AR Fitness Dog: Effects of a User-Mimicking Interactive Virtual Pet on User Experience and Social Presence in Physical Exercise
Bibliographic record
Abstract
This paper explores the impact of an augmented reality (AR) virtual dog, designed to mimic user behavior, on the exercise experience in both solo and group settings. Focusing on the virtual pet's role as a companion during physical activity, we conducted a human-subject experiment comparing three conditions: a mimicking virtual dog, a randomly behaving virtual dog, and no virtual dog. Participants exercised either solo or in groups, specifically in pairs, allowing for a detailed analysis of how the behavior and physical presence of the virtual dog influenced users' exercise experience and social connections. The findings demonstrate that the mimicking virtual dog significantly enhanced the exercise experience, especially in solo settings, by fostering a stronger sense of companionship. In group exercises, the virtual dog acted as a social facilitator, improving group cohesion and interaction. This research highlights the potential of behavior-mimicking virtual pets to enhance both individual and group exercise experiences and offers valuable insights for developing AR-based fitness applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".