Perceptuo-motor planning during functional reaching after stroke
Bibliographic record
Abstract
In healthy young adults, reaching movements are planned such that the initial grasp position on the object is modulated based on the final task goal. This perceptuo-motor coupling has been described as the end-state comfort effect. This study aimed to determine the extent to which visuo-perceptual and motor deficits, but not neglect, due to stroke impact end-state comfort measured as the grasp-height effect. Thirty-four older adults (17 controls, 17 chronic stroke) performed a functional goal-directed two-sequence task with each arm, consisting of reaching and moving a cylindrical object (drain plunger) from an initial to four target platform heights, standardized to body height, in a block randomized sequence. Arm motor impairment (Fugl-Meyer Assessment) and visual-perceptual deficits (Motor-Free Visual Perception Test) were assessed in stroke subjects, and arm and trunk kinematics were assessed in all subjects. The primary outcome measure of the grasp-height effect was the relationship between the grasp heights used at the home position and the final target platform heights. Mixed model analysis was used for data analysis. The grasp-height effect was present in all participants, but decreased in stroke subjects with visuo-perceptual impairments compared to controls. In stroke subjects with sensorimotor impairments alone, indicated by altered kinematics, the grasp-height effect was comparable to controls. This first study examining the grasp-height effect in individuals with stroke provides new knowledge of the impact of visuo-perceptual deficits on movement planning and execution, which may assist clinicians in selecting more effective treatment strategies to improve perceptuo-motor skills and enhance motor recovery.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".