Shoulder Coordination During Full-Can and Empty-Can Rehabilitation Exercises
Bibliographic record
Abstract
CONTEXT: Supraspinatus tear is a common rotator cuff injury. During rehabilitation, debate persists regarding the most appropriate exercises. Whereas shoulder coordination is part of normal arm function, it has been infrequently considered in the context of exercise selection. OBJECTIVE: To assess shoulder-motion coordination during 2 common supraspinatus rehabilitation exercises and to characterize load and motion-direction influences on shoulder coordination. DESIGN: Descriptive laboratory study. SETTING: Motion-analysis laboratory. Patient or Other Participants : Fifteen asymptomatic right-hand-dominant men (age = 26 ± 4 years, height = 1.77 ± 0.06 m, mass = 74.3 ± 7.7 kg). INTERVENTION(S): Full-can and empty-can exercises with and without a 2.27-kg load. MAIN OUTCOME MEASURE(S): We recorded motion with an optoelectronic system. Scapulohumeral rhythm and complete shoulder joint kinematics were calculated to quantify shoulder coordination. The effects of exercise type, load, motion direction, and humerothoracic-elevation angle on the scapulohumeral rhythm and shoulder-joint angles were assessed. RESULTS: We observed multivariate interactions between exercise type and humerothoracic elevation and between load and humerothoracic elevation. Scapulohumeral rhythm increased by a mean ratio of 0.44 ± 0.22 during the full-can exercise, whereas the addition of load increased mean glenohumeral elevation by 4° ± 1°. CONCLUSIONS: The full-can exercise increased the glenohumeral contribution, as hypothesized, and showed normal shoulder coordination. During the empty-can exercise, the increased scapulothoracic contribution was associated with a compensatory pattern that limits the glenohumeral contribution. Using loads during shoulder rehabilitation seems justified because the scapulohumeral rhythm is similar to that of unloaded arm elevation. Finally, motion direction showed a limited effect during the exercises in healthy individuals.
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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) | 0.002 | 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".