TY  - JOUR
AU  - Ciman, Matteo
AU  - Wac, Katarzyna
PY  - 2019
DA  - 2019/05/21
TI  - Smartphones as Sleep Duration Sensors: Validation of the iSenseSleep Algorithm
JO  - JMIR Mhealth Uhealth
SP  - e11930
VL  - 7
IS  - 5
KW  - mobile phone use
KW  - mobile health
KW  - behavioral research
KW  - well being
AB  - Background: Smartphones are becoming increasingly ubiquitous every day; they are becoming more assimilated into our everyday life, being the last thing used before going to sleep and the first one after waking up. This strong correlation between our lifestyle choices and smartphone interaction patterns enables us to use them as sensors for sleep duration assessment to understand individuals’ lifestyle and sleep patterns. Objectives: The objective of this study was to estimate sleep duration based on the analysis of the users’ ON-OFF interaction with their smartphone alone using the iSenseSleep algorithm. Methods: We used smartwatch sleep assessment data as the ground truth. Results were acquired with 14 different subjects collecting smartwatch and smartphone interaction data for up to 6 months each. Results: Results showed that based on the smartphone ON-OFF patterns, individual’s sleep duration can be estimated with an average error of 7% (24/343) [SD 4% (17/343)] min of the total duration), enabling an estimate of sleep start and wake-up times as well as sleep deprivation patterns. Conclusions: It is possible to estimate sleep duration patterns using only data related to smartphone screen interaction. 
SN  - 2291-5222
UR  - http://mhealth.jmir.org/2019/5/e11930/
UR  - https://doi.org/10.2196/11930
UR  - http://www.ncbi.nlm.nih.gov/pubmed/31115341
DO  - 10.2196/11930
ID  - info:doi/10.2196/11930
ER  -