Classification of heart sound based on S-Transform and neural network

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Show simple item record H. M., Hadi Mohd Yusoff, Mashor, Prof. Madya Dr. Mohd Zubir, Suboh Mohamed Sapawi, Mohamed 2011-01-10T06:37:29Z 2011-01-10T06:37:29Z 2010-05-10
dc.identifier.citation p. 189-192 en_US
dc.identifier.isbn 978-1-4244-7167-6
dc.description Link to publisher's homepage at en_US
dc.description.abstract The skill of cardiac auscultatory is very important to physicians for accurate diagnosis of many heart diseases. However, it needs some training and experience to improve the skills of medical students in recognizing and distinguishing the primary symptoms of cardiac diseases based on the heart sound that heard. This paper presents a method for feature extraction and classification of heart sound signals. The S-Transform (ST) technique is used to extract the features of heart sound. Then, the features were applied as inputs to classifier. The Multilayer Perceptron Network has been used to classify heart sound cases. The performance of the technique has been evaluated using 250 cardiac periods of heart sound recorded from heart sound simulator. The result has shown over 98% correct classification which shows the method used is suitable to classify heart sound cases. en_US
dc.language.iso en en_US
dc.publisher Institute of Electrical and Electronics Engineers (IEEE) en_US
dc.relation.ispartofseries Proceedings of the 10th International Conference on Information Sciences, Signal Processing and their Applications (ISSPA) 2010 en_US
dc.subject Heart sound en_US
dc.subject MLP en_US
dc.subject Neural networks en_US
dc.subject Neural networks en_US
dc.subject S-Transform en_US
dc.subject Valvular heart disease en_US
dc.title Classification of heart sound based on S-Transform and neural network en_US
dc.type Working Paper en_US
dc.contributor.url en_US

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