Sbir phase II: voice-based telehealth interface for symptom monitoring and screening for chronic and acute respiratory diseases

This $999,994 cooperative agreement from the National Science Foundation under the Technology, Innovation, and Partnerships program will support Deepconvo Inc.'s development of voice-based telehealth products and services for respiratory disease monitoring and screening. Deepconvo will further develop its chronic obstructive pulmonary disease early exacerbation warning system to more accurately measure lung function deterioration through voice and breath data captured on mobile phones. Key objectives include improving algorithms for varied environments and diverse patient datasets; enhancing exacerbation prediction by training with true hospitalization outcomes; launching a direct-to-patient product to engage users and bridge communication between patients and providers; and testing with additional lung conditions. This award aims to advance biomedical technologies supporting the NSF's mission to solve national challenges through private sector partnerships.

Abstract

The broader impact/commercial potential of this small business innovation research (sbir) phase II project is a voice-based telehealth interface deployed on mobile devices for symptom monitoring and screening for respiratory diseases. This technology may improve the quality of respiratory care and could prevent costly hospitalizations by delivering monitoring and exacerbation warnings to healthcare providers and patients. Chronic and acute respiratory diseases affect over 70 million americans and 1 billion people globally. This technology may help improve patient outcomes and save on patient care costs. The proposed project will further develop the existing chronic obstructive respiratory disease (copd) early exacerbation warning system to measure the earliest deterioration in a patient?s respiratory system through voice and breath data captured through mobile phones. The research objectives include (1) productizing lung function measurement by improving algorithms for measuring lung function in varied real-world environments and on datasets reflective of the target population of patients with respiratory conditions in the US; (2) productizing exacerbation prediction by further training the proof-of-concept algorithm with true respiratory exacerbations resulting in hospitalizations, emergency department visits, and prescription of new or increased medication and treatments; (3) developing and launching a direct-to-patient product with the goals of learning how to most effectively engage the patient to drive usage, communicating effectively with the patient, and bridging the GAP between patient and provider to provide timely and effective interventions; and (4) exploring additional use cases by testing products with patients who suffer from varied lung diseases. 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.