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dc.contributor.authorVan Wallendael, Glenn
dc.contributor.authorArtois, Julie
dc.contributor.authorMareen, Hannes
dc.contributor.authorCapelleman, Robbe
dc.contributor.authorSchuermans, Joke
dc.contributor.authorWezenbeek, Evi
dc.contributor.authorLambert, Peter
dc.date.accessioned2025-04-22T08:58:59Z
dc.date.available2024-09-07T18:21:12Z
dc.date.available2024-09-09T09:30:17Z
dc.date.available2025-04-22T08:58:59Z
dc.date.issued2024
dc.identifier.isbn979-8-3503-7454-4
dc.identifier.issn2831-5510
dc.identifier.otherWOS:001281983200042
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/44409.3
dc.sourceWOS
dc.titleExtended Reality & Virtual Reality for Return-to-Sports Screening
dc.typeProceedings paper
dc.contributor.imecauthorVan Wallendael, Glenn
dc.contributor.imecauthorArtois, Julie
dc.contributor.imecauthorMareen, Hannes
dc.contributor.imecauthorLambert, Peter
dc.contributor.orcidimecVan Wallendael, Glenn::0000-0001-9530-3466
dc.contributor.orcidimecArtois, Julie::0000-0003-2822-5183
dc.contributor.orcidimecMareen, Hannes::0000-0002-0660-3190
dc.contributor.orcidimecLambert, Peter::0000-0001-5313-4158
dc.date.embargo2024-12-31
dc.identifier.doi10.1109/GEM61861.2024.10585487
dc.identifier.eisbn979-8-3503-7453-7
dc.source.numberofpages6
dc.source.peerreviewyes
dc.source.beginpage650
dc.source.endpage655
dc.source.conferenceGaming, Entertainment and Media Conference (GEM)
dc.source.conferencedateJUN 05-07, 2024
dc.source.conferencelocationTurin
dc.source.journalN/A
imec.availabilityPublished - open access
dc.description.wosFundingTextThis research was supported by the Research Foundation -Flanders (FWO), IDLab (Ghent University -imec), Flanders Innovation and Entrepreneurship (VLAIO), and the European Union. Moreover, the computational resources (STEVIN Supercomputer Infrastructure) and services used were kindly provided by Ghent University, the Flemish Supercomputer Center (VSC), the Hercules Foundation and the Flemish Government department EWI. The authors would like to thanks the following master thesis students who contributed extensively to the software, clinical trials, and analysis of the results: Cornelis To, Dhibi Jasim, Dhondt Lisa, Maelfait Andrea, Naudts Michiel, Van den Bossche Margo, Van Gendt Marjolein, and Van Hootegem Alena.


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