@article{Saghafi_Amirfattahi_Mansouri_Kazemi_2024, title={Automatic Segmentation of Heart Sounds (S1 & S2) Using Wavelet}, volume={3}, url={https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/automatic-segmentation-of-heart-sounds-s1-s2-using-wavelet/}, DOI={10.1234/mjee.v3i1.188}, abstractNote={In this paper a new method approach is proposed for automatic segmentation of heart sounds (S1, S2) based on wavelet transform. Unlike many other approaches, this method does not use ECG as reference for detection. The applied criterion for segmentation is based on a very important physiologic attribute of heart which is the difference between the pressure of heart valves while opening and closing which causes high frequency components in heart sound. The main idea in this paper is to extract detail and approximation wavelet coefficients of heart sound (PCG) to detect the heart cycle via the Shannon energy of coefficients and then segment S1 and S2. The results show the present algorithm is capable of accurate segmentation of 90% of first heart sounds (S1) and 88.9% of second heart sounds (S2).}, number={1}, journal={Majlesi Journal of Electrical Engineering}, publisher={OICC Press}, author={Saghafi, MohammadAli and Amirfattahi, Rasoul and Mansouri, Mojtaba and Kazemi, Mohsen}, year={2024}, month={Feb.}, keywords={Wavelet Transform, Detail and Approximation coefficients, S1 and S2 sounds., Phonocardiogram} }