Mechanomyography-Based Closed-Loop Control of FES Enabling Prolonged Force Assistance by Monitoring Muscle Fatigue
Zehao Liu, Weiguang Huo, Ravi Vaidyanathan
AI summary
Problem
FES-induced muscle fatigue rapidly limits therapeutic efficacy, but reliable, non-invasive fatigue monitoring during stimulation is lacking, and adaptive control systems to manage it remain rare.
Approach
The system uses a pressure-based mechanomyography (PMMG) sensor for real-time fatigue tracking, processes the signal with a Kalman filter, and employs a fuzzy PID controller to dynamically modulate FES pulse width.
Key results
- Extended median FES repetitions by 112% over open-loop control
- Delayed onset of functional force failure (>50% drop) with strong statistical trend (p=0.0625)
- Increased cumulative normalized force (total work) by an average of 82.4%
- Validated adaptive control logic through simulation and in-vivo human trials
Why it matters
Provides a practical, adaptive FES solution that could significantly enhance rehabilitation outcomes for stroke and spinal cord injury patients by overcoming rapid muscle fatigue.
Abstract
Functional Electrical Stimulation (FES) is a crit- ical 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 effec- tive 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 capac- ity, 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 meaning- ful 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 sig- nificance (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.