Virtual Reality-Based Navigation Task to Reveal Obstacle Avoidance Performance in Individuals With Visuospatial Neglect
Why this work is in the frame
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Bibliographic record
Abstract
Persons with post-stroke visuospatial neglect (VSN) often collide with moving obstacles while walking. It is not well understood whether the collisions occur as a result of attentional-perceptual deficits caused by VSN or due to post-stroke locomotor deficits. We assessed individuals with VSN on a seated, joystick-driven obstacle avoidance task, thus eliminating the influence of locomotion. Twelve participants with VSN were tested on obstacle detection and obstacle avoidance tasks in a virtual environment that included three obstacles approaching head-on or 30 (°) contralesionally/ipsilesionally. Our results indicate that in the detection task, the contralesional and head-on obstacles were detected at closer proximities compared to the ipsilesional obstacle. For the avoidance task collisions were observed only for the contralesional and head-on obstacle approaches. For the contralesional obstacle approach, participants initiated their avoidance strategies at smaller distances from the obstacle and maintained smaller minimum distances from the obstacles. The distance at detection showed a negative association with the distance at the onset of avoidance strategy for all three obstacle approaches. We conclusion the observation of collisions with contralesional and head-on obstacles, in the absence of locomotor burden, provides evidence that attentional-perceptual deficits due to VSN, independent of post-stroke locomotor deficits, alter obstacle avoidance abilities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it