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Preliminary findings support the feasibility of mobile coaching-based exergames for combined motor and cognitive training and motivate further exploring of presence-enhancing features.
Lifting 3D hand poses from 2D monocular representations remains challenging due to the limited availability of large-scale, diverse 3D-annotated hand datasets, in contrast to the abundance of human body motion data. We address this limitation by transferring motion representations learned from large body pose corpora t...
This study proves that GMH-D is a reliable framework for assessing 3D hand movements in clinical applications and contributes to the advancement of hand tracking technology, and the establishment of a validation procedure as a good-practice to prove efficacy of deep-learning-based hand-tracking.
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