Philippe Renevey, Ricard Delgado-Gonzalo1, Christophe Verjus2, Josep Sola3, Selina Combertaldi, Björn Rasch, Brigitte Leeners, Franziska Dammeier, Florian Kübler
1-Page Extended Abstract (Poster)
18:15 - 20:15 | Mon 5 Mar | Caribbean ABC | MoPO
Sleep is a natural mechanism that allows the restoration of cognitive and physical abilities in humans and most mammals. The alteration of the normal sleep pattern is an indication of an underlying medical condition, or of a degradation of sleep itself, and is therefore a significant indicator of health status. The gold standard for sleep analysis is the polysomnograph (PSG). Its obtrusiveness makes it unsuitable for long-term sleep studies. Recently it has been shown that using an optical wrist-worn sensor allows to obtain reliable estimates of cardiac activity (e.g., beat-to-beat intervals) with minimal obtrusiveness. The detection of beat-to-beat intervals allows for the subsequent estimation of several key features such as heart rate, heart rate variability (HRV), sleep phases, and respiration rate during sleep. The current paper presents the performance of the wrist-worn device at performing multiple tasks: (1) detecting beat-to-beat intervals, (2) estimating heart rate, and (3) estimating respiration rate. The data collected for the performance evaluation has been obtained using the commercial system developed by Ava. This system acquires simultaneous data from a three-axis accelerometer and a photoplethysmography (PPG) sensor.
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