Heart sound segmentation is the process of identifying the various events like S1, S2, S3, S4, and murmurs present in the phonocardiogram (PCG) signal. In this paper, a heart sound segmentation algorithm for segmenting S1 and S2 heart sound which corresponds to the systolic and diastolic activity of the heart is presented. The proposed method is based on variational mode decomposition (VMD) algorithm. The recorded PCG is decomposed into various modes using VMD. A novel criterion is proposed to select an appropriate mode which is based on center frequency and relative energy. Then the Shannon entropy envelope of the selected mode is computed. S1 and S2 heart sound is segmented by applying dynamic threshold on the Shannon entropy envelope. The segmentation algorithm is tested on both available standard database (Physionet, Pascal, Michigan, and eGeneralMedical) and recorded signal. The simulation results demonstrate that the proposed method achieved the sensitivity, positive predictivity, and the accuracy of above 95% with detection error rate of below 6%. © 2017 IEEE.