Evaluation of spreading factor inertial weight PSO for FLC of FES-assisted paraplegic indoor rowing exercise

This paper describes the evaluation of the spreading factor inertia weight Particle Swarm Optimization (PSO) for the fuzzy logic control (FLC) of FES-assisted paraplegic indoor rowing exercise (FES-rowing). The FES-rowing is introduced as a total body exercise for rehabilitation of lower extremities through the application of functional electrical stimulation (FES). FLC is used to control the knee trajectories for smooth rowing manoeuvre and minimize the total electrical stimulation required by the muscles. PSO is implemented to optimize the parameter of the FLC. The objective function specified is to minimize the mean squared error of knee angle trajectory. The inertia weight of the PSO is updated using spreading factor technique and it performance is compared to the performance of PSO with time variant inertia weight. In view of good results obtained, it is concluded that Spreading Factor Inertia weight PSO is able to obtain the optimal parameter for FLC of FES-rowing.