DEVELOPMENT OF A COMBINATION FORCED OSCILLATION - SPIROMETER DEVICE
Bibliographic record
Abstract
We developed a novel device, called the oscillation spirometer (OS) that can track changes in respiratory system impedance (Zrs) and can provide standard measures of respiratory resistance and spirometry. Current devices do not easily track temporal variation in Zrs. The device consists of a self-actuated piston containing an airflow resistance. During spirometry mode, the screen mesh pneumotachograph (PT) is stationary while during oscillation modes the PT translates generating oscillatory pressure. The actuator position is monitored continuously by a laser position sensing detector. To facilitate the design process, we developed a computer simulation of the actuator including mechanical and electromechanical compartments. A second model was created to simulate the patient Zrs and the two models were coupled and used to optimize design parameters such as magnet size, stroke volume, and piston cross-section, in a recursive design process. The result was a portable device with optimal stroke volume for expected patient loads. Three different designs were considered for the airflow resistance (orifice, groove and screen mesh resistances), and were tested using mock-up models. The final screen mesh resistance was linear, with a 98% lower 2nd order nonlinearity term than the next best design, and met American Thoracic Society standards. The OS could be used as a hand-held spirometer, or as a mounted FOT device suitable for detecting respiratory system resistance (Rrs) and its variation. It therefore has the potential to have a substantial impact in the respiratory market.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".