Optimal trajectory planning for a constrained functional electrical stimulation-based human walking.

Area of Science:

• Biomedical Engineering
• Rehabilitation Robotics
• Biomechanics

Background:

• Functional electrical stimulation (FES)-based walking activates fewer muscles than voluntary walking, posing challenges for control.
• Muscle fatigue is a significant limitation in FES-assisted locomotion.
• Existing gait trajectories from able-bodied individuals may not be optimal for FES-based systems.

Purpose of the Study:

• To develop a dynamic model for FES-elicited walking incorporating orthosis and walker constraints.
• To design optimal stimulation and force profiles that minimize muscle activation and fatigue.
• To evaluate the feasibility of the proposed model and optimization algorithm for FES walking.

Main Methods:

• A dynamic model was created for FES-elicited walking, including constraints from an orthosis and a walker.
• An optimization algorithm was employed to determine stimulation and force profiles.
• The algorithm aimed to minimize muscle activations and arm reaction forces from the walker.

Main Results:

• The study simulated ten walking steps using the developed model and optimization algorithm.
• The simulation demonstrated the feasibility of the dynamic walking model.
• The optimization approach showed potential for minimizing muscle activation during FES walking.

Conclusions:

• The developed dynamic model accurately represents FES-elicited walking with assistive devices.
• Optimizing stimulation and force profiles, rather than relying on normal walking trajectories, is crucial for FES-based locomotion.
• This approach offers a promising strategy to reduce muscle fatigue and improve FES walking.