Technologically sensed social exposure related to slow-wave sleep in healthy adults
Name
11325_2014_1005_ReferencePDF.pdf
Size
413.67 KB
Format
Adobe PDF
Checksum (MD5)
62be95543b3eaba0721652bdd9de2a23
Author(s)
Butt, Maryam
Ouarda, Taha B. M. J.
Quan, Stuart F.
Pentland, Alex Paul
Khayal, Inas
Date Issued
May 2014
Journal
Sleep and Breathing
Publisher
Springer Berlin Heidelberg
Citation
Butt, Maryam, Taha B. M. J. Ouarda, Stuart F. Quan, Alex Pentland, and Inas Khayal. “Technologically Sensed Social Exposure Related to Slow-Wave Sleep in Healthy Adults.” Sleep Breath 19, no. 1 (May 27, 2014): 255–261.
Version
Author's final manuscript
Abstract
Objective:
The aim of this study is to understand the relationship between automatically captured social exposure and detailed sleep parameters of healthy young adults.
Methods:
This study was conducted in a real-world setting in a graduate-student housing community at a US university. Social exposure was measured using Bluetooth proximity sensing technology in mobile devices. Sleep was monitored in a naturalistic setting using a headband sleep monitoring device over a period of 2 weeks. The analysis included a total of 11 subjects (6 males and 5 females) aged 24–35 (149 subject nights).
Results:
Slow-wave sleep showed a significant positive correlation (Spearman’s rho = 0.51, p < 0.0001) with social exposure, whereas light non-REM (N1 + N2) sleep and wake time were found to be negatively correlated (rho = −0.25, p < 0.01; rho = −0.21, p < 0.01, respectively). The correlation of median slow-wave sleep with median social exposure per subject showed a strong positive significance (rho = 0.88, p < 0.001). On average, within subjects, following day’s social exposure was higher when (slow-wave NREM + REM) percentage was high (Wilcoxon sign-ranked test, p < 0.05).
Conclusions:
Subjects with higher social exposure spent more time in slow-wave sleep. Following day’s social exposure was found to be positively affected by previous night’s (slow-wave NREM + REM) percentage. This suggests that sleep affects following day’s social exposure and not vice versa. Capturing an individual’s dynamic social behavior and sleep from their natural environment can provide novel insights into these relationships.
MIT Department
MIT Technology and Development Program
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/s11325-014-1005-x
