Medicine and Health

Monitoring sleep using smartphone data in a population of college students

C. Langholm, A. J. S. Byun, et al.

Discover groundbreaking research by Carsten Langholm, Andrew Jin Soo Byun, Janet Mullington, and John Torous on how smartphone sensors can effectively monitor sleep in college students. This innovative study found a strong correlation between sensor-based and self-reported sleep durations, paving the way for practical and scalable sleep monitoring solutions using everyday technology.

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Playback language: English

Index

Abstract

This study investigates the feasibility of using smartphone sensor data to monitor sleep in college students. Data from 67 students using the mindLAMP app over 28 days was analyzed. Sensor-based sleep duration estimates correlated strongly with self-reported sleep duration (r=0.83). A predictive model using sensor data and surveys accurately predicted Pittsburgh Sleep Quality Index (PSQI) scores within 1 point. The findings suggest smartphone-based sleep monitoring offers a practical and scalable alternative to traditional methods.

Publisher

npj Mental Health Research

Published On

Mar 17, 2023

Authors

Carsten Langholm, Andrew Jin Soo Byun, Janet Mullington, John Torous

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