Classification of voluntary cough sound and airflow patterns for detecting abnormal pulmonary function
Ayman A Abaza1,2, Jeremy B Day1,2, Jeffrey S Reynolds1,2
1National Institute for Occupational Safety and Health, Health Effects Laboratory Division, Pathology and Physiology Research Branch, 1095 Willowdale Road, Morgantown, West Virginia, USA.
Cough (London, England)
|November 26, 2009
Summary
Analyzing voluntary cough airflow and sound can accurately detect lung disease. This novel system achieves high classification performance, aiding in diagnosing respiratory conditions.
Area of Science:
- Pulmonology
- Biomedical Engineering
- Signal Processing
Background:
- Involuntary cough is a key symptom in many respiratory diseases.
- Coughing clears airways but also causes physiological stress.
- Voluntary cough analysis can be a valuable diagnostic tool.
Purpose of the Study:
- To assess if voluntary cough airflow and acoustic characteristics can differentiate between healthy individuals and those with lung disorders.
- To develop an automated system for classifying lung function based on cough analysis.
Main Methods:
- Fifty-two healthy subjects and sixty subjects with lung disorders performed voluntary coughs.
- Airflow and acoustic features were extracted from cough sounds.
- A classifier using principal component analysis (PCA) reconstruction was applied.
Main Results:
- The system achieved 94% (female) and 97% (male) overall classification accuracy for abnormal lung physiology.
- Receiver Operating Characteristic (ROC) analysis demonstrated 98% sensitivity and 98% specificity for both groups.
Conclusions:
- A novel automated system for cough classification has been developed.
- This system accurately detects abnormal lung function using combined airflow and acoustic cough properties.
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