## 2 Background
These murmurs sounds and clicks are a key points to identify cardiovascular disease [7]. Murmurs in the heart sound can be discovered using stethoscope, echocardiography or phonocardiography. Murmurs are classified as continuous murmurs, systolic murmurs and diastolic murmurs. Systolic murmurs are present during systole and they are generated during the ventricles contraction (ventricular ejection). In the heart sound component they are present between S1 and S2 hence are called as systolic murmurs. Based on their types, these systolic murmurs can be called as either ejection murmurs (atrial septal defect, pulmonary stenosis, or aortic stenosis) Figure 1e, or regurgitant murmurs (ventricular septal defect, tricuspid regurgitation, mitral regurgitation or mitral valve prolapse) Figure 1c. Diastolic murmurs are created during diastole (after systole), when the ventricles relax. Diastolic murmurs are present between the second and first heart sound portion, this type of murmur is usually due to mitral stenosis (MS) or aortic regurgitation (AR) by as shown in Figure 1d. Mitral valve prolapse (MVP) is a disease where the murmur sound is present in between the systole section as shown in Figure 1b. The murmur of AR is high pitched and the murmur of AS is low pitched. In mitral regurgitation (MR), systolic component S1 is either soft or buried or absent, and the diastolic component S2 is widely split. In mitral stenosis, the murmur is low pitched and rumbling and is present along the diastolic component. In mitral valve prolapse, the murmur can be found throughout S1 compment. The sound signal of VSD and MR are mostly alike [2; 7]. Summarizing the above discussion, we can see that heart sound signal can be acquired using and electronic stethoscope, in each complete cycle of heart sound signal we have S1-S4 intervals, S3 and S4 are rare heart sounds and are not normally audible but can be shown on the graphical recording i.e., phonocardiogram [4]. S3 and S4 intervals are called murmur sound and the heart sound signal which carries murmurs are called abnormal heart sounds and can be classified according to murmur position in the signal. In this study automatic classification of heart sound signal is carried out using five categories, one normal category and four abnormal categories. These abnormal categories are aortic stenosis (AS), mitral regurgitation (MR), mitral stenosis (MS) and MVP (murmur exist in the systole interval). Figure 1 shows graphical representation of theses heart sound signals categorically. The classification of heart sound signal can be carried out by several machine learning classifiers available for biomedical signal processing. One of them is SVM which can be used for classification of heart sounds. SVM is machine learning, classification and recognition technique that totally works on statistical learning and theorems, the classification accuracy of SVM is much more efficient than conventional classification techniques [8]. Another classifier that recently gained attention is DNN, DNN acoustic models have high performance in speech processing as well as other bio medical signal processing [9]. In this paper, our study shows that these classifiers (SVM and DNN also centroid displacement based KNN) have good performance for heart sound signal classification. The performance of Convolutional Neural Network is optimized for image classification, so this method is not suitable for the feature set we used in this paper. We also used Recurrent Neural Network in the pilot test, but our DNN method showed better results [10; 11].