Heart Murmur Classification with Feature Selection

Authors

Dinesh Kumar
Paulo de Carvalho
Manuel Antunes
Rui Pedro Paiva
Jorge Henriques

Abstract

Heart sounds entail crucial heart function information. In conditions of heart abnormalities, such as valve
dysfunctions and rapid blood flow, additional sounds are heard in regular heart sounds, which can be employed in pathology diagnosis. These additional sounds, or so-called murmurs, show different characteristics with respect to cardiovascular heart diseases, namely heart valve disorders. In this paper, we present a method of heart murmur classification composed by three basic steps: feature extraction, feature selection, and classification using a nonlinear classifier. A new set of 17 features extracted in the time, frequency and in the state space domain is suggested. The features applied for murmur classification are selected using the floating sequential forward method (SFFS). Using this approach, the original set of 17 features is reduced to 10 features. The classification results achieved using the proposed method are compared on a common database with the classification results obtained using the feature sets proposed
in two well-known state of the art methods for murmur classification. The achieved results suggest that the proposed method achieves slightly better results using a smaller feature set.

Conference

International Conference of the IEEE Engineering in Medicine and Biology Society - EMBC'2010, August 2010

Cited by

Year 2013 : 5 citations

Salama, Mostafa A., et al. "Rough set-based identification of heart valve diseases using heart sounds." Rough Sets and Intelligent Systems-Professor Zdzis?aw Pawlak in Memoriam. Springer Berlin Heidelberg, 2013. 475-491.

Hamdy, Ahmed, et al. "Cardiac disorders detection approach based on local transfer function classifier." Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on. IEEE, 2013.

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

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

Year 2012 : 1 citations

1. Mostafa A. Salama, Aboul Ella Hassanien, Jan Platos, Aly A. Fahmy and Vaclav Snasel (2012). “Rough Sets-Based Identification of Heart Valve Diseases Using Heart Sounds”, HYBRID ARTIFICIAL INTELLIGENT SYSTEMS Lecture Notes in Computer Science, 2012, Volume 7208/2012, 667-676.

Year 2011 : 1 citations

1. Mostafa A. Salama, Aboul Ella Hassanien, Aly A. Fahmy and Tai-hoon Kim (2011). “Heart Sound Feature Reduction Approach for Improving the Heart Valve Diseases Identification”, SIGNAL PROCESSING, IMAGE PROCESSING AND PATTERN RECOGNITION Communications in Computer and Information Science, 2011, Volume 260, 280-290.