Optimal Control of Walking with Functional Electrical Stimulation: Inclusion of Physiological Constraints

Automatic sensory driven control of functional electrical stimulation (FES) assistive systems is of interest for neurorehabilitation of hemiplegic individuals. MEMS based accelerometers and gyroscopes are likely candidates for sensors within a practical FES system. In this paper we demonstrate that static optimization in the space of angular velocities that incorporates physiological constraints is an effective method for the synthesis of stimulation pattern with respect to the use of dynamic programming for optimization. The example presented in the paper uses the walking pattern from a healthy individual and parameters that are characteristic for a hemiplegic individual. Optimization was based on minimization of the tracking error from the desired trajectory defined in the phase space of angular velocities of leg segments and muscle effort. The evaluation of the applicability of the static optimization was based on the analysis of the tracking of joint angles. We found that maximal tracking error was bellow 7 degrees, which belongs to the typical variation of the joint angles during normal walking of a healthy individual.