Design and testing of breathing retraining device a multiphasic exploratory study in healthy subjects
Bibliographic record
Abstract
Introduction and aim. Traditional spirometers are limited by bulkiness and lack of biofeedback, which can hinder their effec tiveness in pulmonary rehabilitation. This study aimed to evaluate the accuracy of an innovative breathing retraining device in measuring inhaled volume and assess user satisfaction compared to standard spirometers. Material and methods. A multiphasic exploratory study was conducted with 102 healthy adults (aged 18–60 years). The study included three phases: need analysis through focus group discussions, prototype development using polycarbonate materials and 3D printing, and effectiveness testing. Inhalation exercises were performed with both the new device and a standard spi rometer. Primary outcomes were inhaled volume and marker displacement, with user satisfaction assessed via the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) questionnaire. Results. The new device showed a strong correlation between inhaled volume and marker displacement (r=0.842, p<0.001). The mean inhaled volume was 2.07±0.61 liters, with a mean marker displacement of 5.19±0.59 cm. The mean QUEST 2.0 satis faction score was 3.54, indicating high user satisfaction. Conclusion. The redesigned breathing retraining device not only addresses critical gaps in existing technologies but also offers a practical, user-friendly solution for pulmonary rehabilitation. By combining accuracy, real-time feedback, and portability, this innovation has the potential to redefine respiratory therapy standards in both clinical and home-based settings, paving the way for broader applications and improved patient outcomes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".