Implementation of fuzzy control over FES-assisted locomotion for CVA patients

In this research, an Functional Electrical Stimulation (FES) system has been designed to assist Cerebral Vascular Accident (CVA) patients during the locomotion rehabilitation process. Cutaneous electrical stimulation applied over tibialis anterior muscle induced the ankle's dorsi flexion to certain degrees. An artificial neural network (ANN) was implemented to estimate the nonlinear mapping relation between stimulation levels and both ankle and knee angles for each individual subject. A rule-based fuzzy controller was used to real-time adjust the stimulating waveform so that convergence to a suitable desired flexion angle was achieved. A user friendly Windows-based interface was offered, where all fuzzy parameters and rules are adjustable, offering physical therapists' a flexible tool to find out most suitable angles for different individuals. The whole system including hardware and software has been successfully setup and tested with normal subjects in laboratory; it has also been installed to operate with a treadmill as a locomotion rehabilitation system in the hospital, where clinical tests will be held.