%0 Journal Article
%T Wavelet Packet Entropy for Heart Murmurs Classification
%A Fatemeh Safara
%A Shyamala Doraisamy
%A Azreen Azman
%A Azrul Jantan
%A Sri Ranga
%J Advances in Bioinformatics
%D 2012
%I Hindawi Publishing Corporation
%R 10.1155/2012/327269
%X Heart murmurs are the first signs of cardiac valve disorders. Several studies have been conducted in recent years to automatically differentiate normal heart sounds, from heart sounds with murmurs using various types of audio features. Entropy was successfully used as a feature to distinguish different heart sounds. In this paper, new entropy was introduced to analyze heart sounds and the feasibility of using this entropy in classification of five types of heart sounds and murmurs was shown. The entropy was previously introduced to analyze mammograms. Four common murmurs were considered including aortic regurgitation, mitral regurgitation, aortic stenosis, and mitral stenosis. Wavelet packet transform was employed for heart sound analysis, and the entropy was calculated for deriving feature vectors. Five types of classification were performed to evaluate the discriminatory power of the generated features. The best results were achieved by BayesNet with 96.94% accuracy. The promising results substantiate the effectiveness of the proposed wavelet packet entropy for heart sounds classification. 1. Introduction Accurate and early diagnosis of cardiac diseases is of great importance which is possible through heart auscultation. It is the most common and widely recommended method to screen for structural abnormalities of the cardiovascular system. Detecting relevant characteristics and forming a diagnosis based on the sounds heard through a stethoscope, however, is a skill that can take years to be acquired and refine. The efficiency and accuracy of diagnosis based on heart sound auscultation can be improved considerably by using digital signal processing techniques to analyze phonocardiographic (PCG) signals [1¨C3]. Phonocardiography is the recording of sonic vibrations of heart and blood circulation. PCG signals can provide valuable information regarding the performance of heart valves, therefore it has a high potential for detecting various heart diseases [4, 5]. Two loudest heart sounds are the first and the second sounds, referred to as S1 and S2. The time interval between S1 and S2 is called systole and the time interval between S2 and next S1 is called diastole. Normal heart sounds are low-frequency transient signals produced by the heart valves while pathological heart sounds, such as heart murmurs, are high-frequency, noise-like sounds [6]. Heart murmurs are produced as a result of turbulence in blood flow through narrow cardiac valves or reflow through the atrioventricular valves. Congenital heart defects or acquired heart valve diseases are often
%U http://www.hindawi.com/journals/abi/2012/327269/