Compensatory Versus Noncompensatory Shoulder Movements Used for Reaching in Stroke
Why this work is in the frame
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Bibliographic record
Abstract
Background The extent to which the upper-limb flexor synergy constrains or compensates for arm motor impairment during reaching is controversial. This synergy can be quantified with a minimal marker set describing movements of the arm-plane. Objectives To determine whether and how (a) upper-limb flexor synergy in patients with chronic stroke contributes to reaching movements to different arm workspace locations and (b) reaching deficits can be characterized by arm-plane motion. Methods Sixteen post-stroke and 8 healthy control subjects made unrestrained reaching movements to targets located in ipsilateral, central, and contralateral arm workspaces. Arm-plane, arm, and trunk motion, and their temporal and spatial linkages were analyzed. Results Individuals with moderate/severe stroke used greater arm-plane movement and compensatory trunk movement compared to those with mild stroke and control subjects. Arm-plane and trunk movements were more temporally coupled in stroke compared with controls. Reaching accuracy was related to different segment and joint combinations for each target and group: arm-plane movement in controls and mild stroke subjects, and trunk and elbow movements in moderate/severe stroke subjects. Arm-plane movement increased with time since stroke and when combined with trunk rotation, discriminated between different subject groups for reaching the central and contralateral targets. Trunk movement and arm-plane angle during target reaches predicted the subject group. Conclusions The upper-limb flexor synergy was used adaptively for reaching accuracy by patients with mild, but not moderate/severe stroke. The flexor synergy, as parameterized by the amount of arm-plane motion, can be used by clinicians to identify levels of motor recovery in patients with 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 | 0.002 |
| 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) | 0.000 | 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