The classification for 'equilibrium triad' sensory loss based on sEMG signals of calf muscles

Yu, H; Guo, K; Luo, J; Cao, K; Nguyen, HT; Su, SW

The classification for 'equilibrium triad' sensory loss based on sEMG signals of calf muscles

Yu, H

Guo, K Luo, J Cao, K

Nguyen, HT

Su, SW

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2017, pp. 2142 - 2145
Issue Date:: 2017-09-13

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Field	Value	Language
dc.contributor.author	Yu, H https://orcid.org/0000-0003-3018-064X	en_US
dc.contributor.author	Guo, K	en_US
dc.contributor.author	Luo, J	en_US
dc.contributor.author	Cao, K https://orcid.org/0000-0002-4473-2065	en_US
dc.contributor.author	Nguyen, HT https://orcid.org/0000-0003-3373-8178	en_US
dc.contributor.author	Su, SW https://orcid.org/0000-0002-5720-8852	en_US
dc.date.issued	2017-09-13	en_US
dc.identifier.citation	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2017, pp. 2142 - 2145	en_US
dc.identifier.isbn	9781509028092	en_US
dc.identifier.issn	1557-170X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/125687
dc.description.abstract	© 2017 IEEE. Surface Electromyography (sEMG) has been commonly applied for analysing the electrical activities of skeletal muscles. The sensory system of maintaining posture balance includes vision, proprioception and vestibular senses. In this work, an attempt is made to classify whether the body is missing one of the sense during balance control by using sEMG signals. A trial of combination with different features and muscles is also developed. The results demonstrate that the classification accuracy between vision loss and the normal condition is higher than the one between vestibular sense loss and normal condition. When using different features and muscles, the impact on classification results is also different. The outcomes of this study could aid the development of sEMG based classification for the function of sensory systems during human balance movement.	en_US
dc.relation.ispartof	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS	en_US
dc.relation.isbasedon	10.1109/EMBC.2017.8037278	en_US
dc.relation.isreplacedby	10453/128063
dc.relation.isreplacedby	http://hdl.handle.net/10453/128063
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	The classification for 'equilibrium triad' sensory loss based on sEMG signals of calf muscles	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0903 Biomedical Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	closed_access	*
pubs.declined	2018-06-25T09:52:15.32+1000
pubs.merge-to	10453/128063
pubs.merge-to	http://hdl.handle.net/10453/128063
pubs.deleted	2018-06-25T09:52:15.32+1000
pubs.publication-status	Published	en_US

Abstract:

© 2017 IEEE. Surface Electromyography (sEMG) has been commonly applied for analysing the electrical activities of skeletal muscles. The sensory system of maintaining posture balance includes vision, proprioception and vestibular senses. In this work, an attempt is made to classify whether the body is missing one of the sense during balance control by using sEMG signals. A trial of combination with different features and muscles is also developed. The results demonstrate that the classification accuracy between vision loss and the normal condition is higher than the one between vestibular sense loss and normal condition. When using different features and muscles, the impact on classification results is also different. The outcomes of this study could aid the development of sEMG based classification for the function of sensory systems during human balance movement.

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http://hdl.handle.net/10453/125687