Distinguishing sleep from wake with a radar sensor: a contact-free real-time sleep monitor. Issue 8 (8th January 2021)

• Record Type: Journal Article
• Authors: Heglum, Hanne Siri Amdahl; Kallestad, Håvard; Vethe, Daniel; Langsrud, Knut; Sand, Trond; Engstrøm, Morten
• Is Part Of: Sleep. Volume 44:Issue 8(2021)
• Publication Date: 2021-01-08
• Subjects: sleep -- radar -- actigraphy -- polysomnography -- sleep monitoring -- ambulatory home monitoring; Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsab060
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: This 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.