Revolutionizing motor dysfunction treatment: A novel closed-loop electrical stimulator guided by multiple motor tasks
Xudong Guo1, Peng Wang1, Xiaoyue Chen1
1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, PR China.
Medical Engineering & Physics
|June 21, 2024
Summary
This study introduces a novel biofeedback electrical stimulator using predictive control to adapt functional electrical stimulation (FES) parameters, overcoming muscle fatigue for motor dysfunction recovery.
Area of Science:
- Biomedical Engineering
- Neurorehabilitation
- Control Systems
Background:
- Functional electrical stimulation (FES) aids motor function recovery in neurological disorders.
- Muscle fatigue limits conventional FES efficacy.
- Novel adaptive stimulation is needed to improve FES outcomes.
Purpose of the Study:
- To develop and validate a biofeedback electrical stimulator with predictive control for adaptive FES.
- To address muscle fatigue challenges in FES protocols.
- To enable precise modulation of stimulation parameters for motor task execution.
Main Methods:
- Developed a biofeedback electrical stimulator with multi-motor tasks and predictive control.
- Modeled stimulated muscle using a time-varying Hammerstein model.
- Employed recursive least squares for online parameter identification and predictive control for closed-loop adaptation.
Main Results:
- Accurate identification of Hammerstein model parameters with low RMS error (3.83%).
- Predictive control effectively adjusted stimulus parameters for desired sEMG trajectories.
- Validated on elbow, wrist, and grasping motor tasks.
Conclusions:
- The developed biofeedback electrical stimulator shows potential for assisting patients with motor dysfunction.
- This intelligent electrical stimulation model offers a foundation for advanced neurorehabilitation.
- Adaptive FES control can improve functional recovery outcomes.
