Skip to main navigation Skip to search Skip to main content

I-Corps: Mobile Phone Based Vital Sign Detection

Project: Research

Abstract & Details

Description

Award ID: 2138673

The broader impact/commercial potential of this I-Corps project involves the development of an accessible, evidence-based, biofeedback intervention to allow individuals suffering with mental health disorders to have immediate access to effective treatment. A first use case is for the approximately 11% of Americans who experience reoccurring panic attacks, which has significant societal cost such that these individuals are more likely to visit emergency rooms, miss work, and experience subsequent comorbidity. This segment of the population currently has limited access to evidence-based treatment due to long therapy waitlists and often ineffective offerings. The proposed digital therapeutic technology aims to answer this unmet need by providing immediate, inexpensive, evidence-based intervention available on a smartphone. Advances made with this technology could be expanded to also inform biofeedback intervention for other mental health problems including general anxiety, post-traumatic stress disorder, substance abuse disorders, and even chronic pain. This I-Corps project develops new approaches for characterizing physiological states from mobile phone videoes and delivering personalized therapies where and when they are most needed. The novel computational algorithms leverage machine learning to enable accurate estimations of physiological signals that are robust to imperfect data quality inherent in measurements made during daily life. The technology may also be feasible for use during episodes of high emotional reactivity. This project builds on innovations in the clinical measurement and intervention by integrating algorithms into a mobile application, using it to collect datasets of real-world suffering and to inform personalized interventions. The feasibility of the tool has been demonstrated as a digital therapeutic for panic attacks. This project will explore the commercialization potential of this approach. 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.

NSF Program Director: Ruth Shuman
StatusClosed
Effective start/end date07/15/2112/31/22

Funding

  • I-Corps Teams: $50,000.00

Active Fiscal Year

  • FY2023
  • FY2022

Start Fiscal Year

  • FY2021

TIP Programs

  • I-Corps Teams

Key Technology Areas

  • Artificial Intelligence
  • (confidence score: 99%)

Technology Foci

  • Artificial Intelligence (Broad)
  • (confidence score: 100%)

Congressional District at Award

  • District n. 00 of Vermont

Current Congressional District

  • District n. 00 of Vermont

United States

  • Vermont

Core Based Statistical Area (CBSA)

  • Burlington-South Burlington, VT

County

  • County: Chittenden, VT

EPSCoR Jurisdiction

  • Yes

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine