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App-driven oscillometry

Open-source, low-cost App-driven Internet of Things approach to facilitate respiratory oscillometry at home and in developing countries

González JE, Rodríguez MA, Caballero E, Pardo A, Marco S, Farré R.

Pulmonology, 30: 180-183, 2024.   DOI: 10.1016/j.pulmoe.2023.10.004

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ABSTRACT

Background: Oscillometry is useful for monitoring respiratory mechanics, but widely extending the technique to small healthcare centers and home monitoring is unaffordable with the so far industrial approach based on relatively high-cost stand-alone devices. Here the aim was to prove that a novel e-Health oscillometry approach consisting of a low-cost, open-source, App-driven oscillometry device is feasible. Methods: The setting is based on three components: A) a manager website for the healthcare staff to include new patients (with individual measuring conditions, e.g., oscillation frequencies), and to browse patients' oscillometry data. B) an App controlling the oscillometry measurement guides the patient with screen and audio instructions along the measurement, computes and shows the oscillometry data (including outlier detection), and uploads them to the website. C) a simple App-driven measuring device based on low-cost components (4"-loudspeaker, transducers, filters, and Internet-of-Things Arduino microcontroller). As the App already provides the computation and user interface functions, the measuring device is very cheap (<100 €).  Results: The setting functionality was repeatedly tested with simulated patient analogs and a spontaneously breathing voluntary subject, showing robust performance. The detailed codes for the website, App and Arduino are freely available in open-source format (Supplementary material), so any user can replicate (or adapt) the setting. Conclusion: The developed and tested e-Health oscillometry setting proves that a low-cost approach may be developed for affordably extending the application of oscillometry in small healthcare centers and for home monitoring in both developed and low- and middle-income countries.

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© Ramon Farré
October 2023

Unit of Biophysics and Bioengineering
School of Medicine and Health Sciences
Casanova 143
08036 Barcelona, Spain

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