Classification of surface electromyographic signal using fuzzy logic for prosthesis control application

Author

Ahmad, Siti A. ; Ishak, Asnor J. ; Ali, Sawal

Author_Institution

Dept. of Electrcial & Electron. Eng., Univ. Putra Malaysia, Serdang, Malaysia

fYear

2010

fDate

Nov. 30 2010-Dec. 2 2010

Firstpage

471

Lastpage

474

Abstract

This paper describes the classification stage of an electromyographic (EMG) control system for prosthetic hand application. Moving ApEn was used as main method to extract features from the two channels of surface EMG signal at the forearm of the upper limb. A fuzzy logic system is used to classify the extracted information in discriminating the final grip posture. The results demonstrate the ability of the system to classify the information related to different grip postures.

Keywords

electromyography; entropy; fuzzy logic; medical control systems; medical signal processing; prosthetics; signal classification; EMG control system; fuzzy logic; grip postures; moving ApEn algorithm; moving approximate entropy algorithm; prosthesis control application; prosthetic hand application; sEMG signal classification; surface electromyography; upper limb forearm EMG; Artificial intelligence; Contracts; Copper; Educational institutions; Electromyography; Silicon; fuzzy logic; moving ApEn; prosthesis control; surface EMG; upper limb;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Sciences (IECBES), 2010 IEEE EMBS Conference on

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-4244-7599-5

Type

conf

DOI

10.1109/IECBES.2010.5742283

Filename

5742283