Validating Predictive Simulation-Derived Electrical Stimulation Cycling in a Person with Spinal Cord Injury

Area of Science:

• Rehabilitation Engineering
• Biomedical Engineering
• Neuroscience

Background:

• Functional electrical stimulation (FES) is a key rehabilitation tool, particularly for FES cycling, improving health and quality of life.
• Optimizing FES cycling requires precise stimulation parameters, with less focus on stimulation profiles compared to timing strategies.

Purpose of the Study:

• To develop and test a novel predictive simulation-derived stimulation profile for FES cycling.
• To compare the effectiveness of this new profile against the conventional bang-bang control strategy.

Main Methods:

• Developed coupled torque-driven and muscle-driven models for FES cycling.
• Defined and solved an optimal control problem to derive the stimulation profile.
• Implemented the derived signal in an experimental setting and validated it on a spinal cord injury volunteer.

Main Results:

• The predictive simulation-derived stimulation profile demonstrated superior performance.
• Compared to the bang-bang control strategy, the new profile resulted in increased power output, cadence, and balance.
• This represents the first successful implementation of a predictive simulation-derived stimulation profile for FES cycling.

Conclusions:

• Predictive simulations offer a powerful approach to optimize FES cycling rehabilitation.
• The developed stimulation profile significantly enhances user outcomes in FES cycling.
• This strategy holds potential for improving rehabilitation effectiveness for individuals with spinal cord injuries.