Association between Anthropometric Variables, Sex, and Visual Biofeedback in Dynamic Postural Control Assessed on a Computerized Wobble Board
Bibliographic record
Abstract
Anthropometrics and sex influence balance performances, and visual information can change anthropometrics’ relation and the postural sway. Therefore, the aim of the present study was to evaluate the effect of anthropometric characteristics, sex, and visual biofeedback and/or their interaction on a computerized wobble board. Twenty-seven (14 females, 13 males) young adults performed three 30-s double leg stance trials on a wobble board during two conditions: with visual and without visual biofeedback. Visual biofeedback improved (p = 0.010) balance on a wobble board with respect to the condition without visual biofeedback. Regardless of sex, no differences between conditions were found (p = 0.088). When investigating the effect of anthropometrics variables, sex, and their interactions on conditions, a significant main effect of the lower limb/height ratio, sex, and their interaction on the condition without visual biofeedback was found (p = 0.0008; R2 = 0.57). For the visual biofeedback condition, significant effects for sex and body mass (p = 0.0012; R2 = 0.43) and sex and whole-body moment of inertia (p = 0.0030; R2 = 0.39) were found. Results from the present study showed (1) visual biofeedback improved wobble board balance performance; (2) a significant main effect of lower limb/height ratio, sex, and their interaction on the wobble board performances without visual biofeedback emerged; (3) significant effects were found for sex and body mass and sex and moment of inertia in the visual biofeedback condition. Findings from the present study could have an impact on training and evaluations protocols, especially when several populations such as children, athletes, older adults and people with balance disorders are involved.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 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".