Volume 4, Issue 4, August 2016, Page: 27-36
Detection of Abnormality in Electrocardiogram (ECG) Signals Based on Katz’s and Higuchi’s Method Under Fractal Dimensions
Md. Mashiur Rahman, Department of EEE, Ahsanullah University of Science and Technolo
A. H. M. Zadidul Karim, Department of EEE, University of Asia Pacific, Dhaka, Bangladesh
Abdullah Al Mahmud, Department of EEE, University of Asia Pacific, Dhaka, Bangladesh
Salma Nazia Rahman, Department of EEE, University of Asia Pacific, Dhaka, Bangladesh
Received: Jul. 28, 2016;       Accepted: Aug. 9, 2016;       Published: Sep. 5, 2016
DOI: 10.11648/j.cbb.20160404.11      View  3387      Downloads  152
Abstract
Analysis process of electrocardiogram (ECG) is a major research interests in bio-medical signal processing. The reasons of this interest is the growth of cardiac health care activities all over the world and the rapid progress in digital computer technology which play an essential role to the detection of diseases at various stages from bio medical signals. The assessment process of diagnostic results for these bio medical signals heavily depends upon quantity, accuracy and speed. Computer based analysis is very useful in clinical therapy. In this Paper a method of analysis (ECG) signals using fractal features have been proposed and practical experiments have done to show that this method provides a good electronic diagnosis pattern for cardiac abnormality because it has been used by some specialist doctors to diagnose various types of diseases with accuracy. By the fact that ECG signals show a fractal patterns, it has been tried to find out a comparison between Katz’s and Higuchi’s method under fractal dimension (FD) of the ECG time series in a feature extraction phase. All ECG signals have been acquired from the Massachusetts Institute of Technology (MITBIH) arrhythmia database. The obtained results confirm the superiority of the Katz’s and Higuchi’s method to identify cardiac abnormality as compared to traditional one which is analyses of ECG signals based on morphology features and three ECG temporal features.(i.e. the QRS complex duration, the RR interval and the RR interval averaged over the ten last beats).
Keywords
ECG, Katz’s Method, Higuchi’s Method, Fractal Features, Heart
To cite this article
Md. Mashiur Rahman, A. H. M. Zadidul Karim, Abdullah Al Mahmud, Salma Nazia Rahman, Detection of Abnormality in Electrocardiogram (ECG) Signals Based on Katz’s and Higuchi’s Method Under Fractal Dimensions, Computational Biology and Bioinformatics. Vol. 4, No. 4, 2016, pp. 27-36. doi: 10.11648/j.cbb.20160404.11
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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