University of Twente Student Theses


Sleep Apnoea Detection Using Small & Cheap Sensors

Benistant, J.R. (2016) Sleep Apnoea Detection Using Small & Cheap Sensors.

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Abstract:Sleep apnoea syndrome (SAS) is a more occurring disease with big consequences if left untreated. The registration is expensive and uncomfortable. We want to introduce a cheap and small tool that can correctly register SAS in large populations. We have designed a BTLE sensor capable or registering the respiratory effort and pressure signal. Our data is pre-processed and analysed in existing sleep apnoea analysing software. We included 10 patients. We used 4 accelerometers, a pressure sensor (nasal cannula), a pulse oximeter and laptop microphone during our registrations. We found an agreement of 87.1\% of the registered events with the gold standard, the polysomnography (PSG). Our pressure signal showed a very good linear correlation ($r^2$=0.9451) with the PSG signal. Our respiratory effort signal has a high linear correlation ($r^2$=0.8381) with the PSG's RIP band and our registered oxygen desaturation index has a maximum deviation of 1 event/hour. Our analysis would have scored 7 out of 9 patients in the right sleep apnoea category. With this study we have shown that it is possible to reliably determine SAS by using cheap electronics, a laptop and existing analysing software.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Subject:44 medicine
Programme:Technical Medicine MSc (60033)
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