Cardiac auscultation analysis system with Neural Network and SVM technique

The system of this study is aimed to support doctors with an analyzed Cardiac auscultation. Extract the information from the heart sound signal obtained from stethoscope mobbed on the robot arm control is used in the further signal processing. Due to time consuming and accuracy, Support Vector Machine is introduced to replace Neural Network for better performance. With the proposed technique, the high classification performances were achieved 96.4% accuracy for classifying normal and abnormal heart sound while shortening the training time almost 300%. As the result, multi-classifier was introduced for advance development. This paper shows the comparison work between Neural Network and Support Vector Machine.