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dc.contributor.authorTierney, Gregory
dc.contributor.authorJoodaki, Hamed
dc.contributor.authorKrosshaug, Tron
dc.contributor.authorForman, Jason L.
dc.contributor.authorCrandall, Jeff R.
dc.contributor.authorSimms, Ciaran
dc.date.accessioned2018-09-13T11:30:20Z
dc.date.available2018-09-13T11:30:20Z
dc.date.created2017-11-06T13:08:19Z
dc.date.issued2018
dc.identifier.citationSports Biomechanics. 2018, 17, 33-47.nb_NO
dc.identifier.issn1476-3141
dc.identifier.urihttp://hdl.handle.net/11250/2562500
dc.descriptionBrage finner du siste tekst-versjon av artikkelen, og den kan inneholde ubetydelige forskjeller fra forlagets pdf-versjon. Forlagets pdf-versjon finner du på tandfonline.com / In Brage you'll find the final text version of the article, and it may contain insignificant differences from the journal's pdf version. The definitive version is available at tandfonline.comnb_NO
dc.description.abstractPlayer-to-player contact inherent in many unhelmeted sports means that head impacts are a frequent occurrence. Model-Based Image-Matching (MBIM) provides a technique for the assessment of three-dimensional linear and rotational motion patterns from multiple camera views of a head impact event, but the accuracy is unknown for this application. The goal of this study is to assess the accuracy of the MBIM method relative to reflective marker-based motion analysis data for estimating six degree of freedom head displacements and velocities in a staged pedestrian impact scenario at 40 km/h. Results showed RMS error was under 20 mm for all linear head displacements and 0.01–0.04 rad for head rotations. For velocities, the MBIM method yielded RMS errors between 0.42 and 1.29 m/s for head linear velocities and 3.53–5.38 rad/s for angular velocities. This method is thus beneficial as a tool to directly measure six degree of freedom head positional data from video of sporting head impacts, but velocity data is less reliable. MBIM data, combined in future with velocity/acceleration data from wearable sensors could be used to provide input conditions and evaluate the outputs of multibody and finite element head models for brain injury assessment of sporting head impacts.nb_NO
dc.language.isoengnb_NO
dc.subjectconcussionnb_NO
dc.subjectrugbynb_NO
dc.subjectimagenb_NO
dc.subjectprocessingnb_NO
dc.titleAssessment of model-based image-matching for future reconstruction of unhelmeted sport head impact kinematicsnb_NO
dc.title.alternativeAssessment of model-based image-matching for future reconstruction of unhelmeted sport head impact kinematicsnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber33-47nb_NO
dc.source.volume17nb_NO
dc.source.journalSports Biomechanicsnb_NO
dc.source.issue1nb_NO
dc.identifier.doi10.1080/14763141.2016.1271905
dc.identifier.cristin1511303
dc.description.localcodeSeksjon for idrettsmedisinske fag / Department of Sport Medicinenb_NO
cristin.unitcode150,34,0,0
cristin.unitnameSeksjon for idrettsmedisinske fag
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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