Automatic segmentation and detection of heart sound components S1, S2, S3 and S4

In this paper, we propose an automatic segmentation and detection of heart sound components (S1, S2, S3 and S4) which incorporates Empirical Mode Decomposition (EMD) denoising, autocorrelation-based cardiac cycle calculation, Shannon energy envelope extraction, first derivative peak and boundary detection, and real peak selection using Heron's formula. The proposed method is evaluated on synthetic data corrupted by white Gaussian noise. The simulation results show that the proposed method is able to segment and identify the heart sound component correctly from normal and abnormal heart sound data.