Heart Murmur Recognition and Segmentation by Complexity Signatures



Heart sound segmentation has been a challenge of investigation for several years in diagnosis and preventing of many cardiovascular diseases. Heart sound triggers warning in presence of disrored/diseases. However, murmur prevalence in heart sound is the most common abnormalities are heard in many heart disorders. This paper introduces an algorithm for heart murmur identification from the other heart sound components such as S1 and S2. The algorithm includes wavelet decomposition for multi-resolution support and features that are extracted using nonlinear signal processing technique. Under this technique, heart sound signal are transformed in phase space computing the important parameter delay dimension which facilitates visualization heart sound behavior and important features extraction such as complexity. The method has been tested with diverse lesions of heart murmur 91.09+-5:38% sensitivity and 95.25+-2:49% specificity have been achieved.


Cardiac sound processing; heart murmur


EMBC -2008, 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, August 2008

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Year 2013 : 3 citations

 Yu-han, Cheng, and Ma Yong. "A New Method of Vehicle Initiative Safety: Heart Sound Acquisition and Identification Technology." ICCGI 2013, The Eighth International Multi-Conference on Computing in the Global Information Technology. 2013.

 Liu Jia Jin, et al. "A low-cost intelligent mobile terminal heart sound acquisition system based on." (2013).

 Marascio, Giuseppe, and Pietro Amedeo Modesti. "Current trends and perspectives for automated screening of cardiac murmurs." Heart Asia 5.1 (2013): 213-218.

Year 2011 : 2 citations

 S. Yuenyong, A. Nishihara, W. Kongprawechnon, K. Tungpimolrut, "A framework for automatic heart sound analysis without segmentation", in Journal of BioMedical Engineering OnLine 2011, 10:13.

 K. Prasanga, A. M. Abeykoon, S. Prasad, “Auscultation based stethoscopic diagnostic device for cardiac murmur identification”, IEEE International Conference on Industrial Technology, 14-16 March, 2011, pp. 367-372

Year 2010 : 1 citations

 Abeykoon, A.H.S. ; Prasanga, D.K. ; Prasad, S. ; Perera, W. ; Perera, K. , "Knowledge on heart patients through stethoscopic cardiac murmur identification for E-healthcare", 8th International Conference on ICT and Knowledge Engineering, 2010, pp. 58 - 63