Heart sound segmentation algorithm based on high-order Shannon entropy

The algorithm based on Shannon energy is improved for robust segmentation of heart sound with murmurs. First, the heart sound signal is preprocessed by wavelet to eliminate background noises and high-frequency murmurs. Then, the high-order Shannon entropy of signal is calculated as envelope to overcome the interference of low-frequency murmurs. Finally, the envelope is segmented into four parts: the first heart sound, the systolic period, the second heart sound, and the diastolic period according to physiology knowledge; and the accurate boundaries of the segmentation are detected. The algorithm was tested using normal and abnormal clinical data. The results show that the correct ratio of the algorithm is over 96%.