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dc.contributor.authorRide, Jason
dc.contributor.authorJames, Daniel
dc.contributor.authorLee, James
dc.contributor.authorRowlands, David
dc.contributor.editorPatrick Drane and James Sherwood
dc.date.accessioned2017-09-14T23:11:16Z
dc.date.available2017-09-14T23:11:16Z
dc.date.issued2012
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 paper details a developed system that uses a distributed server-client architecture to collect and store large sets of athlete data as well as providing mechanisms for later analysis and visualisation for feedback. The server utilises MATLAB with the Athlete Data Processing Toolbox. A local SQL server handles data storage and PHP with AJAX/JSON is used to communicate with clients. Clients use a web browser interface to communicate with the server and provide relevant analysis and visualisation tools to the end user.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
dcterms.licensehttp://creativecommons.org/licenses/by-nc-nd/3.0/en_US
dc.description.versionPublisheden_US
gro.facultyGriffith Sciences, Griffith School of Engineeringen_US
gro.rights.copyrightCopyright 2012 The Authors. Published by Elsevier Ltd. Open access under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) License which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited. You may not alter, transform, or build upon this work.en_US
gro.date.issued2012
gro.hasfulltextFull Text


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