Effects of augmented reality-based telerehabilitation in adhesive capsulitis of the shoulder: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Home exercise is important for the treatment of adhesive capsulitis of the shoulder (ACS). Although studies on telerehabilitation to increase compliance and accuracy of home exercise are increasing in various musculoskeletal conditions, there are few studies on ACS. OBJECTIVES: This study aims to investigate the effectiveness of augmented reality (AR)-based asynchronous telerehabilitation using UNICARE Home+ versus conventional home exercise in participants with ACS. METHODS: One hundred participants with unilateral ACS were recruited and randomly assigned to telerehabilitation group (TR group) and conventional rehabilitation group (CR group). All participants, regardless of group, received the same hospital-based physical therapy once or twice for at least 3 months, plus an additional 3 months of home exercise. The TR group performed home exercises with an asynchronous telerehabilitation system, and the CR group performed home exercises with brochures. The primary outcome was the changes in the passive range of motion (PROM) of the affected shoulder joint between baseline and 3 months. The secondary outcomes were active ROM (AROM), shoulder pain measured by Numeric Rating Scale (NRS), shoulder pain and disability index (SPADI), 36-Item Short Form Survey (SF-36), European Quality of Life Five Dimensions Five Level Scale (EQ-5D-5L), and Canadian Occupational Performance Measure (COPM) at the 6 assessment points: at baseline, 1-, 2-, 3-, 4.5- and 6-month. RESULTS: There were no statistically significant differences in baseline PROM and 3-month PROM between the 2 groups. From baseline to 6 months, all PROM, all AROM, NRS, SPADI, COPM, SF-36 and EQ-5D-5L were significantly improved over time within each group in both groups (all P<0.001). However, there was no significant Group×Time interaction in any outcome, which means that the effect of time did not depend on which group the participants belonged to. CONCLUSION: AR and Kinect sensor-based telerehabilitation for participants with ACS improved shoulder pain, functional outcomes, and quality of life, but did not show superiority over conventional rehabilitation. CLINICALTRIALS: gov: NCT04316130.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".