The Effects of Delayed Visual Feedback on Dynamic Postural Control
Bibliographic record
Abstract
Purpose: Vision provides essential sensory feedback to maintain upright stance yet is affected by inherent processing delays within the central nervous system. Mismatches between visual and motor responses caused by visual delays may also result in motion sickness. In the current study, virtual reality (VR)-generated visual delays were used to examine the relationships among delayed visual feedback, postural responses, and visually induced motion sickness during a dynamic balance task. Methods: Young healthy adults stood on a force plate mounted to a motorized platform that sinusoidally translated continuously in the anteroposterior (AP) direction for 60 seconds; they wore a VR head-mounted display, surface electromyography (EMG), and full-body motion capture markers. Center of pressure (CoP) was recorded through ground reaction forces using the force plate, kinematics were collected to observe whole-body responses, and surface EMG was used to record muscle activity. Questionnaires were completed after each trial to evaluate subjective measures of perceived stability and visually induced motion sickness. Results: The amplitude of kinetic, kinematic responses, and muscle activity increased with visual delay and returned to baseline levels when participants were re-exposed to the visual delay conditions. Conclusions: Strategies used to maintain postural stability under delayed feedback conditions can adapt to sensory delays, without experiencing motion sickness, even if the perceived stability is initially compromised.
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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) | 0.000 | 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 | 0.000 |
| 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".