Development and Evaluation of a Monocular Camera–Based Mobile Exergame for at-Home Intervention in Individuals at High Risk of Type 2 Diabetes: Randomized Controlled Trial
Bibliographic record
Abstract
Background: Exergames have emerged as effective interventions for promoting physical activity and preventing type 2 diabetes (T2D). Kinect-based exergames have demonstrated improvements in exercise adherence and health outcomes, but their high cost and reliance on specialized hardware hinder widespread home-based adoption. Recent advances in computer vision now enable monocular camera-based systems, offering a potentially cost-effective and scalable alternative for promoting physical activity at home. Objective: This study aimed to evaluate the feasibility and user experience of monocular camera-based exergames as a home-based intervention for individuals at risk for T2D. Methods: Forty-five community-dwelling individuals at high risk for T2D (mean age 47.12, SD 6.92 years) were recruited and randomized into three groups (n=15 each): (1) control group (traditional offline exercise), (2) Kinect group (Kinect-based exergame), and (3) monocular group (monocular camera-based exergame). Participants engaged in a 10-minute intervention once per week for 7 weeks. Data were collected at 3 time points: baseline (exercise performance: heart rate and perceived fatigue), postintervention (exercise performance and user experience, including game experience and intrinsic motivation), and follow-up (user engagement and qualitative feedback). One-way ANOVA was used for data analysis. Results: Exercise performance was comparable across all groups, with no significant differences in heart rate (P=.76) or fatigue levels (P=.25). However, participants in the monocular group reported significantly lower fatigue than those in the control group (P=.04). Intrinsic motivation was significantly higher in both the Kinect (mean 35.13, SD 3.20) and monocular (mean 34.00, SD 4.41) groups than in the control group (mean 26.06, SD 1.87; P<.001), with no significant difference between the 2 exergame groups (P=.44). While most user experience measures showed no significant differences, the monocular group reported a higher perceived challenge (mean 3.45, SD 0.51) than the Kinect group (mean 2.96, SD 0.39; P=.09). Additionally, the monocular group exhibited higher engagement, as evidenced by more frequent use, fewer challenges, and a greater intention to continue using the system. Conclusions: Monocular camera-based exergame is a feasible and effective solution for promoting physical activity in individuals at risk for T2D. It offers motivational and experiential benefits similar to Kinect-based systems but requires less costly and more accessible equipment. These findings suggest that monocular systems have strong potential as scalable tools for home-based chronic disease prevention.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".