SleepGuru: Personalized Sleep Planning System for Real-life Actionability and Negotiability

ACM Symposium on User Interface Software and Technology (UIST’22)

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Jungeun Lee, Sungnam Kim, Minki Cheon, Hyojin Ju, JaeEun Lee, Inseok Hwang



Widely-accepted sleep guidelines advise regular bedtimes and sleep hygiene. An individual’s adherence is often viewed as a matter of self-regulation and anti-procrastination. We pose a question from a different perspective: What if it comes to a matter of one’s social or professional duty that mandates irregular daily life, making it incompatible with the premise of standard guidelines? We propose SleepGuru, an individually actionable sleep planning system featuring one’s real-life compatibility and extended forecast. Adopting theories on sleep physiology, SleepGuru builds a personalized predictor on the progression of the user’s sleep pressure over a course of upcoming schedules and past activities sourced from her online calendar and wearable fitness tracker. Then, SleepGuru service provides individually actionable multi-day sleep schedules which respect the user’s inevitable real-life irregularities while regulating her week-long sleep pressure. We elaborate on the underlying physiological principles and mathematical models, followed by a 3-stage study and deployment. We develop a mobile user interface providing individual predictions and adjustability backed by cloud-side optimization. We deploy SleepGuru in-the-wild to 20 users for 8 weeks, where we found positive effects of SleepGuru in sleep quality, compliance rate, sleep efficiency, alertness, long-term followability, and so on.