The influence of a concurrent cognitive task on lower limb reaction time among stroke survivors with right- or left-hemiplegia
Bibliographic record
Abstract
OBJECTIVE: To determine the impact of cognitive interference on foot pedal reaction time among stroke survivors with right- (RH) or left-hemiplegia (LH). DESIGN: Cross-sectional comparison without randomization. SUBJECTS/PATIENTS: 10 patients post-stroke with RH, 10 with LH; 10 age-matched controls. METHODS: Foot pedal response times were measured using three different reaction time (RT) paradigms: simple RT, dual-task RT (counting backward by serial 3 seconds), and choice RT (correct response contingent on stimuli to eliminate pre-programing). RH and LH used the non-paretic leg for all trials. Three 3 (RT task) × 3 (group) mixed-model factorial ANOVAs were used to compare RT, movement time (MT), total response time (TRT). RESULTS: Overall controls demonstrated faster RT than RH (332 ± 73 versus 474 ± 144 ms, P < 0.001) or LH (402 ± 127 ms, P < 0.05); LH group demonstrated faster RT than those with RH (P < 0.05). Control subjects demonstrated significantly faster RT than RH for all RT conditions (P < 0.05 for all). In contrast, controls achieved significantly faster RT than LH for the choice RT condition only (P < 0.05), but not for the simple (P = 0.12) or dual-task RT conditions (P = 0.25). CONCLUSIONS: Compared to controls, response time was significantly impaired among LH and RH when the response could not be pre-programmed. While current simple RT testing commonly employed by driver rehab specialists may be sufficient for detecting RT deficits in patients with RH, simple or dual-task RT tests alone may fail to detect RT deficiencies among LH, even when testing the non-paretic limb. Choice RT should be added to post-stroke driver fitness assessment, particularly for patients with LH.
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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 | 0.000 | 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) | 0.001 | 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".