An Affordable, User-friendly Telerehabilitation System Assembled Using Existing Technologies for Individuals Isolated With COVID-19: Development and Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Isolation due to a COVID-19 infection can limit activities and cause physical and mental decline, especially in older adults and people with disabilities. However, due to limited contact, adequate rehabilitation is difficult to provide for quarantined patients. Telerehabilitation technology could be a solution; however, issues specific to COVID-19 should be taken into consideration, such as strict quarantine and respiratory symptoms, as well as accessibility to deal with rapid increases in need due to the pandemic. OBJECTIVE: This study aims to develop and to investigate the feasibility of a telerehabilitation system for patients who are quarantined due to COVID-19 by combining existing commercial devices and computer applications. METHODS: A multidisciplinary team has identified the requirements for a telerehabilitation system for COVID-19 and developed the system to satisfy those requirements. In the subsequent feasibility study, patients diagnosed with COVID-19 (N=10; mean age 60 years, SD 18 years) were included. A single session of telerehabilitation consisted of stretching exercises, a 15-minute exercise program, and a video exercise program conducted under real-time guidance by a physical therapist through a video call. The system included a tablet computer, a pulse oximeter, videoconferencing software, and remote control software. The feasibility of the system was evaluated using the Telemedicine Satisfaction Questionnaire (TSQ; 14 items) and an additional questionnaire on the telerehabilitation system (5 items). Each item was rated from "1 = strongly disagree" to "5 = strongly agree." RESULTS: The telerehabilitation system was developed by combining existing devices and applications, including a pulse oximeter and remote control mechanism, to achieve user-friendliness, affordability, and safety, which were determined as the system requirements. In the feasibility study, 9 out of 10 patients were able to use the telerehabilitation system without any on-site help. On the TSQ, the mean score for each item was 4.7 (SD 0.7), and in the additional items regarding telerehabilitation, the mean score for each item was 4.3 (SD 1.0). CONCLUSIONS: These findings support the feasibility of this simple telerehabilitation system in quarantined patients with COVID-19, encouraging further investigation on the merit of the system's use in clinical practice.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".