Stroke Affects Locomotor Steering Responses to Changing Optic Flow Directions
Bibliographic record
Abstract
BACKGROUND: Stroke patients manifest steering difficulties during walking, which may arise from an altered perception of visual motion. OBJECTIVE: To examine the ability of stroke patients to control their heading direction while walking in a virtual environment (VE) describing translational optic flows (OFs) expanding from different directions. METHODS: The authors evaluated 10 stroke patients and 11 healthy people while they were walking overground and visualizing a VE in a helmet-mounted display. Participants were instructed to walk straight in the VE and were randomly exposed to an OF having a focus of expansion (FOE) located in 5 possible locations (0 degrees, +/-20 degrees, and +/-40 degrees to the right or left). The body's center of mass (CoM) trajectory, heading direction, and horizontal body reorientation were recorded with a Vicon-512 system. RESULTS: Healthy participants veered opposite to the FOE location in the physical world, with larger deviations occurring at the most eccentric FOE locations. Stroke patients displayed altered steering behaviors characterized either by an absence of CoM trajectory corrections, multiple errors in the heading direction, or systematic veering to the nonparetic side. Both groups displayed relatively small CoM trajectory corrections that led to large virtual heading errors. CONCLUSIONS: The control of heading of locomotion in response to different OF directions is affected by stroke. An altered perception of heading direction and/or a poor integration of sensory and motor information are likely causes. This altered response to OF direction while walking may contribute to steering difficulties after stroke.
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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) | 0.002 | 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".