A Device for Prehabilitation of Total Knee Replacement Surgery (Slider): Usability Study
Bibliographic record
Abstract
BACKGROUND: Rehabilitation, or "prehabilitation," is essential in preparing for and recovering from knee replacement surgery. The recent demand for these services has surpassed available resources, a situation further strained by the COVID-19 pandemic, which has led to a pivot toward digital solutions such as web- or app-based videos and wearables. These solutions, however, face challenges with user engagement, calibration requirements, and skin contact issues. This study evaluated the practicality of a low-contact, gamified device designed to assist with prehabilitation exercises. OBJECTIVE: The study aimed to assess the practicality and user-friendliness of a newly designed physiotherapy device (Slider) that enables exercise monitoring without the need for direct contact with the skin. METHODS: A total of 17 patients awaiting knee replacement surgery at a UK National Health Service (NHS) hospital participated in this study. They used the device over a 2-week period and subsequently provided feedback through a usability and acceptability questionnaire. RESULTS: The study was completed by all participants, with a majority (13/17, 76%) finding the device intuitive and easy to use. The majority of patients were satisfied with the device's ability to meet their presurgery physiotherapy requirements (16/17, 94%) and expressed a willingness to continue using it (17/17, 100%). No safety issues or adverse effects were reported by the participants. CONCLUSIONS: The results indicate that the device was found to be a feasible option for patients to conduct presurgery physiotherapy exercises independently, away from a clinical setting. Further research involving a larger and more diverse group of participants is recommended to validate these findings more robustly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".