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

Volume

3

fYear

1996

fDate

13-16 May 1996

Firstpage

1439

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrotechnical Conference, 1996. MELECON '96., 8th Mediterranean

Conference_Location

Bari

Print_ISBN

0-7803-3109-5

Type

conf

DOI

10.1109/MELCON.1996.551219

Filename

551219