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dc.contributor.authorKiziltas, D.en_US
dc.contributor.authorCelikcan, U.en_US
dc.contributor.editorLivesu, Marco and Pintore, Gianni and Signoroni, Albertoen_US
dc.date.accessioned2018-10-18T05:51:14Z
dc.date.available2018-10-18T05:51:14Z
dc.date.issued2018
dc.identifier.isbn978-3-03868-075-8
dc.identifier.issn2617-4855
dc.identifier.urihttps://doi.org/10.2312/stag.20181298
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/stag20181298
dc.description.abstractIn this work, we present the design and the implementation of Knee Up, an exergame that promotes knee health via standing knee raises exercises. It allows users to exercise at home and perform the exercise in a gaming environment. By motion capture using RGB-D data, estimated positions of the user's skeletal joints are acquired and processed in real-time. For the game, 3D virtual environments have been created with gamification elements so that users can enjoy more interactive and engaging exercise sessions. The game facilitates to evaluate the quality of performed standing knee raises exercise through a rule-based recognition algorithm and, in return, to provide timely feedback. A formal user study was conducted in order to assess the usability and gamification aspects of Knee Up. Study results demonstrate that Knee Up is generally well-received in terms of usability, engagement, ease of learning-to-play, and exercise sustainability; and validate that the rule-based recognition algorithm works satisfactorily well.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectExergame
dc.subjectKnee Exercise
dc.subjectMotion Analysis
dc.subjectRGB
dc.subjectD
dc.subjectKinect
dc.titleKnee Up: an Exercise Game for Standing Knee Raises by Motion Capture with RGB-D Sensoren_US
dc.description.seriesinformationSmart Tools and Apps for Graphics - Eurographics Italian Chapter Conference
dc.description.sectionheadersInteraction Between Humans and Systems
dc.identifier.doi10.2312/stag.20181298
dc.identifier.pages57-64


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