Novel PCG Analysis Method for Discriminating Between Abnormal and Normal Heart Sounds |
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| Affiliation: | 1. Intelligent Biometric Group, School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia;2. Department of Computer Programming, Faculty of Education–Shabwa, University of Aden, Shabwa, Republic of Yemen;1. Department of Computer Technology, Fırat University, Elazığ, Turkey;2. Department of Computer Engineering, Faculty of Engineering, Fırat University, Elazığ, Turkey;3. Department of Software Engineering, Faculty of Engineering, Samsun University, Samsun, Turkey;4. Department of Software Engineering, Faculty of Engineering, Fırat University, Elazığ, Turkey;1. The ENSAIT Textile Institute, Roubaix, France;2. INSERM CIC-IT 1403, Maison Régionale de la Recherche Clinique, CHRU de Lille, Lille, France |
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| Abstract: | A novel approach for separation among normal and heart murmurs sounds based on Phonocardiogram (PCG) analysis is introduced in this paper. The purpose of this work is to find the appropriate algorithm able to detect heart failures. Different features have been extracted from time and frequency domains. After the normalization step, the Principal Component Analysis algorithm is used for data reduction and compression. Support Vectors Machine (SVM), and k-Nearest Neighbors (kNN) classifiers were used with different kernels and number of neighbors in the classification step. Simulation results obtained from different databases are compared. The developed system gave good results when applied to different datasets. The accuracy of 96%, and 100% for the first, and the second dataset respectively were obtained. The algorithm shows its effectiveness in separation between normal and pathological cases. |
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| Keywords: | Phonocardiogram Signal processing MFCC SVM k-NN Classification |
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