Literature DB >> 31674096

(Not so) Smart sleep tracking through the phone: Findings from a polysomnography study testing the reliability of four sleep applications.

Edita Fino1, Giuseppe Plazzi2,3, Marco Filardi2, Michele Marzocchi4, Fabio Pizza2,3, Stefano Vandi2,3, Michela Mazzetti1.   

Abstract

An increasing number of sleep applications are currently available and are being widely used for in-home sleep tracking. The present study assessed four smartphone applications (Sleep Cycle-Accelerometer, SCa; Sleep Cycle-Microphone, SCm; Sense, Se; Smart Alarm, SA) designed for sleep-wake detection through sound and movement sensors, by comparing their performance with polysomnography. Twenty-one healthy participants (six males, 15 females) used the four sleep applications running on iPhone (provided by the experimenter) simultaneously with portable polysomnography recording at home, while sleeping alone for two consecutive nights. Whereas all apps showed a significant correlation with polysomnography-time in bed, only SA offered significant correlations for sleep efficacy. Furthermore, SA seemed to be quite effective in reliable detection of total sleep time and also light sleep; however, it underestimated wake and partially overestimated deep sleep. None of the apps resulted capable of detecting and scoring rapid eye movement sleep. To sum up, SC (functioning through both accelerometer and microphone) and Se did not result sufficiently reliable in sleep-wake detection compared with polysomnography. SA, the only application offering the possibility of an epoch-by-epoch analysis, showed higher accuracy than the other apps in comparison with polysomnography, but it still shows some limitations, particularly regarding wake and deep sleep detection. Developing scoring algorithms specific for smartphone sleep detection and adding external sensors to record other physiological parameters may overcome the present limits of sleep tracking through smart phone apps.
© 2019 European Sleep Research Society.

Entities:  

Keywords:  polysomnography; sleep applications; sleep tracking; smartphone

Mesh:

Year:  2019        PMID: 31674096     DOI: 10.1111/jsr.12935

Source DB:  PubMed          Journal:  J Sleep Res        ISSN: 0962-1105            Impact factor:   3.981


  2 in total

1.  The First-Night Effect in Elite Sports: An Initial Glance on Polysomnography in Home-Based Settings.

Authors:  Annika Hof Zum Berge; Michael Kellmann; Sarah Jakowski
Journal:  Front Psychol       Date:  2021-03-25

Review 2.  Framework for the Design Engineering and Clinical Implementation and Evaluation of mHealth Apps for Sleep Disturbance: Systematic Review.

Authors:  Melissa Aji; Christopher Gordon; Elizabeth Stratton; Rafael A Calvo; Delwyn Bartlett; Ronald Grunstein; Nick Glozier
Journal:  J Med Internet Res       Date:  2021-02-17       Impact factor: 5.428

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.