Effect of a Wearable Motion Sensor Device in Facilitating In-Home Rehabilitation Program in Patients After Total Knee Arthroplasty (Preprint)
Bibliographic record
Abstract
BACKGROUND Total knee arthroplasty (TKA) is an effective procedure for patients with end-stage knee osteoarthritis. Postoperative rehabilitation programs are essential for facilitating functional recovery after TKA. However, clinical results vary because of inconsistent patient compliance. OBJECTIVE This study aimed to verify the feasibility of a treatment model that involves applying a wearable motion sensor device (MSD) to assist patients in performing home-based exercises after TKA. METHODS The MSD comprised inertial measurement unit–based sensors and mobile apps for patients and physicians, which allowed for knee mobility tracing, home-based exercise support, and progress monitoring. The interrater reliability of knee mobility measurements was assessed using the intraclass correlation coefficient (ICC). Different knee flexion angles and the time spent for completing the 5-times sit-to-stand test (5TSST) in 12 healthy participants were measured by 2 experienced physicians and using the MSD, and their results were compared using ICC. A pilot prospective control trial was then conducted, in which 12 patients following TKA were allocated to 2 groups: the home-based exercise group and the MSD-assisted rehabilitation group. Changes in knee range of motion, pain, functional score (assessed using the Western Ontario and McMaster Universities Arthritis Index), performance (tested using 5TSST), and exercise completion rates were compared between the groups over 2 months of follow-up. RESULTS Knee flexion at different angles and the time spent for completing 5TSST measured using the MSD exhibited excellent reliability compared with the physician measurements (ICC range: 0.996 and 0.996 respectively). Furthermore, patients in the MSD-assisted rehabilitation group reported higher exercise completion rate within 2 months of the in-home exercise program compared with participants in the home-based exercise group, which lead to more favorable outcomes in the knee extension angle and maximal and average angular velocity in 5TSST. CONCLUSIONS MSD-assisted home-based rehabilitation following TKA is a useful treatment model for telerehabilitation because it enhances patients’ compliance to training, which improves functional recovery. This method helps overcome critical obstacles in home-based physiotherapy among patients after TKA. Therefore, this study has crucial implications for patients and health systems.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".