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, Yong Qing
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).
Publisher Copyright:
© 2022 Author(s).
PY - 2022/9/1
Y1 - 2022/9/1
N2 - Apnoea, a major sleep disorder, affects many adults and causes 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 treatment, 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 apnoea-Pi open-source surface acoustic wave (SAW) platform (Apnoea-Pi) to monitor and recognise apnoea in patients. The platform is based on a thin-film SAW device using bimorph ZnO and Al structures, including those fabricated as Al foils or plates, to achieve breath tracking based on 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 the thin-film SAW device out-performed standard and off-the-shelf capacitive electronic sensors in terms of their response 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, affects many adults and causes 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 treatment, 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 apnoea-Pi open-source surface acoustic wave (SAW) platform (Apnoea-Pi) to monitor and recognise apnoea in patients. The platform is based on a thin-film SAW device using bimorph ZnO and Al structures, including those fabricated as Al foils or plates, to achieve breath tracking based on 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 the thin-film SAW device out-performed standard and off-the-shelf capacitive electronic sensors in terms of their response 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.
UR - http://www.scopus.com/inward/record.url?scp=85137116011&partnerID=8YFLogxK
U2 - 10.1063/10.0013471
DO - 10.1063/10.0013471
M3 - Article
AN - SCOPUS:85137116011
VL - 5
JO - Nami Jishu yu Jingmi Gongcheng/Nanotechnology and Precision Engineering
JF - Nami Jishu yu Jingmi Gongcheng/Nanotechnology and Precision Engineering
SN - 1672-6030
IS - 3
M1 - 033002
ER -