Use of the wii balance board to assess changes in postural balance across athletic season
Bibliographic record
Abstract
Objective The purpose of this study was to investigate potential utility of a customised Wii Balance Board (WBB) program to assess postural balance in an athletic population. Researchers hypothesised that WBB measures would be strongly correlated to the Balance Error Scoring System (BESS) used in concussion assessments. Design Cross-sectional time series. Static and dynamic balance was assessed using the WBB and BESS at three time points of an athletic season: 1) pre-season, 2) mid-season, and 3) post-season. Setting University research laboratory Subjects Intervention Outcome measures 1) BESS, 2) WBB dynamic recovery time, and 3) WBB static Centre of Pressure (COP). Results WBB COP data were found to be strongly correlated with BESS scores across all time points [pre-season (r=0.689, p<0.05), mid-season (r=0.767, p<0.01), and post-season (r=0.780, p<0.01)]. There were significant differences in recovery time (p<0.005) and COPx variance for the single-leg BESS condition across all time points (p<0.005). No significant differences were observed in raw BESS scores across time points. Conclusions Study results support the use of a WBB as an objective tool in measuring variance in static and dynamic postural balance. This program has potential utility for clinicians when assessing balance deficits related to concussion. Planned work will examine the use of the WBB program in measuring variance in postural balance in individuals with sport-related concussion. Competing interests None.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".