Visual Biofeedback and Postural Control: Exploring Potential Implicit Visual Integration
Bibliographic record
Abstract
Real-time visual biofeedback (vBF) of body sway is known to enhance postural control by reducing center of pressure (COP) displacement. However, the mechanisms underlying its influence remain unclear, particularly regarding implicit processing. The objective of this study was to examine whether vBF is utilized implicitly by exposing 40 young adults to both real-time (accurate) and erroneous (delayed) COP feedback without explicitly explaining its purpose. Participants were simply instructed to stand as still as possible. After the experiment, 15 out of 40 participants spontaneously recognized the feedback's nature. Results indicated that both aware and unaware participants exhibited improved postural control under accurate vBF (i.e., reduced COP variability, smaller COP area, increased COP irregularity, and greater reliance on higher sway frequencies). In contrast, erroneous vBF induced minimal changes. While these findings highlight a possible implicit integration of the visual feedback, the results also underscore the need for future research to investigate this phenomenon with more refined methods, as classifying participants into aware and unaware groups presents certain challenges.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".