Vernon, Jethro, Canyelles-Pericas, Pep, Torun, Hamdi, Binns, Richard, Ng, Wai Pang, Wu, Qiang and Fu, Yong Qing (2022) Breath monitoring, sleep disorder detection and tracking using thin film acoustic waves and open-source electronics. Nanotechnology and Precision Engineering, 5 (3). 033002. ISSN 2589-5540
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Abstract
Apnoea, a major sleep disorder, has affected many adults and caused several issues, such as fatigue, high blood pressure, liver conditions, increased risk of type II diabetes and heart problems. Therefore, advanced monitoring and diagnosing tools of apnoea disorders are needed to facilitate better treatments, with advantages such as accuracy, comfort of use, cost effectiveness and embedded computation capabilities to recognise, store, process and transmit time series data. In this work we present an adaptation of our Acousto-Pi open-source Surface Acoustic Wave (SAW) platform (Apnoea-Pi), to monitor and recognise apnoea in patients. The platform is based on thin film SAW, using bimorph ZnO and aluminium structures, including those fabricated in Al foils or plates, to achieve for breath tracking based on the humidity and temperature changes. We applied open-source electronics and provided embedded computing characteristics for signal processing, data recognition, storage, and transmission of breath signals. We show that thin film SAW devices out-perform standard and off-the-shelf capacitive electronic sensors regarding to their responses and accuracy for human breath tracking purposes. This in combination with embedded electronics makes a suitable platform for human breath monitoring and sleep disorder recognition.
Item Type: | Article |
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Additional Information: | Funding information: This work was financially supported by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant EP/P018998/1, as well as the UK Fluidic Network Special Interest Group of Acoustofluidics (EP/N032861/1). |
Uncontrolled Keywords: | Surface acoustic waves, sleep disorder, apnoea, open-source electronics, pattern recognition, piezoelectric thin film |
Subjects: | B900 Others in Subjects allied to Medicine F200 Materials Science H600 Electronic and Electrical Engineering |
Department: | Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering |
Depositing User: | John Coen |
Date Deposited: | 04 Aug 2022 14:23 |
Last Modified: | 14 Sep 2022 14:30 |
URI: | https://nrl.northumbria.ac.uk/id/eprint/49743 |
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