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dc.contributor.authorRide, Jasonen_US
dc.contributor.authorJames, Danielen_US
dc.contributor.authorLee, Jamesen_US
dc.contributor.authorRowlands, Daviden_US
dc.contributor.editorPatrick Drane and James Sherwooden_US
dc.date.accessioned2017-04-24T08:24:05Z
dc.date.available2017-04-24T08:24:05Z
dc.date.issued2012en_US
dc.date.modified2013-06-03T03:57:24Z
dc.identifier.issn1877-7058en_US
dc.identifier.doi10.1016/j.proeng.2012.04.069en_US
dc.identifier.urihttp://hdl.handle.net/10072/47080
dc.description.abstractOver the last decade, inertial sensors have become a valuable tool for extracting quantitative data from athletes. Due to their small size, unobtrusive nature and relative affordability, there is considerable interest in using multi-channel multi-sensor configurations to gain further insight into sporting performance parameters. As the amount of raw information that can be recorded in a single training session increases, so too does the complexity of the data mining algorithms required to emphasise, extract and derive its performance metrics. This ...en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherElsevieren_US
dc.publisher.placeNetherlandsen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom403en_US
dc.relation.ispartofpageto408en_US
dc.relation.ispartofjournalProcedia Engineeringen_US
dc.relation.ispartofvolume34en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchBiomechanical Engineeringen_US
dc.subject.fieldofresearchcode090302en_US
dc.titleA distributed architecture for storing and processing multi channel multi-sensor athlete performance dataen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.facultyGriffith Sciences, Griffith School of Engineeringen_US
gro.date.issued2012
gro.hasfulltextNo Full Text


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