Title :
EMG pattern discrimination for patient-response control of FES in paraplegics for walker supported using artifical neural network (ANN)
Author :
Kocyigit, Yücel ; Karlik, Bekir ; Korürek, Mehmet
Author_Institution :
Fac. of Eng., Celal Bayer Univ., Manisa, Turkey
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
Keywords :
ART neural nets; autoregressive processes; biocontrol; bioelectric phenomena; biomechanics; electromyography; handicapped aids; legged locomotion; medical signal processing; muscle; neurophysiology; pattern classification; EMG pattern classification; EMG pattern discrimination; FES; above-lesion surface EMG signals; artifical neural network; autoregressive model; functional electrical stimulation; functioning neural substrates; lower limb function; paralyzed individuals; paraplegics; patient-response control; patient-responsive manner; spinal cord injury; standing; walker; walker-supported walking patients; walking functions; Artificial neural networks; Central nervous system; Centralized control; Control systems; Ear; Electromyography; Intelligent networks; Legged locomotion; Muscles; Signal processing;
Conference_Titel :
Electrotechnical Conference, 1996. MELECON '96., 8th Mediterranean
Conference_Location :
Bari
Print_ISBN :
0-7803-3109-5
DOI :
10.1109/MELCON.1996.551219
