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A Proposal for Cardiac Arrhythmia Classification using Complexity MeasuresAROTARITEI, D.   , COSTIN, H. , PASARICA, A. , ROTARIU, C. |
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Author keywords
complexity theory, decision trees, electrocardiography, random sequences, classification algorithms, fuzzy set
References keywords
classification(13), arrhythmia(13), systems(8), fuzzy(7), cardiac(7), biomedical(6), applications(6), analysis(6), algorithm(6), neural(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2017-08-31
Volume 17, Issue 3, Year 2017, On page(s): 29 - 34
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.03004
Web of Science Accession Number: 000410369500004
SCOPUS ID: 85028535223
Abstract
Cardiovascular diseases are one of the major problems of humanity and therefore one of their component, arrhythmia detection and classification drawn an increased attention worldwide. The presence of randomness in discrete time series, like those arising in electrophysiology, is firmly connected with computational complexity measure. This connection can be used, for instance, in the analysis of RR-intervals of electrocardiographic (ECG) signal, coded as binary string, to detect and classify arrhythmia. Our approach uses three algorithms (Lempel-Ziv, Sample Entropy and T-Code) to compute the information complexity applied and a classification tree to detect 13 types of arrhythmia with encouraging results. To overcome the computational effort required for complexity calculus, a cloud computing solution with executable code deployment is also proposed. |
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.