An Interactive Physical-Cognitive Game-Based Training System Using Kinect for Older Adults: Development and Usability Study
Bibliographic record
Abstract
BACKGROUND: Declines in physical and cognitive functions are recognized as important risk factors for falls in older adults. Promising evidence suggests that interactive game-based systems that allow simultaneous physical and cognitive exercise are a potential approach to enhance exercise adherence and reduce fall risk in older adults. However, a limited number of studies have reported the development of a combined physical-cognitive game-based training system for fall risk reduction in older adults. OBJECTIVE: The aim of this study is to develop and evaluate the usability of an interactive physical-cognitive game-based training system (game-based exercise) for older adults. METHODS: In the development phase (Part I), a game-based exercise prototype was created by integrating knowledge and a literature review as well as brainstorming with experts on effective fall prevention exercise for older adults. The output was a game-based exercise prototype that covers crucial physical and cognitive components related to falls. In the usability testing (Part II), 5 games (ie, Fruits Hunter, Where Am I?, Whack a Mole, Sky Falls, and Crossing Poison River) with three difficulty levels (ie, beginner, intermediate, and advanced levels) were tested in 5 older adults (mean age 70.40 years, SD 5.41 years). After completing the games, participants rated their enjoyment level while engaging with the games using the Physical Activity Enjoyment Scale (PACES) and commented on the games. Descriptive statistics were used to describe the participants' characteristics and PACES scores. RESULTS: The results showed that the average PACES score was 123 out of 126 points overall and between 6.66 and 7.00 for each item, indicating a high level of enjoyment. Positive feedback, such as praise for the well-designed interactions and user-friendly interfaces, was also provided. CONCLUSIONS: These findings suggest that it is promising to implement an interactive, physical-cognitive game-based exercise in older adults. The effectiveness of a game-based exercise program for fall risk reduction has yet to be determined.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".