COVID-19 is significantly more lethal in the elderly1 with the greatest risk in those cared for in long-term care facilities (LTCs) where mortality rates range from 19% to 72% worldwide. Monitoring COVID-19 infections in LTCs remains a particular challenging. The existing and a continued expected shortage of sufficient molecular COVID-19 testing coupled to false negative rates as high as 15% necessitates a critical need for new and complementary technologies that can surveil, alert, and track COVID-19 infections in this population. Our group are pioneers in the development of novel soft electronics. Our recent publication, supported by our active Phase I STTR, was published in Nature Biomedical Engineering detailing a next generation ultra-low profile, soft, and flexible sensor (ADAM) that continuously measures subtle acousto- mechanic signals generated by the body via an embedded high-frequency, 3-axis accelerometer in direct mechanical communication with the skin. The ADAM sensor communicates via Bluetooth with our custom mobile application for real time streaming as well as on sensor data storage enabling stand-alone operation. All data streams are cloud synchronized (HIPAA compliant). The highly novel soft, flexible nature allows for the ADAM sensor to be mountable on unusual locations of high information density. Specifically, we exploit the SN?the only location on the body where there is no dampening effect at the skin level with the intrathoracic cavity. This enables a SN- mounted ADAM sensor to capture heart rate (HR), respiratory rate (RR), temperature, physical activity (PA), swallow count, and talk time, along with additional novel respiratory biomarkers relevant to COVID-19. In this proposal, we propose to develop a new COVID-19 software package, machine learning enhancements to our cough algorithm, and validation in LTCs with both elderly patients and staff to evaluate usability, feasibility, and adherence. The high level of technology readiness with partner LTCs allows us to deploy efficiently to generate essential data for a future FDA Emergency Use Authorization. Our team of experts in engineering, dermatology, gerontology, and machine learning are highly qualified to develop this COVID-19 surveillance system that offers both commercial and clinical value with broad applicability to a wide range of other respiratory and chronic medical conditions after the pandemic subsides.

Public Health Relevance

COVID-19 is significantly more lethal in the elderly resident in long-term care facilities. The shortage of molecular COVID-19 testing necessitates a critical need for new and complementary technologies that can surveil, alert, and track COVID-19 infections in this population. Our recent publication, supported by this active Phase I STTR, was published in Nature Biomedical Engineering detailing a next generation ultra-low profile, soft, and flexible sensor (ADAM) that continuously measures heart rate (HR), respiratory rate (RR), temperature, physical activity (PA), swallow count, and talk time, along with additional novel respiratory biomarkers relevant to COVID-19 directly adapted to the elderly.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Small Business Technology Transfer (STTR) Grants - Phase I (R41)
Project #
3R41AG062023-02S1
Application #
10167884
Study Section
Program Officer
Salive, Marcel
Project Start
2018-09-30
Project End
2021-05-31
Budget Start
2020-09-01
Budget End
2021-05-31
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Sonica, LLC
Department
Type
DUNS #
081039857
City
Evanston
State
IL
Country
United States
Zip Code
60208