Effects of using wearable devices to monitoring physical activity in pulmonary rehabilitation programs for chronic respiratory diseases: A systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Pulmonary rehabilitation (PR) is an intervention aimed at the comprehensive care of individuals with chronic respiratory diseases. Patients with chronic obstructive pulmonary disease (COPD) and asthma present low levels of physical fitness because they avoid physical exercises due to the fear of triggering recurrent symptoms. Wearable devices have been integrated into behavioral modification interventions for physical activity in PR protocols. Therefore, this review aims to identify how wearable devices are being utilized for monitoring chronic respiratory diseases in pulmonary rehabilitation programs. METHODS AND ANALYSIS: Searches will be conducted on Medline, Cochrane Central Register of Controlled Trials, Embase (CENTRAL), CINAHL and PEDro electronic databases, as well as a search in the grey literature. We will include baseline data from randomized clinical trials reporting the use of wearable devices for monitoring physical activity in protocols for pulmonary rehabilitation programs for chronic respiratory diseases. Studies that discuss only the development of algorithms or applications for the assessment of diseases or unavailable full texts will be excluded. The main reviewer will conduct the initial search and exclusion of duplicates, while two independent reviewers will select studies, extract data, and assess the methodological quality using the PEDro tool. PROSPERO REGISTRATION NUMBER: CRD42024504137.
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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 | 0.039 | 0.043 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.021 | 0.014 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.065 | 0.006 |
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".