Are Wii Fit And Active?: Reproducibility Of Measured Physical Activity During Different Activities.
Bibliographic record
Abstract
The Nintendo Wii and Wii Fit games are growing in popularity and presumed to increase physical activity. Before determining the impact of the Wii and Wii Fit on physical activity, the reproducibility of how activity is measured during these activities is warranted. PURPOSE: To examine the reproducibility of accelerometer counts and heart rate measurements during Wii based activities, treadmill walking and passive television watching. METHODS: Nine university students aged 18 to 22 years completed five activities which were counterbalanced in each of two separate testing sessions. Wii Boxing, Wii Fit (Strength, Aerobics and Games components), and walking on a treadmill, were considered "active" while watching television, and Wii Mario Galaxy were "sedentary" screen time controls. Each activity was performed consecutively for fifteen minutes. Walking was performed on a treadmill at speeds of 2.5 and 4.0 mph. Two ActiGraph GT1M accelerometers were used to measure physical activity in this study; one attached to the wrist and the other at the hip. The participants' heart rates were recorded every 5 minutes. Paired t-test analyses and correlations were conducted for each activity using SPSS. RESULTS: There were no significant (p<0.05) differences between day 1 and day 2 heart rates or wrist and hip accelerometer counts for the different activities across time. However, heart rate responses and activity counts measured on the wrist and hip differed. CONCLUSIONS: These results demonstrate that measuring physical activity associated with these varied activities including the Wii activities is reproducible from day to day but may require numerous measures to accurately assess intensity and movement associated with each different type of activity. Supported by Acadia University AUFA25.55.
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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 | 0.007 | 0.024 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".