The Impact of Cognitive Impairment on Pedal Control and Crash Risk Following Stroke: A Pilot Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Driving after stroke requires complex coordination of cognitive and motor systems, yet the influence of post-stroke cognitive impairment on lower limb motor control during driving remains poorly understood. This pilot study examined the association between cognitive function and lower limb motor control of gas/brake pedal control in stroke survivors. We hypothesized that compromised cognitive function would be associated with worse gas and brake pedal control. Twenty stroke survivors (65.89 ± 9.67 years; 6 females) participated. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and Useful Field of View (UFOV) test scores for divided and selective attention. Participants performed a car-following task in a driving simulator requiring precise gas and brake control. Pedal control was quantified by gas pedal error, brake force error, and brake response time. Participants were categorized into cognitively normal and cognitively impaired groups (n=10 each). Driving behavior was assessed using the Driving Habits Questionnaire (DHQ), and crash risk was determined via UFOV classification. Increased gas pedal error was associated with poorer MoCA scores and selective attention deficits. Delayed brake response times correlated with lower MoCA scores and poorer divided and selective attention. Although self-reported driving behavior was comparable between groups, 60% of cognitively impaired participants demonstrated moderate to high crash risk compared to cognitively normal participants, who exhibited low crash risk. Cognitive impairment after stroke is significantly linked to impaired lower limb control during driving and elevated crash risk. These findings highlight an urgent need to integrate cognitive assessment along with motor assessments in post-stroke rehabilitation. Future advances in neuroengineering technologies, and personalized motor-cognitive interventions could play a critical role in restoring safe driving capabilities and mobility independence after stroke.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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