A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast algorithms for discrete and continuous wavelet transforms
IEEE Transactions on Information Theory - Part 2
Computers in Biology and Medicine
Computer method for perinatal screening of cardiac murmur using fetal phonocardiography
Computers in Biology and Medicine
Automatic phonocardiograph signal analysis for detecting heart valve disorders
Expert Systems with Applications: An International Journal
On the separation of heart sound components using a translated empirical mode decomposition
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
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This paper is concerned with the identification and automatic measure of the split in the second heart sound (S2) of the phonocardiogram signal (PCGs) for normal or pathological case. The second heart sound S2 consists of two acoustic components A2 and P2, the former is due to the closure of the aortic valve and the latter is due to the closure of the pulmonary valve. The aortic valve usually closes before the pulmonary valve, introducing a time delay known as ''split''. A automatic technique based on the discrete wavelet transform (DWT) and the continuous wavelet transform (CWT) is developed in this paper to measure the split of the second cardiac sound (S2) for the normal and pathological cases of the PCG signals. To quantify the splitting, the two components in S2 (i.e. A2 and P2) are identified and, the delay between the two components can be estimated. It is shown that the wavelet transform can provide best information and features of the split of S2 and the major components (A2 and P2) and consequently aid in medical diagnosis.