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STTR Phase I: BedDot: A Contactless Sensor Device for Sleep Activity Monitoring

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 1940864
Agency Tracking Number: 1940864
Amount: $225,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: I
Solicitation Number: N/A
Solicitation Year: 2019
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-01-01
Award End Date (Contract End Date): 2020-12-31
Small Business Information
DUNS: 117073227
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Maria Valero
 (404) 935-1222
Business Contact
 Maria Valero
Phone: (404) 935-1222
Research Institution
 University of Georgia Research Foundation Inc
 Zion Tse
 150 Paul D. Coverdell Center
500 D.W. Brooks Drive
Athens, GA, 30602
 Nonprofit college or university
The broader impacts of this Small Business Technology Transfer (STTR) Phase I project include the technology advancement of smart sensing and the improvement of the quality of life and care of seniors, by providing real-time safety, activity and health monitoring during sleep; and sending alerts, reports and analysis to their loved ones and caregivers. The growth of this demographic segment, the reduction of family size, and increased mobility bring significant challenges to senior care. According to U.S. Census Bureau projections, the number of Americans 65 and older will increase to 55 million in 2022, and to 70 million by 2030; of this group, the population over 85 years of age is the fastest growing segment. Seniors and caregivers will benefit from the new sensor technology developed in this project, whether they live in their own homes or in assisted-living facilities, contributing to healthcare quality improvement and cost reduction. The advanced signal processing and machine learning techniques developed in this project will advance the field of data analytics and smart sensing. The proposed project is the first to develop a real-time contactless sleep monitoring device based on vibration sensing. The sensor will provide reliable monitoring of sleep activities and vital signs while placed under mattresses in various building environments. This project will mark the first attempt to develop a contactless blood pressure monitoring function. The advanced signal processing and machine learning algorithms will be refined and validated regarding vital sign estimation (heart rate, respiration rate, and blood pressure) and sleep activity recognition (entry/exit of the bed, movement, posture change). A key challenge of data analytics algorithm development is to self-adapt to changes in the physical and noise environment. Various algorithms and functions will be integrated into one device with a user-friendly graphic interface; then the product's advantages and limitations will be evaluated systematically in different relevant environments and compared with other devices. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

* Information listed above is at the time of submission. *

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