Normalised Mutual Information of High-Density Surface Electromyography during Muscle Fatigue

Bingham, A, Poosapadi Arjunan, S, Jelfs, B and Kumar, D 2017, 'Normalised Mutual Information of High-Density Surface Electromyography during Muscle Fatigue', Entropy, vol. 19, no. 12, pp. 1-14.


Document type: Journal Article
Collection: Journal Articles

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Title Normalised Mutual Information of High-Density Surface Electromyography during Muscle Fatigue
Author(s) Bingham, A
Poosapadi Arjunan, S
Jelfs, B
Kumar, D
Year 2017
Journal name Entropy
Volume number 19
Issue number 12
Start page 1
End page 14
Total pages 14
Publisher MDPI AG
Abstract This study has developed a technique for identifying the presence of muscle fatigue based on the spatial changes of the normalised mutual information (NMI) between multiple high density surface electromyography (HD-sEMG) channels. Muscle fatigue in the tibialis anterior (TA) during isometric contractions at 40% and 80% maximum voluntary contraction levels was investigated in ten healthy participants (Age range: 21 to 35 years; Mean age = 26 years; Male = 4, Female = 6). HD-sEMG was used to record 64 channels of sEMG using a 16 by 4 electrode array placed over the TA. The NMI of each electrode with every other electrode was calculated to form an NMI distribution for each electrode. The total NMI for each electrode (the summation of the electrode's NMI distribution) highlighted regions of high dependence in the electrode array and was observed to increase as the muscle fatigued. To summarise this increase, a function, M(k), was defined and was found to be significantly affected by fatigue and not by contraction force. The technique discussed in this study has overcome issues regarding electrode placement and was used to investigate how the dependences between sEMG signals within the same muscle change spatially during fatigue.
Subject Biological Mathematics
Biomedical Engineering not elsewhere classified
Keyword(s) High density surface electromyography
Mutual information
Muscle fatigue
DOI - identifier 10.3390/e19120697
Copyright notice © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
ISSN 1099-4300
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