Measurement of Centre of Pressure Using the Wii Balance Board in Older Adults with Simulated Visual Impairment
Bibliographic record
Abstract
Abstract Postural stability is a complex skill dependent upon the coordination of motor, sensory and cognitive systems. The purpose of this project was therefore to explore how older adults’ balance performance is impacted by increased cognitive load, hearing loss, and simulated vision loss. Twenty-eight older adults between the ages of 50 and 93 years (M = 73.86, SD = 10.43) were tested. Participants underwent standard sensory acuity and cognitive functioning tests. The balance trials varied as a function of cognitive load and visual challenge resulting in five conditions: (1) eyes closed, (2) normal vision clear goggles (NV) (3) simulated low vision (20/80) goggles (LV) (4) LV and math task, (5) NV and math task. Postural stability was assessed with three key center of pressure parameters: total path length (TPL), anterior-posterior amplitude (APA) and medial-lateral amplitude (MLA). A mixed-model ANOVA using hearing acuity as a covariate revealed significant effects of complexity in sway amplitude: (APA: p < .017; MLA: p < .020), while TPL approached significance (p < .074). T-tests revealed significant (p < .05) decreases in balance performance across all 3 centre of pressure parameters when comparing single task NV to dual-task NV, NV vs. eyes closed and single task NV vs. LV dual-task. There were significant positive correlations between hearing acuity and balance (MLA) under single task NV (r = .491) and LV conditions (r = .497). Results suggest the attentional demands from increased cognitive load and sensory loss lead to decreases in older adults’ single- and dual-task balance performance.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".