Literature DB >> 33705555

Distinguishing sleep from wake with a radar sensor A contact-free real-time sleep monitor.

Hanne Siri Amdahl Heglum1,2, Håvard Kallestad3,4, Daniel Vethe3,4, Knut Langsrud3,4, Rond Sand1,5, Morten Engstrøm1,5.   

Abstract

This work aimed to evaluate if 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 exam (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 this 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 exam, accuracies were above 81%, sensitivities about 89%, specificities above 53% and Cohen's kappa values above 0.44. Sleep variable estimates showed no significant inter-method bias, but the limits of agreement were quite wide for the group of patients referred to a sleep exam. 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. © Sleep Research Society 2021. Published by Oxford University Press on behalf of the Sleep Research Society.

Entities:  

Keywords:  Sleep; actigraphy; ambulatory home monitoring; polysomnography; radar; sleep monitoring

Year:  2021        PMID: 33705555     DOI: 10.1093/sleep/zsab060

Source DB:  PubMed          Journal:  Sleep        ISSN: 0161-8105            Impact factor:   5.849


  2 in total

1.  Evaluating consumer and clinical sleep technologies: an American Academy of Sleep Medicine update.

Authors:  Sharon Schutte-Rodin; Maryann C Deak; Seema Khosla; Cathy A Goldstein; Michael Yurcheshen; Ambrose Chiang; Dominic Gault; Joseph Kern; Daniel O'Hearn; Scott Ryals; Nitun Verma; Douglas B Kirsch; Kelly Baron; Steven Holfinger; Jennifer Miller; Ruchir Patel; Sumit Bhargava; Kannan Ramar
Journal:  J Clin Sleep Med       Date:  2021-11-01       Impact factor: 4.062

2.  Time to put a spotlight on out-patient chronotherapy for depression.

Authors:  Havard Kallestad; Jan Scott
Journal:  BJPsych Open       Date:  2021-11-24
  2 in total

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