Interpretation of Heart Sound Signal through Automated Artifact-Free Segmentation

Abstract

Purpose: Digital recording of heart sounds commonly known as Phonocardiogram (PCG) signal, is a convenient primary diagnostic tool for analyzing condition of heart. Phonocardiogram aids physicians to visualize the acoustic energies that results from mechanical aspect of cardiac activity. PCG signal cycle segmentation is an essential processing step towards heart sound signal analysis. Sound artifacts due to inappropriate placement of stethoscope, body movement, cough etc. makes segmentation difficult. Artifact-free segmented heart sound cycles are convenient for physicians to interpret and it is also useful for computerized automated classification of abnormality. Methods: We have developed a framework which selects good quality heart sound subsequences which are artifact-free and reused the features involved in this processing in segmentation. In this work, we have used information contained in frequency subbands by decomposing the signal using Discrete Wavelet Packet Transform (DWPT). The algorithm identifies the parts of the signal where artifacts are prominent and it also detects major events in heart sound cycles. Results: The algorithm shows good results when tested on normal and five commonly occurring pathological heart sound signals. An average accuracy of 93.71% is registered for artifactfree subsequence selection process. The cycle segmentation algorithm gives an accuracy of 98.36%, 98.18% and 93.97% respectively for three databases used in the experiment. Conclusions: The work provides a solution for artifact-free segmentation of heart sound cycles to assist interpretation of heart sound by physicians in objective analysis through recording in a computer. It is also useful for development of an automated decision support system on heart sound abnormality.