Dynamic Optimization of FES and Orthosis-Based Walking Using Simple Models.

Area of Science:

• Biomechanics
• Robotics
• Rehabilitation Engineering

Background:

• Functional electrical stimulation (FES) and orthosis-based walking present challenges due to complex human muscle and walking dynamics.
• Muscle fatigue and force limitations are significant constraints in FES-assisted locomotion.

Purpose of the Study:

• To explore numerical optimal control methods for FES and orthosis-based walking.
• To develop simple models of walking movement incorporating FES, orthosis, and assistive devices like walkers.
• To compute optimal gait parameters using dynamic optimization.

Main Methods:

• Developed simplified models for FES and orthosis-assisted walking.
• Employed dynamic optimization to compute lower limb joint trajectories and control inputs.
• Minimized a cost function including muscle stimulation and walker-pushing forces.
• Performed simulations to determine optimal step length and steady-state angular velocity.

Main Results:

• Computed optimal walking trajectories using dynamic optimization.
• Identified significant differences between optimal FES/orthosis walking and able-bodied walking.
• Determined optimal step length and steady-state initial angular velocity.

Conclusions:

• Dynamic optimization is a viable method for computing gait parameters for FES and orthosis-based walking.
• Recommends using dynamic optimization for clinical implementation instead of arbitrary parameter selection.
• Suggests optimizing step length, velocity, and joint trajectories for improved FES-assisted gait.