Acoustic Features for the Identification of Coronary Artery Disease

Abstract

Goal: Earlier studies have documented that coronary artery disease (CAD) produces weak murmurs, which might be detected through analysis of heart sounds. An electronic stethoscope with a digital signal processing unit could be a low cost and easily applied method for diagnosis of CAD. The current study is a search for heart sound features which might identify CAD.

Methods: Nine different types of features from five overlapping frequency bands were obtained and analyzed using 435 recordings from 133 subjects.

Results: New features describing an increase in low-frequency power in CAD patients were identified. The features of the different types were relatively strongly correlated. Using a quadratic discriminant function, multiple features were combined into a CAD-score. The area under the receiving operating characteristic for the CAD score was 0.73 (95% CI: 0.69-0.78).

Conclusion: The result confirms that there is a potential in heart sounds for the diagnosis of CAD, but that further improvements are necessary to gain clinical relevance.