Obstacle Avoidance and Dual-Tasking During Reaching While Standing in Patients With Mild Chronic Stroke
Bibliographic record
Abstract
Background. Poststroke individuals use their paretic arms less often than expected in daily life situations, even when motor recovery is scored highly in clinical tests. Real-world environments are often unpredictable and require the ability to multitask and make decisions about rapid and accurate arm movement adjustments. Objective. To identify whether and to what extent cognitive–motor deficits in well-recovered individuals with stroke affect the ability to rapidly adapt reaching movements in changing cognitive and environmental conditions. Methods. Thirteen individuals with mild stroke and 11 healthy controls performed an obstacle avoidance task in a virtual environment while standing. Subjects reached for a virtual juice bottle with their hemiparetic arm as quickly as possible under single- and dual-task conditions. In the single-task condition, a sliding glass door partially obstructed the reaching path of the paretic arm. A successful trial was counted when the subject touched the bottle without the hand colliding with the door. In the dual-task condition, subjects repeated the same task while performing an auditory–verbal working memory task. Results. Individuals with stroke had significantly lower success rates than controls in avoiding the moving door in single-task (stroke: 51.8 ± 21.2%, control: 70.6 ± 12.7%; P = .018) and dual-task conditions (stroke: 40.0 ± 27.6%, control: 65.3 ± 20.0%; P = .015). Endpoint speed was lower in stroke subjects for successful trials in both conditions. Obstacle avoidance deficits were exacerbated by increased cognitive demands in both groups. Individuals reporting greater confidence using their hemiparetic arm had higher success rates. Conclusion. Clinically well-recovered individuals with stroke may have persistent deficits performing a complex reaching task.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".