The world is currently vastly underprepared to deal with viral pandemics such as COVID-19. Testing kits around the world are in short supply, and since symptoms are so similar to other common infections such as influenza and the common cold, short testing supplies means doctors will only administer tests to patients who fit very specific symptoms – leaving others in the dark as to whether they are infected. This causes an unknown number of people – many who may be infected, to potentially spread the virus to others. The world desperately needs a way to quantitatively triage individuals who are at high risk of carrying COVID-19 based on more than just their self-reported symptoms. In addition, those who are infected and are quarantining at home have no way of knowing how they are progressing in their recovery and/or if their symptoms are sufficient to warrant hospitalization (before it may be too late). All of this is true not just for COVID-19, but for any future viral infection that may take the world by storm. Thus, even if COVID-19 tests eventually become available in large quantities, the technology developed in this program will still be useful to help self-triage and self-monitor subjects in future viral outbreaks.

The purpose of this RAPID project is to research and develop wearable platform technology that can be used to monitor patients, in real time, to determine their likelihood of currently being infected, and if they are infected, how their recovery process is coming along. This will be accomplished via a hybrid wearable device that simultaneously monitors body temperature for fever detection, and respiration function for coughing and shortness of breath measures. Importantly, the technology to be researched and developed herein will be engineered from the ground up to be extremely low power, such that the device can be powered via energy harvesting means without a battery. Implemented with a small integrated circuit, a small sensor array, and ultra-efficient magnetic human body communication technology, the entire platform will be disposable and last for weeks. Recorded data will be wirelessly delivered to a smartphone/smartwatch app, which can collect data across a large and diverse user space for population health analysis. At scale, the device is expected to cost <$0.10 USD, and thus could be used not only in the United States, but across the developing world. By aggregating volunteered data in an anonymous format from many users, the developed app will have epidemiologic applications, and help to illustrate likely infection rates across local, national, and international geographies.

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.

Project Start
Project End
Budget Start
2020-05-15
Budget End
2021-04-30
Support Year
Fiscal Year
2020
Total Cost
$150,000
Indirect Cost
Name
University of California San Diego
Department
Type
DUNS #
City
La Jolla
State
CA
Country
United States
Zip Code
92093