STTR Phase I: Smart IoT Wearable for Remote Monitoring and Assessment of COVID-19 Patients (COVID-19)

  • Funded by National Science Foundation (NSF)
  • Total publications:2 publications

Grant number: 2030629

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2021
  • Known Financial Commitments (USD)

    $256,000
  • Funder

    National Science Foundation (NSF)
  • Principal Investigator

    Lloyd Emokpae
  • Research Location

    United States of America
  • Lead Research Institution

    LASARRUS CLINIC AND RESEARCH CENTER
  • Research Priority Alignment

    N/A
  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Supportive care, processes of care and management

  • Special Interest Tags

    Digital Health

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

The broader impact /commercial potential of this Small Business Technology Transfer (STTR) Phase I project will help COVID-19 patients with a lower burden to the medical system. This project will lead to a low-cost wearable internet of things (IoT) system to enable improved telemedicine. The collected data can be leveraged for public health purposes. The proposed project will develop telemedicine software tools using real-time physiological data from a wearable that is affordable, comfortable, non-invasive, washable, and reusable.

This STTR Phase I project will develop a risk stratification mechanism for patients who experience signs and symptoms suggestive of COVID-19 such as dry cough, shortness of breath, and a fever. Such type of lower respiratory tract illness could be managed at home without resorting to hospital admission. Our objectives include development of: 1) a multi-modality system for diagnosing illness conditions for COVID-19 and similar contiguous diseases; 2) a software telemedicine interface with algorithms that learn and assess the need for further hospitalization; 3) a pilot study.

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.

Publicationslinked via Europe PMC

Enabling effective breathing sound analysis for automated diagnosis of lung diseases.

A wearable multi-modal acoustic system for breathing analysis.