Perception of Self-Motion and Regulation of Walking Speed in Young-Old Adults
Bibliographic record
Abstract
Whether a reduced perception of self-motion contributes to poor walking speed adaptations in older adults is unknown. In this study, speed discrimination thresholds (perceptual task) and walking speed adaptations (walking task) were compared between young (19-27 years) and young-old individuals (63-74 years), and the relationship between the performance on the two tasks was examined. Participants were evaluated while viewing a virtual corridor in a helmet-mounted display. Speed discrimination thresholds were determined using a staircase procedure. Walking speed modulation was assessed on a self-paced treadmill while exposed to different self-motion speeds ranging from 0.25 to 2 times the participants' comfortable speed. For each speed, participants were instructed to match the self-motion speed described by the moving corridor. On the walking task, participants displayed smaller walking speed errors at comfortable walking speeds compared with slower of faster speeds. The young-old adults presented larger speed discrimination thresholds (perceptual experiment) and larger walking speed errors (walking experiment) compared with young adults. Larger walking speed errors were associated with higher discrimination thresholds. The enhanced performance on the walking task at comfortable speed suggests that intersensory calibration processes are influenced by experience, hence optimized for frequently encountered conditions. The altered performance of the young-old adults on the perceptual and walking tasks, as well as the relationship observed between the two tasks, suggest that a poor perception of visual motion information may contribute to the poor walking speed adaptations that arise with aging.
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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 | 0.001 | 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".