Lullaby is a system designed to help users improve the quality of their sleep by monitoring environmental factors that disrupt sleep (currently light, sound, temperature, and motion) along with sleep quality itself (using commercial sleep trackers like the Fitbit) and providing feedback. To be practical for deployment into bedrooms, it is designed to be unobtrusive and inexpensive. It aims to respect users’ privacy in this sensitive context by providing them with the ability to selectively disable data collection and to review and delete collected data. Lullaby helps users identify relationships between sleep disruptions and environmental factors; in the future, we plan for Lullaby to give concrete recommendations for addressing identified sleep disruptors. Lullaby consists of four components: the sensor suite, the data collection computer, a sleep tracking device, and a tablet interface for control and feedback. We conducted evaluations of this technology, and the work was published at UbiComp 2012, where it was awarded Best Paper. Lullaby was funded by the UW Royalty Research Fund, Intel Labs Seattle, and an NSERC PhD fellowship.

People

Matthew Kay
Eun Kyoung Choe
Jesse Shepherd
Ben Greenstein
Nate Watson
Sunny Consolvo
Julie Kientz

Publication

• Kay, M., Choe, E. K., Shepherd, J., Greenstein, B., Watson, N., Consolvo, S., & Kientz, J. A. (2012, September). Lullaby: a capture & access system for understanding the sleep environment. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing (pp. 226-234). ACM.