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Detection and Classification of Heart Murmurs Using Neural Network
Abstract—Auscultation is the best method for detecting the cardiovascular problem, which is theone of the reason of people death in the world. Heart murmurs are the most common abnormalproblem whenapatients arevisitsthedoctorfor auscultation. These sounds of the heart are innocent, harmless or abnormal, which can be a symptom of serious heart disease. In this project, basic neural network tools are sing a neuron based network system. It used to differentiate people among healthy and disease susceptible patients. The heart sound recordings are collected and stored in the existing database. The different heart valve sounds are collected for the comparison and classification of Heart sound record from both healthy and pathological patients. It is having 300 heart sound recordings of length from 50 to 120 seconds. The first step of processing is to convert discrete values of audio file and then to divide the data samples using MATLAB tool. The multiple networks have been preparedwiththeheartmurmurinformationcontainedin heart beat recordings obtained from four different heart sound. These samples are segmented and preprocessed usingMATLAB.
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International Journal for Trends in Technology & Engineering © 2015 IJTET JOURNAL