Use of the Nintendo Wii Balance Board for Studying Standing Static Balance Control: Technical Considerations, Force-Plate Congruency, and the Effect of Battery Life
Bibliographic record
Abstract
The Nintendo Wii Balance Board (WBB) has become popular as a low-cost alternative to research-grade force plates. The purposes of this study were to characterize a series of technical specifications for the WBB, to compare balance control metrics derived from time-varying center of pressure (COP) signals collected simultaneously from a WBB and a research-grade force plate, and to investigate the effects of battery life. Drift, linearity, hysteresis, mass accuracy, uniformity of response, and COP accuracy were assessed from a WBB. In addition, 6 participants completed an eyes-closed quiet standing task on the WBB (at 3 battery life levels) mounted on a force plate while sway was simultaneously measured by both systems. Characterization results were all associated with less than 1% error. R2 values reflecting WBB sensor linearity were > .99. Known and measured COP differences were lowest at the center of the WBB and greatest at the corners. Between-device differences in quiet stance COP summary metrics were of limited clinical significance. Lastly, battery life did not affect WBB COP accuracy, but did influence 2 of 8 quiet stance WBB parameters. This study provides general support for the WBB as a low-cost alternative to research-grade force plates for quantifying COP movement during standing.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".