E193-03 - Forschungsbereich Virtual and Augmented Reality
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Journal:
VISUAL COMPUTER
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ISSN:
0178-2789
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Date (published):
2024
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Number of Pages:
17
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Publisher:
SPRINGER
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Peer reviewed:
Yes
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Keywords:
Body tracking; Exergame; Human-computer interaction; Pose estimation; Preventive rehabilitation; Serious game
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Abstract:
In this paper, we present OffiStretch, a camera-based system for optimal stretching guidance at home or in the workplace. It consists of a vision-based method for real-time assessment of the user’s body pose to provide visual feedback as interactive guidance during stretching exercises. Our method compares the users’ actual pose with a pre-trained target pose to assess the quality of stretching for a number of different exercises. We utilize angular and spatial pose features to perform this comparison for each individual exercise. The result of this pose assessment is presented to the user as real-time visual feedback on an "augmented mirror" display. As our method relies simply on a single RGB camera, it can be easily utilized in everyday training scenarios. We validate our method in a user study, comparing users’ performance and motivation in stretching when receiving audio-visual guidance on a TV screen both with and without our live feedback. While participants performed equally well in both conditions, feedback boosted their motivation to perform the exercises, highlighting its potential for increasing users’ well-being. Moreover, our results suggest that participants preferred stretching exercises with our live feedback over the condition without the feedback. Finally, an expert evaluation with professional physiotherapists reveals that further work must target improvements of the feedback to ensure correct guidance during stretching.
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Research Areas:
Visual Computing and Human-Centered Technology: 100%