Real-time Remote Asthma Monitoring Through Smartphone Voice Analysis

This study examines the impact of home-based monitoring of respiratory function in asthma patients via a smartphone-based vocal biomarker platform. Previous work from cross-sectional studies has indicated that brief voice samples, analyzed by machine learning models, can predict the presence of respiratory conditions (asthma, COPD, ILD, COVID-19 and persistent cough) with an accuracy of approximately 70%. The present study seeks to extend these findings to establish whether the same vocal biomarker models can accurately track changes in respiratory function in asthma patients, and whether this capability, when incorporated into a smartphone app similar to those used for home-based asthma management, can improve relative level of asthma control.