Heart Sound Signals Segmentation and Multiclass Classification

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.v16i15.16817

Keywords:

Heart disease, Heart sounds classification PASCAL Challenge, Heart sounds segmentation, PCG signals analysis.

Abstract


The heart is the organ that pumps blood with oxygen and nutrients into all body organs by a rhythmic cycle overlapping between contraction and dilatation. This is done by producing an audible sound which we can hear using a stethoscope. Many are the causes affecting the normal function of this most vital organ. In this respect, the heart sound classification has become one of the diagnostic tools that allow the discrimination between patients and healthy people; this diagnosis is less painful, less costly and less time consuming. In this paper, we present a classification algorithm based on the extraction of 20 features from segmented phonocardiogram “PCG” signals. We applied four types of machine learning classifiers that are k- Near Neighbor “KNN”, Support Vector Machine “SVM”, Tree, and Naïve Bayes “NB” so as to train old features and predict the new entry. To make our results measurable, we have chosen the PASCAL Classifying Heart Sounds challenge, which is a rich database and is conducive to classifying the PCGs into four classes for dataset A and three classes for dataset B. The main finding is about 3.06 total precision of the dataset A and 2.37 of the dataset B.

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 sound 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 Ph.D. 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.

A 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's degree and the Ph.D. in Automatic, Electrical, Electronic by the Haute Alsace University of Mulhouse (France) in 1993 and the Ph.D. in Signal and Image Processing by the Mohammed V University of Rabat in 2004. From 1993 to 2013 he was a professor in 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 the National Center for Scientific and Technical Research in Rabat.

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Published

2020-12-15

How to Cite

Bourouhou, A., Jilbab, A., Nacir, C., & Hammouch, A. (2020). Heart Sound Signals Segmentation and Multiclass Classification. International Journal of Online and Biomedical Engineering (iJOE), 16(15), pp. 64–79. https://doi.org/10.3991/ijoe.v16i15.16817

Issue

Vol. 16 No. 15 (2020)

Section

Papers