Breath monitoring, sleep disorder detection and tracking using thin film acoustic waves and open-source electronics

Jethro Vernon, Pep Canyelles-Pericas, Hamdi Torun, Richard Binns, Wai Pang Ng, Qiang Wu, Yongqing Fu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
JournalNanotechnology and Precision Engineering
Publication statusAccepted/In press - 27 Jul 2022

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