A proposed framework for processing heart sounds formalizes analytical stages to enable computer-assisted diagnosis and teaching of cardiac auscultation.
A formalized computational framework for analyzing heart sounds may assist in teaching cardiac auscultation and developing automated diagnostic tools.
Skilled cardiologists perform cardiac auscultation, acquiring and interpreting heart sounds, by implicitly carrying out a sequence of steps. These include discarding clinically irrelevant beats, selectively tuning in to particular frequencies and aggregating information across time to make a diagnosis. In this paper, we formalize a series of analytical stages for processing heart sounds, propose algorithms to enable computers to approximate these steps, and investigate the effectiveness of each step in extracting relevant information from actual patient data. Through such reasoning, we provide insight into the relative difficulty of the various tasks involved in the accurate interpretation of heart sounds. We also evaluate the contribution of each analytical stage in the overall assessment of patients. We expect our framework and associated software to be useful to educators wanting to teach cardiac auscultation, and to primary care physicians, who can benefit from presentation tools for computer-assisted diagnosis of cardiac disorders. Researchers may also employ the comprehensive processing provided by our framework to develop more powerful, fully automated auscultation applications.
Syed et al. (Wed,) conducted a other in Cardiac disorders. Framework for the analysis of acoustical cardiac signals was evaluated. A proposed framework for processing heart sounds formalizes analytical stages to enable computer-assisted diagnosis and teaching of cardiac auscultation.