Surface EMG classification using moving approximate entropy
Ahmad, S.A. and Chappell, P.H. (2008) Surface EMG classification using moving approximate entropy. 2007 International Conference on Intelligent and Advanced Systems, 1163-7.
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Description/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.
| Item Type: | Article |
|---|---|
| Additional Information: | Imported from ISI Web of Science |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > EEE |
| Item ID: | 269719 |
| Date Deposited: | 21 Apr 2010 07:46 |
| Last Modified: | 02 Mar 2012 14:05 |
| Contributors: | Ahmad, S.A. (Author) Chappell, P.H. (Author) |
| Date: | 2008 |
| Additional Information: | Imported from ISI Web of Science |
| Status: | Unpublished |
| Further Information: | Google Scholar |
| URI: | http://eprints.soton.ac.uk/id/eprint/269719 |
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