@Article{info:doi/10.2196/13421,
author="Lin, Yu-Hsuan
and Wong, Bo-Yu
and Pan, Yuan-Chien
and Chiu, Yu-Chuan
and Lee, Yang-Han",
title="Validation of the Mobile App--Recorded Circadian Rhythm by a Digital Footprint",
journal="JMIR Mhealth Uhealth",
year="2019",
month="May",
day="16",
volume="7",
number="5",
pages="e13421",
keywords="circadian rhythm; sleep; smartphone; mobile applications",
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. ",
issn="2291-5222",
doi="10.2196/13421",
url="https://mhealth.jmir.org/2019/5/e13421/",
url="https://doi.org/10.2196/13421",
url="http://www.ncbi.nlm.nih.gov/pubmed/31099340"
}