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

Computation of an analytical control solution for functional electrical stimulation (FES) and orthosis-based walking is a daunting task due to the inherent nonlinear structure of the human muscle and walking dynamics. Furthermore, since muscle fatigue and available muscle force are major limiting issues, we explored the domains of numerical optimal control methods to address these issues. We first focused on the development of simple models to represent walking movement. These models account for walking produced via a limited number of activated muscles using FES along with a novel orthosis, and an assistive device such as a walker. Using dynamic optimization, the lower limb joint angle trajectories and control inputs were computed by minimizing the cost function comprising muscle stimulation variables and forces required to push a walker. Computer simulations for optimizations were performed across a range of step lengths to find the optimal step length (minimum cost per distance). Then, the optimal steady-state initial angular velocity (for optimal step length) was computed from a range of angular velocities of the lower-limb segments. We found considerable differences between able-bodied walking trajectories and the optimal walking trajectories for FES and orthosis-based walking. Based on this computer simulation study, we recommend that instead of arbitrary selection of stimulation profiles or gait parameters, dynamic optimization can be utilized to compute gait parameters such as step length, steady state velocity, and joint angle trajectories in future clinical implementation of FES and orthosis-based walking.