehensive simulation and then tested with four healthy participants. The results demonstrate that the closed-loop fuzzy PID controller yielded a functionally meaningful improvement in performance over an open-loop-controlled protocol. The system substantially extended the duration of effective FES and, critically, delayed the onset of functional failure (indicated by a force drop >50%), with performance improvements showing a strong trend toward statistical significance (Wilcoxon signed-rank test, p = 0.0625). This work delivers a practical and effective solution for managing fatigue during FES therapy, holding the potential to significantly enhance rehabilitation outcomes.