STTR Phase I: The use of wrist-worn devices and sensory stimulation for evaluating sleep

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to improve people's lives by creating the first wrist-based device that can reliably assess sleep quality. A large pool of undiagnosed patients and the growing population of the elderly point to a massive end-user market for sleep disorder diagnostics devices. The market is steadily increasing due to the visible tilt in preference from drugs to home care sleep tests that are more convenient and lack side effects. This trend is also due to improvements in consumer based sensor technology, limited number of technicians or specialized physicians, and long wait times. In accordance with these market needs, this project is designed to develop a system for assessing sleep at home in a patient friendly and easy to environment. This technology is expected to be especially attractive to elderly patients looking for alternatives to medications and traditional sleep disorder tests. Because the algorithm developed in this project will be tested and validated in a sleep laboratory, it will be accepted in both clinical and non-clinical setting. The proposed project is a research and development effort to create and test a new system for detecting sleep stages. Because poor sleep is common in modern society and has considerable consequences, including decreased work productivity/abilities, increased rate of accidents and traffic fatalities, and increased health care costs, there is a great need for a new system that can provide an ambulatory assessment of sleep quality under real-world conditions. Although there are many wrist-based devices on the market that are well-suited for measuring sleep in both home and clinical settings, none of these devices can currently allow reliable assessment of sleep quality. This project will develop a new algorithm for a wrist-based device that will detect sleep quality based on actigraphy, photoplethysomnography, and physiological responses to sensory stimulation. This research will apply a multi-modal approach to assess quality of sleep and advance the science of diagnosis and treatment of sleep disorders.