EMG pattern discrimination for patient-response control of FES in paraplegics for walker supported using artifical neural network (ANN)

Abstract

FES (functional electrical stimulation) encompasses the use of electricity in functioning neural substrates. FES is used to restore lower limb function to individuals paralyzed by spinal cord injury. The system determines a patient-responsive manner using above-lesion surface EMG signals to activate standing and walking functions. In this work, classification of EMG patterns which were used by FES to restore lower limb function of walker-supported walking patients was done by using ANN.