Design Issues of Spring Brake Orthosis: Evolutionary Algorithm Approach

Abstract

Spring Brake Orthosis (SBO) generates the swing phase of gait by employing a spring at the knee joint to store energy during the knee extension through quadriceps stimulation, which is then released to produce knee flexion. Spring parameters (for the knee flexion part) and the stimulus signal parameters (for the knee extension part) are the only optimizable quantities amongst the factors that determine the SBO generated knee joint trajectory. In this work, subject specific optimum spring parameters (spring constant, spring rest angle) for SBO purposes are obtained using genetic algorithms (GA). The integral of time-weighted absolute error (ITAE) between the reference and actual trajectory is defined as the cost function.

The later part of the optimization procedure (second half of the swing phase) identified two potential objective functions: (i) the ITAE between the reference (natural) and actual trajectory and (ii) the final angular velocity attained by the knee joint at the end of the excursion, which should be as low as possible to avoid (a) excessive stimulation, caused by the trajectory requirement, which causes fatigue, (b) knee damage. Multi-objective GA (MOGA) is used for this purpose.

Finally, the stimulus signal parameters are optimized for the functional electrical stimulation (FES) driven extending knee for two objectives: (i) square of the knee joint orientation nearest to the full extension (0°) during the whole FES assisted excursion and any instant t _c and (ii) square of the knee joint angular velocity at t _c, resulting in optimal knee joint trajectory.