Does It Really Matter Where You Look When Walking on Stairs? Insights from a Dual-Task Study
Bibliographic record
Abstract
Although the visual system is known to provide relevant information to guide stair locomotion, there is less understanding of the specific contributions of foveal and peripheral visual field information. The present study investigated the specific role of foveal vision during stair locomotion and ground-stairs transitions by using a dual-task paradigm to influence the ability to rely on foveal vision. Fifteen healthy adults (26.9 ± 3.3 years; 8 females) ascended a 7-step staircase under four conditions: no secondary tasks (CONTROL); gaze fixation on a fixed target located at the end of the pathway (TARGET); visual reaction time task (VRT); and auditory reaction time task (ART). Gaze fixations towards stair features were significantly reduced in TARGET and VRT compared to CONTROL and ART. Despite the reduced fixations, participants were able to successfully ascend stairs and rarely used the handrail. Step time was increased during VRT compared to CONTROL in most stair steps. Navigating on the transition steps did not require more gaze fixations than the middle steps. However, reaction time tended to increase during locomotion on transitions suggesting additional executive demands during this phase. These findings suggest that foveal vision may not be an essential source of visual information regarding stair features to guide stair walking, despite the unique control challenges at transition phases as highlighted by phase-specific challenges in dual-tasking. Instead, the tendency to look at the steps in usual conditions likely provides a stable reference frame for extraction of visual information regarding step features from the entire visual field.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".