Progressive lenses distortions effect on postural stability in virtual reality environment
Bibliographic record
Abstract
Background. In most cases, presbyopic vision is corrected using progressive lenses. In spite of the geometric advanced of such products, some progressive lens wearers have difficulty adapting to them because of the distortions perceived in the bottom of the lenses. The purpose of the present study was to evaluate the influence of the visual distortions induced by progressive lenses on the postural stability of the wearers. Methods. In order to simulate the visual distortions induced by progressive lens wear, twelve young observers (22 to 35 years of age) were placed in a fully immersive virtual reality environment where the virtual floor, defined by a 10 × 10 m2 black and white checkerboard pattern, oscillated sinusoidally. The amplitude (1 to 4°) and temporal frequency (0.03 to 2.0 Hz) of the oscillation were systematically manipulated (for a total of 21 conditions). Postural reactivity, defined by the amplitude of lateral (side-to-side) sway and the instability index, was measured as a function of virtual checkerboard distortion using magnetic sensors placed at the head and close to the centre of mass of the subjects and transformed using Fourier. Results. Results showed that postural instability increased with the amplitude of stimulation, suggesting a direct relationship between amount of postural movement and visual distortions. Furthermore, subjects gained stability as the temporal frequency of the distortions increased. However, even in the high temporal frequency conditions, postural reactivity depended significantly on the distortions. Our results suggest that the adaptation difficulties to the progressive lenses could be related to the visual distortions induced in the lower visual field. Participants reported feelings of ‘seasickness’ during task execution for high temporal frequency conditions comparable to what some presbyopes feel during initial progressive lens wear.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".