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dc.contributor.authorHeglum, Hanne Siri Amdahl
dc.contributor.authorKallestad, Håvard
dc.contributor.authorVethe, Daniel
dc.contributor.authorLangsrud, Knut
dc.contributor.authorSand, Trond
dc.contributor.authorEngstrøm, Morten
dc.date.accessioned2023-04-13T06:26:44Z
dc.date.available2023-04-13T06:26:44Z
dc.date.created2021-09-20T16:31:14Z
dc.date.issued2021
dc.identifier.citationSleep. 2021, 44 (8), 1-15.en_US
dc.identifier.issn0161-8105
dc.identifier.urihttps://hdl.handle.net/11250/3062753
dc.description.abstractThis work aimed to evaluate whether a radar sensor can distinguish sleep from wakefulness in real time. The sensor detects body movements without direct physical contact with the subject and can be embedded in the roof of a hospital room for completely unobtrusive monitoring. We conducted simultaneous recordings with polysomnography, actigraphy, and radar on two groups: healthy young adults (n = 12, four nights per participant) and patients referred to a sleep examination (n = 28, one night per participant). We developed models for sleep/wake classification based on principles commonly used by actigraphy, including real-time models, and tested them on both datasets. We estimated a set of commonly reported sleep parameters from these data, including total-sleep-time, sleep-onset-latency, sleep-efficiency, and wake-after-sleep-onset, and evaluated the inter-method reliability of these estimates. Classification results were on-par with, or exceeding, those often seen for actigraphy. For real-time models in healthy young adults, accuracies were above 92%, sensitivities above 95%, specificities above 83%, and all Cohen's kappa values were above 0.81 compared to polysomnography. For patients referred to a sleep examination, accuracies were above 81%, sensitivities about 89%, specificities above 53%, and Cohen's kappa values above 0.44. Sleep variable estimates showed no significant intermethod bias, but the limits of agreement were quite wide for the group of patients referred to a sleep examination. Our results indicate that the radar has the potential to offer the benefits of contact-free real-time monitoring of sleep, both for in-patients and for ambulatory home monitoring.en_US
dc.language.isoengen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleDistinguishing sleep from wake with a radar sensor: A contact-free real-time sleep monitoren_US
dc.title.alternativeDistinguishing sleep from wake with a radar sensor: A contact-free real-time sleep monitoren_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber1-15en_US
dc.source.volume44en_US
dc.source.journalSleepen_US
dc.source.issue8en_US
dc.identifier.doi10.1093/sleep/zsab060
dc.identifier.cristin1936248
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal