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Modeling and control of functional electrical stimulation cycling training system
Mingxu Sun1,2, Fangyuan Cheng1, Tingting Wang1
1School of Electrical Engineering, University of Jinan, Jinan, 250022, China.
Scientific Reports
|February 22, 2025
Summary
This study optimized functional electrical stimulation (FES) for cycling rehabilitation using a novel control algorithm. The adaptive system improved training stability and duration, enhancing patient outcomes.
Area of Science:
- Rehabilitation Engineering
- Biomedical Engineering
- Control Systems
Background:
- Functional electrical stimulation (FES) is a rehabilitation technique.
- Current FES methods rely on manual, trial-and-error adjustments by therapists.
- This limits optimal stimulation pattern determination for effective rehabilitation.
Purpose of the Study:
- To develop an optimized FES control system for cycling rehabilitation.
- To maximize torque efficiency through advanced modeling and control algorithms.
- To improve the stability and duration of FES-assisted cycling training.
Main Methods:
- Proposed a pedal hill modeling approach for optimal stimulus mode.
- Developed a composite control algorithm integrating particle swarm optimization (PSO), back propagation (BP) neural network, and proportional integral derivative (PID) control.
- Recruited six participants for experimental validation.
Main Results:
- The proposed adaptive pulse width control system demonstrated superior performance.
- Key metrics including root mean square error (RMSE) and average error (AVE) showed significant improvement.
- Participants experienced longer continuous training times and more stable cycling speeds compared to fixed or no control conditions.
Conclusions:
- The novel FES control system effectively optimizes stimulation patterns for cycling.
- Adaptive pulse width control enhances training efficiency and user experience in FES rehabilitation.
- This approach offers a more stable and effective method for FES-assisted cycling training.
