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dc.contributor.authorHardaker, Pamelaen
dc.contributor.authorPassow, Benjamin N.en
dc.contributor.authorElizondo, Daviden
dc.date.accessioned2013-11-12T11:17:51Z
dc.date.available2013-11-12T11:17:51Z
dc.date.issued2013-09
dc.identifier.citationHardaker, P., Passow, B. N. and Elizondo, D. (2013) Walking State Detection from Electromyographic Signals towards the Control of Prosthetic Limbs. Proceedings of the 13th Annual Workshop on Computational Intelligence' (UKCI'13), Guildford, United Kingdom, 9-11 September 2013.en
dc.identifier.urihttp://hdl.handle.net/2086/9344
dc.description.abstractThis paper presents experiments in the use of an Electromyographic sensor to determine whether a person is standing, walking or running. The output of the sensor was captured and processed in a variety of different ways to extract those features that were seen to be changing as the movement state of the person changed. Experiments were carried out by adjusting the parameters used for the collection of the features. These extracted features where then passed to a set of Artificial Neural Networks trained to recognise each state. This methodology exhibits an accuracy needed to control a prosthetic leg.en
dc.language.isoenen
dc.publisherProceedings of the 13th Annual Workshop on Computational Intelligence (UKCI'13)en
dc.subjectWalking State Detectionen
dc.subjectElectromyographic Signalsen
dc.subjectProstheticen
dc.subjectNeural Networksen
dc.subjectSignal Processingen
dc.subjectFeature Extractionen
dc.subjectPattern Recognitionen
dc.titleWalking State Detection from Electromyographic Signals towards the Control of Prosthetic Limbsen
dc.typeConferenceen
dc.researchgroupDIGITSen
dc.researchgroupCentre for Computational Intelligence
dc.peerreviewedYesen
dc.funder-en
dc.projectid-en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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