Comparison of Foot Pedal Reaction Time Among Patients with Right or Left Hemiplegia and Able-Bodied Controls
Bibliographic record
Abstract
BACKGROUND: Although inpatient stroke rehabilitation provides clinicians with the opportunity to prepare patients for continuation of prestroke activities, little is known about the patients' ability to safely resume driving at the point of discharge to the community. OBJECTIVE: To compare foot pedal response times of 20 stroke patients with right hemiplegia (RH) or left hemiplegia (LH) and 10 controls. METHODS: A cross-sectional design was used. Response times were measured using 3 foot pedal operation techniques: (1) right-sided accelerator with right leg operating accelerator and brake, (2) right-sided accelerator with left leg operating accelerator and brake, and (3) left-sided accelerator with left leg operating accelerator and brake. Outcomes included reaction time (RT), movement time (MT), and total response time (TRT). RESULTS: Controls demonstrated faster RT than patients with RH (263 vs 348 ms; P < .001) or LH (316 ms; P < .05) for all conditions, as well as faster MT than patients with RH (P < .05 for all) but not LH when using the right leg (258 vs 251 ms; P = .82). Controls demonstrated faster TRT than patients with RH (P < .001 for all) but not LH when using the right leg (515 vs 553 ms; P = .44). CONCLUSIONS: When using the nonparetic leg, patients with LH had braking response times comparable to controls, but patients with RH demonstrated significant impairment of both the paretic and nonparetic legs.
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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 | 0.002 |
| 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) | 0.003 | 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".