Title: Advancements in soft computing methods for EMG classification

Authors: Manvinder Kaur; Saravjeet Singh; Dhanonjoy Shaw

Addresses: Department of Biomedical Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal 131039, Haryana, India ' Department of Biomedical Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal 131039, Haryana, India ' Indira Gandhi Institute of Physical Education and Sports Sciences, University of Delhi, New Delhi 110018, Delhi, India

Abstract: Electromyography (EMG) signals that represent the electrical activity of muscles are increasingly used for various clinical and biomedical applications. Detection, processing and classification of EMG signals require advanced soft computing methods to gain better understanding and precise evaluation of these signals in various applications such as rehabilitation technology, neurophysiological disorders and assistive technological findings. This paper provides comprehensive overview of the different methods for classification of EMG signals.

Keywords: EMG classification; electromyography; soft computing; EMG signals; rehabilitation technology; neurophysiological disorders; assistive technology.

DOI: 10.1504/IJBET.2016.075428

International Journal of Biomedical Engineering and Technology, 2016 Vol.20 No.3, pp.253 - 271

Received: 04 May 2015
Accepted: 06 Sep 2015
Published online: 22 Mar 2016 *

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