TY - JOUR
T1 - Breath monitoring, sleep disorder detection and tracking using thin film acoustic waves and open-source electronics
AU - Vernon, Jethro
AU - Canyelles-Pericas, Pep
AU - Torun, Hamdi
AU - Binns, Richard
AU - Ng, Wai Pang
AU - Wu, Qiang
AU - Fu, Yongqing (Richard)
N1 - 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).
PY - 2022/9/1
Y1 - 2022/9/1
N2 - 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.
AB - 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.
KW - Surface acoustic waves
KW - sleep disorder
KW - apnoea
KW - open-source electronics
KW - pattern recognition
KW - piezoelectric thin film
U2 - 10.1063/10.0013471
DO - 10.1063/10.0013471
M3 - Article
SN - 2589-5540
VL - 5
JO - Nanotechnology and Precision Engineering
JF - Nanotechnology and Precision Engineering
IS - 3
M1 - 033002
ER -