SBIR Phase II: An AI-powered wearable system and platform for long-term remote monitoring of pulmonary function (COVID-19)

  • Funded by National Science Foundation (NSF)
  • Total publications:0 publications

Grant number: 2112096

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2021
    2023
  • Known Financial Commitments (USD)

    $958,275
  • Funder

    National Science Foundation (NSF)
  • Principal Investigator

    Maria Artunduaga
  • Research Location

    United States of America
  • Lead Research Institution

    Respira Labs Inc
  • 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 Innovation Research (SBIR) Phase II project is to improve care for pulmonary conditions, such as Chronic Obstructive Pulmonary Disease (COPD). This disease affects 30 million Americans, kills more than 150,000 a year and is the third leading cause of U.S. deaths. COPD costs Americans nearly $72 billion a year, half of which is spent on ER visits and hospital stays resulting from respiratory crises. Hospitalized COPD patients have reduced quality of life, more rapid lung disease progression, and a 50% increase in mortality in the subsequent two years. Currently, ongoing monitoring of COPD lung deterioration relies largely on patient-reported symptoms and inadequate tools (65-70% accurate). As a result, half of COPD deterioration remains undetected. The proposed technology facilitates early diagnosis and treatment of COPD attacks by continuous remote tracking of lung function, thereby preventing unnecessary ER visits and hospitalizations. This device improves care for long-term conditions like COPD or asthma, but also those with relatively quick onset, such as COVID-19.

The proposed project advances translation of a device using acoustic resonance to measure lung air volume. The project develops an expanded data set for analysis and deployment at scale. The project further incorporates advanced classification models into the analysis workflow to track and predict deteriorating lung function in a cloud-computing environment. The project will also develop a version to run on a patient's mobile device to enable real-time feedback.

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.