The effects of aging on action and visual strategies when walking through apertures
Bibliographic record
Abstract
Avoiding collisions with objects is a requirement of everyday locomotion. The actions individuals take to move through a cluttered environment are governed by how passable one perceives the open space to be. Naturally, people want to avoid colliding with objects to reduce the risk of injury. In the current study the participants (N=13) walked along an 8m path at their self-selected speed towards a static door aperture. The aperture varied in width from 40-90cm. The participants were instructed to safely pass through the aperture using a suitable method. The objectives of the study were to determine: (1) if the actions of older adults (i.e. critical point, velocity change onset, & shoulder rotation onset) are different from those previously reported with young adults (Warren & Whang, 1987); (2) if gaze behaviours (i.e. fixation locations and durations) are different from those reported from younger adults (Higuchi et al., 2009)); and (3) if fixation patterns are reflective of action differences. Preliminary results indicate that older adults use different action strategies when approaching and passing through apertures than young adults. Older adults appear to have a larger critical point (i.e. aperture width/shoulder width) than previously reported in younger adults (i.e. 1.5 vs. 1.3). Further analysis will determine whether older adults have similar sequential action changes (i.e. velocity change followed by shoulder rotation initiation) as younger adults (Cinelli & Patla, 2007). Preliminary data analysis has also shown that older adults' fixation patterns were different from younger adults when approaching the aperture. Older adults appear to direct fixations towards the floor and more towards the door edges than younger adults during a similar task. These results suggest that the nature of the older adults' fixation patterns are directly influencing their “cautious” actions when passing through door apertures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".