Optical wrist-worn device for sleep monitoring

dc.contributor.authorRenevey, Philippe
dc.contributor.authorDelgado-Gonzalo, Ricard
dc.contributor.authorLemkaddem, Alia
dc.contributor.authorProença, Martin
dc.contributor.authorLemay, Mathieu
dc.contributor.authorSolà, Josep
dc.contributor.authorTarniceriu, Adrian
dc.contributor.authorBertschi, Mattia
dc.date.accessioned2022-02-14T17:07:48Z
dc.date.available2022-02-14T17:07:48Z
dc.date.issued2018
dc.description.abstractThis paper presents and clinically validates a new method to accurately classify sleep phases within a wrist-worn device (e.g., smartwatch, ?tnessband). The method combines inertial and optical sensors to compute the wearer’s motion, breathing rate, and pulse rate variability, and to estimate the different sleep stages (WAKE, REM and NREM). The presented method achieves a sensitivity and speci?city for the REM of 89.2 % and 77.9 % respectively; for the NREM class 83.4 % and 84.9 % respectively; and a median accuracy of 81.4 %. The assessment of the performance was obtained by comparing to the gold standard measure in sleep monitoring, polysomnography.
dc.identifier.citationEMBEC & NBC 2017, H. Eskola, O. Väisänen, J. Viik, J. Hyttinen (Eds.), Singapore (Singapore), pp. 615-618
dc.identifier.doi10.1007/978-981-10-5122-7_154
dc.identifier.isbn978-981-10-5121-0 978-981-10-5122-7
dc.identifier.urihttps://hdl.handle.net/20.500.12839/692
dc.identifier.urlhttp://link.springer.com/10.1007/978-981-10-5122-7_154
dc.titleOptical wrist-worn device for sleep monitoring
dc.typeProceedings Article
dc.type.csemdivisionsBU-D
dc.type.csemresearchareasDigital Health
Files