Document Detail

Heart murmur recognition and segmentation by complexity signatures.
MedLine Citation:
PMID:  19163117     Owner:  NLM     Status:  MEDLINE    
Heart sound analysis has been a topic of investigation for several years. Since heart sounds directly encode the mechanical activity of the heart, they enable the assessment and follow-up of several types of heart disorders in pre-symptomatic states. Murmurs are the most common abnormality signature in many heart disorders. This paper introduces an algorithm for heart murmur identification. In the presence of murmurs, heart sounds exhibit chaotic behavior. In the proposed method this is assessed based upon the nonlinear dynamics of the signal. In order to segment murmurs from other heart sound components, the signal is transformed into a phase space that is later reconstructed using the embedded matrix. Based on the phase space, the complexity and the strength of the signal are computed. These features are the basis for sound component boundary location. The method has been tested with a database of heart sounds that include diverse heart lesions and heart murmurs. The algorithms achieved 91.09% sensitivity and 95.25% specificity.
D Kumar; P Carvalho; M Antunes; J Henriques; A Sá e Melo; J Habetha
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
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:  2008     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2008  
Date Detail:
Created Date:  2009-02-16     Completed Date:  2009-04-22     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:  2128-32     Citation Subset:  IM    
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MeSH Terms
Heart Murmurs / diagnosis*
Heart Sounds
Models, Cardiovascular*
Nonlinear Dynamics
Phonocardiography / methods
Sensitivity and Specificity
Signal Processing, Computer-Assisted*

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