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Vocal biomarkers correlate with FEV1 variations during methacholine challenge
Giovanni Paoletti1,2, Giovanni Costanzo2, Morena Merigo2
1Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.
Clinical and Translational Allergy
|March 28, 2025
Summary
This study shows a smartphone app can detect bronchoconstriction using vocal biomarkers, correlating with lung function changes. This technology aids asthma diagnosis and management.
Area of Science:
- Biomedical Engineering
- Respiratory Medicine
- Data Science
Background:
- Mobile health (mHealth) apps are valuable for asthma management and data collection.
- Investigating signal processing and machine learning for detecting airway caliber changes.
- Developing algorithms to identify vocal biomarkers and bronchoconstriction in airway hyperreactivity.
Purpose of the Study:
- To explore the feasibility of using signal processing and machine learning to detect airway caliber alterations.
- To develop a machine learning algorithm for identifying vocal biomarkers and detecting bronchoconstriction.
- To assess the association between vocal biomarkers and bronchial constriction in patients with airway hyperreactivity.
Main Methods:
- Explorative, observational, prospective, longitudinal study design.
- Recruitment of non-smoker adults with suspected asthma (May-September 2023).
- Respiratory sound recording via smartphone app during Methacholine Challenge Test (MCT), with vocal biomarker extraction and correlation to Forced Expiratory Volume in the first second (FEV1) changes.
Main Results:
- Forty-two subjects enrolled; exhalation vocal events showed highest correlation with FEV1.
- Individualized "personal" vocal features demonstrated high correlation, though no single feature was universally robust.
- All correlations were statistically significant, irrespective of MCT outcomes.
Conclusions:
- The app's algorithm effectively correlates specific vocal biomarkers with FEV1 variations during MCT.
- This technology can assist physicians in asthma diagnosis, exacerbation assessment, and therapy monitoring.
- The mHealth approach offers significant socio-economic potential and research utility due to its simplicity.
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