1. Apnoea-Pi
- Author
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Vernon, Jethro, Canyelles-Pericas, Pep, Torun, Hamdi, Binns, Richard, Ng, Wai Pang, Fu, Yong Qing, Yang, Chenguang, Yang, Chenguang, Integrated Devices and Systems, and MESA+ Institute
- Subjects
medicine.medical_specialty ,Time series identification ,Surface acoustic waves ,Piezoelectric thin films ,Physical medicine and rehabilitation ,Apnoea ,Pattern recognition ,medicine ,In patient ,Electronics ,G100 ,Sleep disorder ,business.industry ,G500 ,G400 ,Sleep apnea ,Sleep disorders ,G600 ,medicine.disease ,respiratory tract diseases ,Increased risk ,Open source ,2023 OA procedure ,Open-source electronics ,Sleep (system call) ,business - Abstract
Apnoea is a sleep disorder that affects an increasing number of adults causing harm from fatigue to a growing chance of heart problems. Apnoea disorders can be treated but advanced monitoring and diagnosing tools are needed to identify its strand and offer adequate treatment. Therefore, Apnoea tracking is vital to help keep patients healthy. Sleep Apnoea can cause a number of conditions such as fatigue, high blood pressure, liver functionality and an increased risk of type 2 diabetes. These complications make it necessary to monitor as many potential patients as possible by designing an instrument that is accurate, comfortable to use, fit for purpose, cost effective and with embedded computation capabilities to store, process and transmit time series data. In this work we present Apnoea-Pi, an adaptation of our Acousto-Pi open source surface acoustic wave platform to monitor Apnoea in patients using ultrasonic humidity sensing.
- Published
- 2021
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