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Why you walk like that: Inferring Body Conditions from Single Gait Cycle

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dc.contributor.authorMin, Sehee-
dc.contributor.authorLee, Jehee-
dc.date.accessioned2022-09-30T05:49:14Z-
dc.date.available2022-09-30T05:49:14Z-
dc.date.created2022-07-21-
dc.date.issued2021-08-
dc.identifier.citationSIGGRAPH '21: ACM SIGGRAPH 2021 POSTERS-
dc.identifier.urihttps://hdl.handle.net/10371/184806-
dc.description.abstractGait is a key barometer to analyze human body conditions. We propose a personalized gait analysis framework which can diagnose a possible muscularskeletal disorders with a single gait cycle. Our framework built over a gait manifold which reveals the principle kinematic characteristics in the temporal pose sequence. Body parameters such as muscle, skeleton, and joint limits for an arbitrary gait cycle can be approximated by measuring similarity in the small latent space. We present a physical gait simulator to enrich the gait space paired with the body conditions.-
dc.language영어-
dc.publisherASSOC COMPUTING MACHINERY-
dc.titleWhy you walk like that: Inferring Body Conditions from Single Gait Cycle-
dc.typeArticle-
dc.identifier.doi10.1145/3450618.3469162-
dc.citation.journaltitleSIGGRAPH '21: ACM SIGGRAPH 2021 POSTERS-
dc.identifier.wosid000766399200028-
dc.identifier.scopusid2-s2.0-85112706430-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorLee, Jehee-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
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