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Updated: Oct 14, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
Published on: July 22, 2025
[Research Progress of Breath Sound Analysis in Children with Bronchial Asthma]
1Graduate School of Tianjin Medical University,Tianjin 300070,China.
Insights
Early asthma detection is challenging due to subtle early symptoms. Respiratory sound analysis offers a promising new technology for long-term monitoring and automatic breathing detection, overcoming limitations of current methods.
Area of Science:
- Respiratory Medicine
- Biomedical Engineering
- Artificial Intelligence in Healthcare
Background:
- Bronchial asthma is a prevalent chronic respiratory condition.
- Early diagnosis of asthma is difficult as wheezing, a key symptom, appears late.
- Current diagnostic methods like pulmonary function tests have limitations, especially in young children.
Purpose of the Study:
- To review the research progress in respiratory sound analysis for asthma monitoring.
- To highlight the need for novel technologies in early asthma detection.
- To explore the potential of breath sound analysis in clinical practice.
Main Methods:
- Review of recent research on respiratory sound analysis techniques.
- Digital processing and conversion of collected respiratory sounds.
- Modeling the relationship between sound parameters and asthma.
Main Results:
- Breath sounds are closely linked to airway changes, providing reliable clinical information.
- Respiratory sound analysis can digitally process sounds to form characteristic signal parameters.
- This approach offers potential for long-term breath sound monitoring and automatic breathing detection.
Conclusions:
- Respiratory sound analysis is an emerging technology with significant potential for asthma management.
- This technology can overcome the limitations of traditional diagnostic methods.
- Further research in this area is recommended for clinical application.
Abstract:
Bronchial asthma is a common chronic respiratory disease,and its diagnosis is mainly based on symptoms,signs,and pulmonary function test.Wheezing is a major symptom of asthma attack,which shows no obvious sign in the early stage while appears after the disease has progressed.Therefore,bronchial asthma is difficult to be detected in early stages,which often leads to worsening of the disease conditions.Pulmonary function test can effectively monitor upper and lower airway abnormalities and is currently the main means for monitoring asthma.However,its accuracy is highly dependent on patient's motivation and cooperation,which obviously limits the scope of application,especially for preschoolers and infants.Hence,there is an urgent need for a new technology with the function of long-term breath sound monitoring and automatic breathing detection to overcome the existing clinical deficiencies.Breath sound analysis emerges in the era of medical artificial intelligence,which can digitally process and convert the collected respiratory sounds by using a variety of different methods to form characteristic signal parameters and model the relationship between parameters and diseases.As we know,breath sounds are closely related to airway changes,and thus the detection and analysis of the sounds can provide reliable clinical information for the progress and control evaluation of asthma.This review mainly summaries the research progress of respiratory sound analysis in recent years,hoping to provide reference for further research.
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