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In this study the feasibility of detecting sleep apnoeas with unobtrusive wearable sensors and sounds recorded with a smartphone is studied by making an overnight recording to patients with high probability of sleep apnoeas. The data acquired with the aforementioned devices is: ECG, acceleration, bioimpedance of thorax and processed and raw audio. In data analysis phase it will be studied which combinations of these signals would enable detecting sleep apnoeas with high enough sensitivity and specificity when compared to a night polygraphy reference (Nox T3 device using airflow, breathing movements, audio, position, movement, oxygen saturation, pulse and leg EMG).
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