Segmentation of heart sounds using simplicity features and timing information

Automatic analysis of heart sounds aid physicians in the diagnosis of abnormal heart valve conditions. Segmentation, i.e. identification of first (S1) and second (S2) heart sounds, is the first step in the automatic analysis. In this work, we have proposed a segmentation method which uses energy-based and simplicity-based features computed from multi-level wavelet decomposition coefficients. This method utilizes timing information of S1 and S2 based on biomedical domain knowledge. Proposed method has been evaluated on several normal and abnormal heart sounds for identification of S1 and S2 and compared with windowed energy-based and simplicity-based approaches individually. The proposed method is an efficient and robust technique for identification and gating of S1 and S2, and yields better results than the above approaches.