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STTR Phase I: Ambulatory, Beat-to-Beat Blood Pressure Tracking Enabled by Wireless, Tri-Mode Electronic Tattoos

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 1938254
Agency Tracking Number: 1938254
Amount: $224,876.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: MD
Solicitation Number: N/A
Timeline
Solicitation Year: 2019
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-03-15
Award End Date (Contract End Date): 2020-11-30
Small Business Information
6506 HILLSIDE HOLLOW DR
AUSTIN, TX 78750
United States
DUNS: 079593520
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Pulin Wang
 (617) 792-5818
 pwang.wang22@gmail.com
Business Contact
 Pulin Wang
Phone: (617) 792-5818
Email: pwang.wang22@gmail.com
Research Institution
 University of Texas at Austin
 Nanshu Lu
 
3925 W Braker Lane, Ste 3.340
Austin, TX 78759
United States

 Nonprofit College or University
Abstract

The broader impact of this Small Business Technology Transfer (STTR) Phase I project is to address hypertension, which affects about 75 million Americans and is the primary or contributing cause of nearly 500,000 deaths every year in the U.S. A high-fidelity and high wearability blood pressure (BP) tracker will help the diagnosis and control of hypertension. The proposed project Advance the design and manufacture of wear-and-forget e-tattoos, a stretchable hybrid electronic device integrating both rigid and soft components on a tattoo-like platform, serving as a model for future soft wearable electronics. In addition to the societal impact of improving the lives of hypertension patients, noninvasive imperceptible real-time BP monitoring would assist many fields related to human health and performance, such as fitness training, sleep studies, and clinical trials for prospective therapeutic treatments. The proposed STTR Phase I project will develop an electro-mechanical-acoustic cardiac (EMAC) tattoo for continuous and beat-to-beat blood pressure (BP) tracking. The project will develop: 1) A combined hardware and software strategy for motion artifact minimization, long sought for any ambulatory biometrics sensing; and 2) A machine learning algorithm for personalized recognition and warning of abnormal BP events; 3) An integrated systems solution. These innovations together enable the first ambulatory, beat-to-beat ambulatory BP tracking system with high wearability, low motion artifacts, and warning capabilities in an e-tattoo wearable format. 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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