The University of Southampton
University of Southampton Institutional Repository

Surface EMG classification using moving approximate entropy

Ahmad, Siti A. and Chappell, P.H. (2008) Surface EMG classification using moving approximate entropy In International Conference on Intelligent and Advanced Systems, 2007. ICIAS 2007. IEEE., pp. 1163-1167. (doi:10.1109/ICIAS.2007.4658567).

Record type: Conference or Workshop Item (Paper)

Abstract

Moving approximate entropy has been proposed as a new method to extract information from the surface electromyographic signal. Twenty subjects performed wrist flexion/extension, isometric contraction and co-contraction while electromyographic signals were recorded with surface electrodes. A moving data window of 200 values was applied to the data (moving approximate entropy). The results show that there is regularity in an EMG signal at the beginning and end of a muscle contraction with low regularity during the middle part.

Full text not available from this repository.

More information

Published date: 2008
Additional Information: Imported from ISI Web of Science
Organisations: EEE

Identifiers

Local EPrints ID: 269719
URI: http://eprints.soton.ac.uk/id/eprint/269719
PURE UUID: 46b29219-bd2e-4aeb-b8cf-bf3a6e985332

Catalogue record

Date deposited: 21 Apr 2010 07:46
Last modified: 06 Sep 2017 16:31

Export record

Altmetrics

Contributors

Author: Siti A. Ahmad
Author: P.H. Chappell

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×