Self-Reported Exercise and Objectively Measured Sleep: A Big Data Consumer Sleep Technology Analysis.
Gahan et al., (2022). SLEEP, 45 (S1), A148-A149.
Scientific Papers and Peer Reviewed Publications
Alcohol and caffeine are associated with poor sleep: a big data analysis of self-reported consumption and objectively measured sleep.
Gahan et al., (2022). J Sleep Res, 31 (S1), P518.
Assessing The Impact Of Race And Income On Changes In Self-reported Sleep Quality During The COVID-19 Pandemic.
Burke et al., (2022). J Sleep Res, 31 (S1), P519.
A Long Winter’s Sleep: What Does Big Data From Consumer Sleep Technology Tell Us?
Gahan et al., (2023). SLEEP, 46 (S1), A419–A420.
A Long Winter’s Sleep: What Does Big Data From Consumer Sleep Technology Tell Us?
Gahan et al., (2023). SLEEP, 46 (S1), A419–A420.
Increased Engagement with a Tailored Sleep Guide is Associated with Reduced Variability in Sleep Efficiency in Chronic Insomnia.
Fanson et al., (2023). SLEEP, 46 (S1), A166–A167.
Social Jetlag Decreases Across The Lifespan: A Prospective Big Data Analysis Of Objective Sleep Metrics.
Gottlieb et al., (2025). Journal of Sleep Research, e14433.
Sleep staging monitoring based on sonar smartphone technology.
Zaffaroni et al., (2019). IEEE Eng Med Biol Soc, 2230-2233.
Contactless sleep apnea detection on smartphones.
Nandakumar et al., (2015). MobiSys, 45-57.