High-Fidelity Sensing of the Sleep Environment in the Homes of Older Adults

Info about the Project

Although it is well-established that the environment (e.g., sound, light, temperature) can be a significant contributor to sleep disruption, few technologies have been designed to capture the environmental factors that affect sleep. We developed a low-cost and robust sensor designed to collect highly accurate environmental light and sound data in a natural home environment at fine temporal resolution. We deploy these sensors in the bedrooms of older adults for an extended period to comprehensively describe the sleep environment and to uncover the metrics most salient for sleep disruption.
Faculty: 
Craig Zimring, Elizabeth Mynatt, David Anderson
Students: 
Nicolas Shu