Document Detail


Classification of heart murmurs using cepstral features and support vector machines.
MedLine Citation:
PMID:  19964976     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Murmurs are auscultatory sounds produced by turbulent blood flow in and around the heart. These sounds usually signify an underlying cardiac pathology, which may include diseased valves or an abnormal passage of blood flow. The murmurs are classified based on their occurrence in different parts of the heart cycle; systolic murmurs and diastolic murmurs. This paper investigates features derived from cepstrum of the heart sound signals and use them to train three classifiers; k-nearest neighbor (kNN) classifier, multilayer perceptron (MLP) neural networks and support vector machines (SVM) for classification of heart sounds into normal, systolic murmurs and diastolic murmurs. These features have been compared with features extracted from short-term Fourier transform (STFT) and discrete wavelet transform (DWT) in combination with the above three classifiers. The classification experiments were carried out on the heart sounds samples collected from various web sources. Among various combinations of the above features and classifiers, SVM trained on cepstral features are most promising for murmur classification with an accuracy of around 95%.
Authors:
Jithendra Vepa
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  2009     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2009  
Date Detail:
Created Date:  2009-12-07     Completed Date:  2010-03-16     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2539-42     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Automation
Cardiology / instrumentation
Diagnosis, Computer-Assisted
Equipment Design
Fourier Analysis
Heart Auscultation
Heart Murmurs / physiopathology*
Heart Sounds
Heart Valve Diseases / diagnosis*,  physiopathology
Humans
Models, Statistical
Neural Networks (Computer)
Reproducibility of Results
Signal Processing, Computer-Assisted
Software

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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