Technologies for Pattern Recognition of Late Potentials atrial: the formation of signs
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Abstract
The principles of atrial late potentials (ALP) patterns recognition are considered in the systems of high resolution electrocardiography (HR ECG). The features of ALP are formed on the basis of ECG wavelet-analysis algorithm. The numerical experiments with the ALP models and real ECG signals are conducted. Providing the maximum distance between the classes the diagnostic features of ALP features are chosen using detail coefficients of waveletdecomposition.
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References
S. Gracheva, G. Ivanova, and A. Syrkion, New methods of electrocardiography, Moscow: Technosphere, 2007, p. 552.
V. Kovalenko, Guide to Cardiology, Kyiv: Morion, 2008, p. 1404.
L. T. Malaya, A. I. Dyadyk, and A. E. Bagriy, “Pathogenesis of atrial fibrillation. Message 1”, Ukrainian therapeutic journal, vol. 4, no. 2, pp. 58–65, 2002.
J. Tu and R. Gonzalez, Principles of recognitioneducation, Moscow: Mir, 1978, p. 411.
V. Abakumov, O. Ribin, and J. Svatosh, Biomedical signals. Genesis, production, monitoring, Kiev: Nora-print, 2001, p. 516.
E. O. Ivanko, N. G. Ivanushkina, and Y. V. Prokopenko, “Modeling the processes of occurrence of excitation wave circulation inmyocardium”, Control systems and machines, no. 3, pp. 36–41, 2009.
M. Akay, Time Frequency and Wavelets in Biomedical Signal Processing, IEEE, 1997. DOI:10.1109/9780470546697
N. Smolentsev, Fundamentals of wavelet theory.Wavelets in MATLAB, Moscow: DMK Press, 2008, p. 448.
E. Ivanko, N. Ivanushkina, and Y. Cinecope, “Multilevel analysis of electrocardiograms to identify late atrial potentials”, Electronics and communications, no. 4-5, pp. 160–164, Jan. 2009.
