Objective measurement of sleep by smartphone application: comparison with actigraphy and relation to self-reported sleep

Author:

Maynard Taylor1ORCID,Appleman Erica2ORCID,Cronin-Golomb Alice2ORCID,Neargarder Sandy3

Affiliation:

1. Department of Psychology, Bridgewater State University, Bridgewater, MA 02324, USA

2. Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA

3. Department of Psychology, Bridgewater State University, Bridgewater, MA 02324, USA; Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA

Abstract

Aim: Smartphone technology is increasingly used by the public to assess sleep. Specific features of some sleep-tracking applications are comparable to actigraphy in objectively monitoring sleep. The clinical utility of smartphone apps should be investigated further to increase access to convenient means of monitoring sleep. Methods: Smartphone and subjective sleep measures were administered to 29 community-dwelling healthy adults [aged 20-67, Mean (M) = 26.8; 18 women, 11 men], and actigraphy to 19 of them. Total sleep time (TST) and sleep efficiency were measured with actigraphy and the Sleep Time app (Azumio Inc.). Sleep diaries captured subjective TST and sleep efficiency, and the Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index provided self-report data. An exit questionnaire was administered to examine app feasibility and likelihood of future use. Results: The app significantly overestimated TST when compared to actigraphy. There was no significant difference in sleep efficiency between methodologies. There was also no significant difference between TST recorded through the app and through sleep diaries. Participants’ self-reported ease of use of the smartphone app positively correlated with likelihood of future use. Conclusions: Based on the current findings, future research is needed to investigate the utility and feasibility of multiple smartphone applications in monitoring sleep in healthy and clinical populations.

Publisher

Open Exploration Publishing

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Modeling Sleep Quality Depending on Objective Actigraphic Indicators Based on Machine Learning Methods;International Journal of Environmental Research and Public Health;2022-08-11

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