A Piezoelectric Actuated Airwave Oscillometry Device
Bibliographic record
Abstract
Oscillometry (OS), also known as the forced oscillation technique (FOT) is used to measure lung mechanics and can be used to assess airflow obstruction in diseases such as asthma and chronic obstructive pulmonary disease in adults and children that, over the last decade, has gained a place as an alternative to conventional spirometry used in research studies and clinical practice. OS applies low amplitude pressure oscillations during normal breathing and, unlike spirometry, it doesn’t require challenging respiratory maneuvers enabling its use in over a wider range of ages, patient physical conditions and treatment settings. The present article describes the design and construction of an OS device. Current technology for measuring impedance using oscillatory pressure and flow is bulky using a loudspeaker and devices are substantially more expensive than spirometers, which significantly slows the adoption of this technology despite its clinical advantages. The device we develop here is innovative in that it uses an inexpensive lightweight beam bending piezoelectric based actuator system potentially greatly reducing cost, and simplifying the mechanical requirements. The device applies oscillatory pressure at 6 Hz or 19 Hz by moving a mesh disk of known resistance within a chamber through which the patient also breathes. The signal to noise ratios of the pressure and flow signals were satisfactory, achieving greater than 30dB even when employed on test loads up to a resistance of 15 cmH2O/l/s. This device can be implemented as a clinical diagnostic device or for home use in monitoring applications or included within the breathing circuit during mechanical ventilation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".