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Conference Paper: Motor programs: an artificial neural network approach

TitleMotor programs: an artificial neural network approach
Authors
KeywordsMotor program
Artificial neural network
multilayer perceptron
Backpropagation rule
Issue Date1998
PublisherIEEE.
Citation
Proceedings of the 20th IEEE Engineering in Medicine and Biology Society Conference, Hong Kong, China, 29 October-1 November 1998, v. 20 n. 3, p. 1434-1437 How to Cite?
AbstractIt is commonly assumed that, during learning, the brain creates “motor programs” which store all the information essential to performing a motor skill. Yet there is still no consensus on what constitutes a motor program. In this study, a Multilayer Perceptron (MLP) network with one hidden layer, trained using the backpropagation rule, was used in an attempt to identify motor programs. Nine healthy subjects were asked to use their left hand to make fast and accurate movements in a tracking task of 75 identical steps, by either wrist flexion and extension, or the precision grip. The electromyogram (EMG) activity of 8 finger and hand muscles were simultaneously recorded by standard techniques. Onset timing of muscle activities were quantified from the digitized EMG signals, and were then used as the inputs to the MLP network. Reaction time was also measured, providing the desired output of the network. The trained network captured salient features of the relationship between EMG onset times and reaction time.
Persistent Identifierhttp://hdl.handle.net/10722/46976
ISSN

 

DC FieldValueLanguage
dc.contributor.authorHau, WKTen_HK
dc.contributor.authorBruce, ICen_HK
dc.contributor.authorSiu, LYLen_HK
dc.contributor.authorChen, EYHen_HK
dc.date.accessioned2007-10-30T07:02:58Z-
dc.date.available2007-10-30T07:02:58Z-
dc.date.issued1998en_HK
dc.identifier.citationProceedings of the 20th IEEE Engineering in Medicine and Biology Society Conference, Hong Kong, China, 29 October-1 November 1998, v. 20 n. 3, p. 1434-1437en_HK
dc.identifier.issn1557-170Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/46976-
dc.description.abstractIt is commonly assumed that, during learning, the brain creates “motor programs” which store all the information essential to performing a motor skill. Yet there is still no consensus on what constitutes a motor program. In this study, a Multilayer Perceptron (MLP) network with one hidden layer, trained using the backpropagation rule, was used in an attempt to identify motor programs. Nine healthy subjects were asked to use their left hand to make fast and accurate movements in a tracking task of 75 identical steps, by either wrist flexion and extension, or the precision grip. The electromyogram (EMG) activity of 8 finger and hand muscles were simultaneously recorded by standard techniques. Onset timing of muscle activities were quantified from the digitized EMG signals, and were then used as the inputs to the MLP network. Reaction time was also measured, providing the desired output of the network. The trained network captured salient features of the relationship between EMG onset times and reaction time.en_HK
dc.format.extent328366 bytes-
dc.format.extent3474 bytes-
dc.format.extent3292 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofProceedings of the 20th IEEE Engineering in Medicine and Biology Society Conference-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©1998 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.subjectMotor programen_HK
dc.subjectArtificial neural networken_HK
dc.subjectmultilayer perceptronen_HK
dc.subjectBackpropagation ruleen_HK
dc.titleMotor programs: an artificial neural network approachen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1557-170X&volume=20&issue=3&spage=1434&epage=1437&date=1998&atitle=Motor+programs:+an+artificial+neural+network+approachen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/IEMBS.1998.747153en_HK
dc.identifier.hkuros44356-

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