SBIR Phase I: Voice-based telehealth interface for symptom monitoring and screening for chronic and acute respiratory diseases, including COVID-19
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: 2032220
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$255,984Funder
National Science Foundation (NSF)Principal Investigator
Satya VennetiResearch Location
United States of AmericaLead Research Institution
DEEPCONVO INCResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Diagnostics
Special Interest Tags
Digital Health
Study Type
Non-Clinical
Clinical Trial Details
Not applicable
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 I project is a novel smartphone-based method for symptom monitoring and screening for chronic and acute respiratory diseases, including COVID-19. Current methods of evaluating respiratory diseases are not easily accessible or do not scale to screen large populations. The proposed technology will enable detection and monitoring of respiratory diseases to anyone with access to an internet-connected microphone (e.g., smartphone), using voice as an indicator. The technology will administer simple tests in minutes and deliver results in seconds, without requiring specialized user training. The anticipated outcome is a widespread, real-time screening, monitoring and exacerbation warning system that remotely analyzes voice signals for patients with chronic and acute respiratory diseases, including COVID-19.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop voice-based classifiers that diagnose COVID-19 and monitor the severity of the disease. Existing algorithms that detect vocal biomarkers in breath and speech indicative of lung function and respiratory disease will be extended to incorporate COVID-19 signatures. Audio recordings from patients receiving a positive COVID-19 test will be collected to extract micro -signatures and develop algorithms to automatically recognize and map patterns to clinical findings and reported symptoms. The research objectives include developing: (1) A binary classifier that differentiates symptomatic and asymptomatic patients; (2) A multi-class classifier that correlates (in future predicts) changes in the severity of a patient?s symptoms when provided a series of voice samples (3) Developing a dashboard for physicians that provides up to date reports and visualizations of the cross sectional and longitudinal analytics (4) An API giving lung function metrics and classifiers available for integration into 3rd party IT infrastructure.
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.
This Small Business Innovation Research (SBIR) Phase I project seeks to develop voice-based classifiers that diagnose COVID-19 and monitor the severity of the disease. Existing algorithms that detect vocal biomarkers in breath and speech indicative of lung function and respiratory disease will be extended to incorporate COVID-19 signatures. Audio recordings from patients receiving a positive COVID-19 test will be collected to extract micro -signatures and develop algorithms to automatically recognize and map patterns to clinical findings and reported symptoms. The research objectives include developing: (1) A binary classifier that differentiates symptomatic and asymptomatic patients; (2) A multi-class classifier that correlates (in future predicts) changes in the severity of a patient?s symptoms when provided a series of voice samples (3) Developing a dashboard for physicians that provides up to date reports and visualizations of the cross sectional and longitudinal analytics (4) An API giving lung function metrics and classifiers available for integration into 3rd party IT infrastructure.
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.