Validation of the Mobile App-Recorded Circadian Rhythm by a Digital Footprint.

Abstract:

BACKGROUND:Modern smartphone use is pervasive and could be an accessible method of evaluating the circadian rhythm and social jet lag via a mobile app. OBJECTIVE:This study aimed to validate the app-recorded sleep time with daily self-reports by examining the consistency of total sleep time (TST), as well as the timing of sleep onset and wake time, and to validate the app-recorded circadian rhythm with the corresponding 30-day self-reported midpoint of sleep and the consistency of social jetlag. METHODS:The mobile app, Rhythm, recorded parameters and these parameters were hypothesized to be used to infer a relative long-term pattern of the circadian rhythm. In total, 28 volunteers downloaded the app, and 30 days of automatically recorded data along with self-reported sleep measures were collected. RESULTS:No significant difference was noted between app-recorded and self-reported midpoint of sleep time and between app-recorded and self-reported social jetlag. The overall correlation coefficient of app-recorded and self-reported midpoint of sleep time was .87. CONCLUSIONS:The circadian rhythm for 1 month, daily TST, and timing of sleep onset could be automatically calculated by the app and algorithm.

journal_name

JMIR Mhealth Uhealth

journal_title

JMIR mHealth and uHealth

authors

Lin YH,Wong BY,Pan YC,Chiu YC,Lee YH

doi

10.2196/13421

subject

Has Abstract

pub_date

2019-05-16 00:00:00

pages

e13421

issue

5

issn

2291-5222

pii

v7i5e13421

journal_volume

7

pub_type

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