ExerCube vs. Virtual Reality: A Comparative Study of Exergame Technologies for Older Adults
Bibliographic record
Abstract
Insufficient physical activity is a major challenge in our aging society. Although exergames can provide enjoyable exercise opportunities for older adults, it remains unclear which display technology is best suited to reach this goal. This paper compares two popular exergame technologies with different immersion levels: (i) a virtual reality head-mounted display (VR-HMD) and (ii) the ExerCube, a commercial projection-based system. We conducted a within-participants study ( N =34) with older adults to evaluate player experience, presence, cybersickness, game performance, and physical exertion. Both display types provided a comparably high player experience and physical exertion that can benefit older adults’ physical well-being. The VR-HMD offered superior presence, while the ExerCube led to higher performance and physical activity. Our findings advance the understanding of how different exergame technologies affect older adults’ experiences. We present research and design implications to guide the future development of age-appropriate exergames.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".