International Journal of Bioinformatics and Biomedical Engineering
Articles Information
International Journal of Bioinformatics and Biomedical Engineering, Vol.2, No.4, Jul. 2016, Pub. Date: Sep. 3, 2016
Identification of Abnormality in Electrocardiogram Using Fractal Dimension
Pages: 51-58 Views: 738 Downloads: 354
Authors
[01] Mishuk Mitra, Department of Electrical and Electronic Engineering, University of Asia Pacific (UAP), Dhaka, Bangladesh.
[02] A. H. M Zadidul Karim, Department of Electrical and Electronic Engineering, University of Asia Pacific (UAP), Dhaka, Bangladesh.
[03] Md. Abdullah Al Mahmud, Department of Electrical and Electronic Engineering, University of Asia Pacific (UAP), Dhaka, Bangladesh.
[04] Md. Mashiur Rahman, Department of Electrical and Electronic Engineering, Ahsanullah University of Science and Technology (AUST), Dhaka, Bangladesh.
Abstract
A technique of nonlinear analysis- the fractal analysis, is recently having its popularity to many researchers working on nonlinear data for which most mathematical models produce intractable solutions. The term “Fractals” is derived from the Latin wordfractus, the adjectival from offranger, or break. Fractals as a set of fine structure, enough irregularities to be described in traditional geometrical language and fractal dimension is greater than topological dimension. Fractal is a mathematical analysis for characterizing complexity of repeating geometrical patterns at various scale lengths. The analysis is mostly suitable for analyzing data with self-similarity (i.e., data do not depend on time scale). Due to the self-similarity in the Heart’s electrical conduction mechanism and self-affine behavior of heart rate (HR), fractal analysis can be used as an analyzer of HR time series data. The aim of this work is to analysis heart rate variability (HRV) by applying different method to calculate fractal dimension (FD) of instantaneous heart rate (IHR) derived from ECG. The behavioral change of FD will be analyzed with the variation of data length. Based on FD change, the classification of abnormalities are being tried to identify in ECG. These methods will be applied to a large class of long duration data sets and it is expected that the proposed technique will provide a better result by comparison with others to detect the abnormality of ECG signal.
Keywords
Fractus, Fractal Dimension (FD), Heart Rate Variability (HRV), Electrocardiogram (ECG), Instantaneous Heart Rate (IHR)
References
[01] https://en.wikipedia.org/wiki/Electrocardiography
[02] https://faculty.washington.edu/chudler/ap.html
[03] http://hyperphysics.phy-astr.gsu.edu/hbase/biology/actpot.html
[04] http://www.itaca.edu.es/cardiac-action-potential.htm
[05] http://www.j-circ.or.jp/english/sessions/reports/64th-ss/nerbonne-l1.htm
[06] http://www.bem.fi/book/06/06.htm
[07] http://www.wahl.org/fe/HTML_version/link/FE4W/c4.htm
[08] https://en.wikipedia.org/wiki/Fractal_dimension
[09] http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3459993/
[10] http://www.mathworks.com/help/signal/ug/psd-estimate-using-fft.html
[11] http://www.mathworks.com/help/matlab/examples/fft-for-spectral-analysis.html
[12] Mandelbrot BB, Van Ness JW. Fractional brownian motions, fractional noises and applications. SIAM Rev. 1968;10:422–437.
[13] Mandelbrot BB, Wallis JR. Noah, Joseph, and operational hydrology. Water Resour Res. 1968;4:909–918.
[14] Mandelbrot BB, Wallis JR. Some long-run properties of geophysical records. Water Resour Res. 1969;5:321–340.
[15] Mandelbrot BB, Wallis JR. Computer experiments with fractional Gaussian noises. Part 3, mathematical appendix. Water Resour Res. 1969;5:260–267.
[16] Mandelbrot BB, Wallis JR. Robustness of the rescaled range R/S in the measurement of noncyclic long run statistical dependence. Water Resour Res. 1969;5:967–988.
[17] Mandelbrot BB, Wallis JR. Computer experiments with fractional Gaussian noises. Part 2, rescaled ranges and spectra. Water Resour Res. 1969;5:242–259.
[18] Hurst HE. Long-term storage capacity of reservoirs. Trans AmerSocCivEngrs. 1951;116:770–808.
[19] Hurst HE, Black RP, Simaiki YM. Long-term Storage: An Experimental Study. Constable; London: 1965.
600 ATLANTIC AVE, BOSTON,
MA 02210, USA
+001-6179630233
AIS is an academia-oriented and non-commercial institute aiming at providing users with a way to quickly and easily get the academic and scientific information.
Copyright © 2014 - 2017 American Institute of Science except certain content provided by third parties.