Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/43948
Title: Automatic Classification of Normal and Abnormal PCG Recording Heart Sound Recording Using Fourier Transform
Authors: Yadav, Anjali
Dutta, Malay Kishore
Travieso González, Carlos Manuel 
Alonso, Jesus B. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Heart , Feature extraction , Phonocardiography , Band-pass filters , Cepstrum , Classification algorithms , Fourier transforms, Heart Sound , PCG , Signal Processing , Feature extraction , SVM
Issue Date: 2018
Journal: 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings
Conference: 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 
Abstract: Cardiovascular diseases are very common these days and there arises a need for regular diagnosis of humans. Phonocardiogram is an effective diagnostic tool for analysing the heart sound. It helps in providing better information regarding clinical condition of the heart. This paper proposes an algorithmic method for differentiating a normal heart sound from an abnormal one using the PCG sound data. Cepstrum analysis has been performed on both types of signals and features are extracted from the heart sound. The extracted features are trained and tested with the help of a support vector machine classifier. The proposed method has achieved an accuracy of 95% in correctly classifying a heart sound PCG signal as normal and abnormal.
URI: http://hdl.handle.net/10553/43948
ISBN: 9781538675069
DOI: 10.1109/IWOBI.2018.8464131
Source: 2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings (8464131)
Appears in Collections:Actas de congresos
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