Categorization of normal and abnormal heart ryhtms from phonocardiogram signals

The phonocardiogram is based on recording the mechanical sounds of the heart, especially the sounds of the heart valves, and subsequent analysis. It provides an objective assessment of the cardiovascular system, which is vital for human life. In this thesis, the classification and analysis of normal and abnormal heart sounds obtained from the PCG signal was investigated. The data was obtained from challenge 2016 Physio-net database which consisted of two groups; A and B. Phonocardiogram signals was first decomposed into S1, S2 and S4 waves. Then bursts in each wave were segmented, and average power and dominant frequency were calculated from the segments of these signals. A simple linear Bayesian classifier was used to categorize heart sounds. The average accuracy of group A and B was obtained as 61% and 48% respectively. It was observed that the method fails for group B. However, the result for A was promising.