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Authors: Farid Melgani 1 and Yakoub Bazi 2

Affiliations: 1 University of Trento, Italy ; 2 College of Engineering, Al Jouf University, Saudi Arabia

ISBN: 978-989-8111-18-0

Keyword(s): ECG classification, feature reduction, particle swarm optimization, support vector machine.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: In this paper, we propose a novel classification system for ECG signals based on particle swarm optimization (PSO). The main objective of this system is to optimize the performance of the support vector machine (SVM) classifier in terms of accuracy by automatically: i) searching for the best subset of features where to carry out the classification task; and ii) solving the SVM model selection issue. Experiments conducted on the basis of ECG data from the MIT-BIH arrhythmia database to classify five kinds of abnormal waveforms and normal beats confirm the effectiveness of the proposed PSO-SVM classification system.

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Paper citation in several formats:
Melgani F.; Bazi Y. and (2008). EVOLUTIONARY COMPUTATION APPROACH TO ECG SIGNAL CLASSIFICATION.In Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008) ISBN 978-989-8111-18-0, pages 19-24. DOI: 10.5220/0001060200190024

@conference{biosignals08,
author={Farid Melgani and Yakoub Bazi},
title={EVOLUTIONARY COMPUTATION APPROACH TO ECG SIGNAL CLASSIFICATION},
booktitle={Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)},
year={2008},
pages={19-24},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001060200190024},
isbn={978-989-8111-18-0},
}

TY - CONF

JO - Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2008)
TI - EVOLUTIONARY COMPUTATION APPROACH TO ECG SIGNAL CLASSIFICATION
SN - 978-989-8111-18-0
AU - Melgani, F.
AU - Bazi, Y.
PY - 2008
SP - 19
EP - 24
DO - 10.5220/0001060200190024

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