Effects of Age‐Related Macular Degeneration and Ambient Light on Curb Negotiation
Bibliographic record
Abstract
PURPOSE: To determine how age-related macular degeneration (AMD) and changes in ambient light affect the ability to negotiate a curb while walking. METHODS: Ten older adults with AMD and 11 normal-sighted control subjects performed a curb negotiation task under normal light (∼600 lux), dim light (∼0.7 lux), and following a sudden reduction (∼600 to 0.7 lux) of light. In this task, subjects walked and stepped up or down a simulated sidewalk curb. Movement kinematics and ground reaction forces were measured during curb ascent and descent. Habitual visual acuity, contrast sensitivity, and visual fields were also assessed. RESULTS: Apart from slower gait speed in those with AMD, there were no differences between groups during curb ascent for any other measure. During curb descent, older adults with AMD frequently used shuffling steps in the approach phase to locate the curb edge and showed prolonged double support duration stepping over the curb compared with control subjects. However, reduced lighting, particularly a sudden reduction, led to several significant changes in movement characteristics in both groups. For instance, toe clearance stepping up the curb was greater, and landing force stepping down was reduced. In addition, slower gait speed and greater double support duration were evident in curb ascent and descent. In AMD subjects, contrast sensitivity, visual acuity, and visual field threshold were associated with several kinematic measures in the three light conditions during curb negotiation. CONCLUSIONS: Minor AMD-specific changes in movement are seen during curb negotiation. However, attenuated lighting greatly impacts curb ascent and descent, regardless of eye disease, which manifests as a cautious walking strategy and may increase the risk of falling. Environmental enhancements that reduce the deleterious effects of poor lighting are required to improve mobility and quality of life of older adults, particularly those with AMD.
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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 | 0.001 |
| 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".