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Conference Paper: The use of artificial neural networks in the motor program

TitleThe use of artificial neural networks in the motor program
Authors
KeywordsElectromyography (EMG)
motor program
artificial neural networks (ANNs)
Issue Date2004
PublisherIEEE.
Citation
The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Proceedings, San Francisco, CA, USA, 1-5 September 2004, v. 2, p. 4611-4613 How to Cite?
AbstractThough it is commonly assumed that the brain creates 'motor programs' which store the information essential to perform a motor skill, little direct evidence exists for such motor programs. Electromyography (EMG) provides a look into the motoneurons - level of a movement by measuring the electrical activity in relation to the muscle's involvement in the movement In this paper, artificial neural networks (ANNs) were applied to define the temporal patterns of EMG activity used by normal subjects in performing step-tracking tasks, and how such patterns change with practice. Our results demonstrate that ANNs could be trained to detect the input-output relationship between muscles' onset times and reaction times, and provided evidence to support the existence of a motor program.
Persistent Identifierhttp://hdl.handle.net/10722/46973
ISSN

 

DC FieldValueLanguage
dc.contributor.authorWu, Pen_HK
dc.contributor.authorBao, Jen_HK
dc.contributor.authorXia, Qen_HK
dc.contributor.authorBruce, ICen_HK
dc.date.accessioned2007-10-30T07:02:49Z-
dc.date.available2007-10-30T07:02:49Z-
dc.date.issued2004en_HK
dc.identifier.citationThe 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Proceedings, San Francisco, CA, USA, 1-5 September 2004, v. 2, p. 4611-4613en_HK
dc.identifier.issn1557-170Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/46973-
dc.description.abstractThough it is commonly assumed that the brain creates 'motor programs' which store the information essential to perform a motor skill, little direct evidence exists for such motor programs. Electromyography (EMG) provides a look into the motoneurons - level of a movement by measuring the electrical activity in relation to the muscle's involvement in the movement In this paper, artificial neural networks (ANNs) were applied to define the temporal patterns of EMG activity used by normal subjects in performing step-tracking tasks, and how such patterns change with practice. Our results demonstrate that ANNs could be trained to detect the input-output relationship between muscles' onset times and reaction times, and provided evidence to support the existence of a motor program.en_HK
dc.format.extent431039 bytes-
dc.format.extent3292 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectElectromyography (EMG)en_HK
dc.subjectmotor programen_HK
dc.subjectartificial neural networks (ANNs)en_HK
dc.titleThe use of artificial neural networks in the motor programen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1557-170X&volume=2&spage=4611&epage=4613&date=2004&atitle=The+use+of+artificial+neural+networks+in+the+motor+programen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/IEMBS.2004.1404278en_HK
dc.identifier.hkuros98274-

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