Virtual-Gym<sup>VR</sup>: A Virtual Reality Platform for Personalized Exergames
Bibliographic record
Abstract
Virtual-Gym <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">VR</sup> is a platform for serious exergames in virtual reality. Its purpose is to provide older adults with a fun experience, while, at the same time, encouraging them to complete their personalized exercise sessions. The platform takes as input a description of a prescribed exercise, in terms of a posture-transition grammar, and constructs personalized versions of its games by accordingly configuring the behavior of the interactive objects in these games. The game-configuration process essentially controls the placement and the interaction behavior of the games' objects so that they induce the user to adopt the proper postures, as described by the input exercise specification. At run time, the sequence of game events stimulate the user to move to the prescribed exercise postures and, thus, accomplish their own personalized exercise goals. Given the intended user population of older adults, we have designed three different Virtual-Gym <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">VR</sup> games with metaphors appropriate for three different types of exercises. Our initial experimentation with the Virtual-Gym <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">VR</sup> games indicates that the approach is promising.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".