Heart Sounds Classification for a Medical Diagnostic Assistance

Authors

  • Abdelhamid Bourouhou Research Laboratory in Electrical Engineering, Ecole Normale Supérieure de l'Enseignement Technique, Mohammed V University, Rabat.
  • Abdelilah Jilbab Research Laboratory in Electrical Engineering, Ecole Normale Supérieure de l'Enseignement Technique, Mohammed V University, Rabat.
  • Chafik Nacir Research Laboratory in Electrical Engineering, Ecole Normale Supérieure de l'Enseignement Technique, Mohammed V University, Rabat.
  • Ahmed Hammouch Research Laboratory in Electrical Engineering, Ecole Normale Supérieure de l'Enseignement Technique, Mohammed V University, Rabat.

DOI:

https://doi.org/10.3991/ijoe.v15i11.10804

Keywords:

Heart disease, PCG, supervised learning classifier, GLM, SVM, Physio-Net/CinC Challenge 2016

Abstract


In order to develop the assessment of phonocardiogram “PCG” signal for discrimination between two of people classes – individuals with heart disease and healthy one- we have adopted the database provided by "The PhysioNet/Computing in Cardilogy Challenge 2016", which contains records of heart sounds 'PCG '. This database is chosen in order to compare and validate our results with those already published. We subsequently extracted 20 features from each provided record. For classification, we used the Generalized Linear Model (GLM), and the Support Vector Machines (SVMs) with its different types of kernels (i.e.; Linear, polynomial and MLP). The best classification accuracy obtained was 88.25%, using the SVM classifier with an MLP kernel.

Author Biographies

Abdelhamid Bourouhou, Research Laboratory in Electrical Engineering, Ecole Normale Supérieure de l'Enseignement Technique, Mohammed V University, Rabat.

Abdelhamid BOUROUHOU was born in Rabat, Morocco on December 26th, 1989. Received the Master degree in Electrical Engineering from ENSET, Rabat Mohammed V University, Morocco, in 2014 he is a research student of Sciences and Technologies of the Engineer in ENSIAS, Research Laboratory in Electrical Engineering LRGE, Research Team in Computer and Telecommunication ERIT at ENSET, Mohammed V University, Rabat, Morocco. His interests are in sounds classification for medical diagnostic assistance.

Abdelilah Jilbab, Research Laboratory in Electrical Engineering, Ecole Normale Supérieure de l'Enseignement Technique, Mohammed V University, Rabat.

Abdelilah JILBAB Professor at ENSET Rabat, Morocco; he graduated in electronic and industrial computer aggregation in 1995. Since 2003, he is a member of the laboratory LRIT (Unit associated with the CNRST, FSR, Mohammed V University, Rabat, Morocco). He acquired his PhD in Computer and Telecommunication from Mohammed V-Agdal University, Rabat, Morocco in 2009. His domains of interest include signal processing and embedded systems.

Chafik Nacir, Research Laboratory in Electrical Engineering, Ecole Normale Supérieure de l'Enseignement Technique, Mohammed V University, Rabat.

Chafik NACIR 

Teacher Researcher in Mathematics.

Former Head of the Department of Mathematics and Computer Science.

Former member of the Scientific Commission ENSET of Rabat Morocco.

Ahmed Hammouch, Research Laboratory in Electrical Engineering, Ecole Normale Supérieure de l'Enseignement Technique, Mohammed V University, Rabat.

Ahmed HAMMOUCH received the master degree and the PhD in Automatic, Electrical, Electronic by the Haute Alsace University of Mulhouse (France) in 1993 and the PhD in Signal and Image Processing by the Mohammed V University of Rabat in 2004. From 1993 to 2013 he was a professor in the Mohammed V University in Morocco. Since 2009 he manages the Research Laboratory in Electronic Engineering. He is an author of several papers in international journals and conferences. His domains of interest include multimedia data processing and telecommunications. He is with National Center for Scientific and Technical Research in Rabat.

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Published

2019-07-16

How to Cite

Bourouhou, A., Jilbab, A., Nacir, C., & Hammouch, A. (2019). Heart Sounds Classification for a Medical Diagnostic Assistance. International Journal of Online and Biomedical Engineering (iJOE), 15(11), pp. 88–103. https://doi.org/10.3991/ijoe.v15i11.10804

Issue

Vol. 15 No. 11 (2019)

Section

Papers