Exergames have demonstrated potential as effective interventions for promoting physical activity and preventing type 2 diabetes (T2D), particularly among older adults. Kinect-based exergames, in particular, have been associated with improved adherence to exercise regimens and positive health outcomes. However, widespread implementation is limited by the high cost and reduced accessibility of the required hardware, restricting their use in home-based settings. Recent advances in computer vision have enabled the development of exergames using monocular camera systems, which may represent a cost-effective and scalable alternative. This study investigates the feasibility of monocular-camera-based exergames as a cost-effective and convenient alternative for home-dwelling individuals. A total of 45 community-dwelling older adults aged 60-74 years, identified as high risk for T2D were recruited through local community health centers. Participants were randomly assigned to one of three groups (n = 15 per group): (1) Control group (traditional offline exercise with printed instructions), (2) Kinect group (Kinect-based exergames targeting aerobic capacity, balance, and strength), and (3) Monocular group (monocular-camera-based exergames using real-time 2D pose estimation). The intervention lasted six weeks, with participants completing three 30-minute sessions per week at home. Primary outcomes included exercise performance (completion rate and movement accuracy) and intrinsic motivation. Secondary outcomes included perceived enjoyment, challenge, and usability. Data were analyzed using one-way ANOVA.
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Heart rate
Timeframe: Baseline, Immediately after the intervention
Perceived fatigue
Timeframe: Baseline, Immediately after the intervention