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Title: Multifractal properties of ECG patterns of patients suffering from congestive heart failure
Authors: Dutta, S. 
Keywords: Computational biology
Fluctuations (theory)
Nonlinear dynamics
Issue Date: Dec-2010
Citation: Dutta, S. (2010-12). Multifractal properties of ECG patterns of patients suffering from congestive heart failure. Journal of Statistical Mechanics: Theory and Experiment 2010 (12) : -. ScholarBank@NUS Repository.
Abstract: The multifractal properties of two-channel ECG patterns of patients suffering from severe congestive heart failure (New York Heart Association (NYHA) classes III-IV) are studied and are compared with those for normal healthy people using the multifractal detrended fluctuation analysis methodology. Ivanov et al (1999 Nature 399 461) have studied the multifractality of human heart rate dynamics using the wavelet transformation modulus maxima (WTMM) methodology. But it has been observed by several scientists that multifractal detrended fluctuation analysis (MFDFA) works better than the WTMM method in the detection of monofractal and multifractal characteristics of the data. Galaska et al (2008 Ann. Noninvasive Electrocardiol. 13 155) have observed that MFDFA is more sensitive compared to the WTMM method in the differentiation between multifractal properties of the heart rate in healthy subjects and patients with left ventricular systolic dysfunction. In the present work the variation of two parameters of the multifractal spectrum-its width W (related to the degree of multifractality) and the value of the Hölder exponent α0-for the healthy and congestive heart failure patients is studied. α0 is a measure of the degree of correlation. The degree of multifractality varies appreciably (85-90% C.L.) for the normal and the CHF sets for channel I. For channel II no significant change in the values is observed. The degree of correlation is found to be comparatively high for the normal healthy people compared to those suffering from CHF. © 2010 IOP Publishing Ltd and SISSA.
Source Title: Journal of Statistical Mechanics: Theory and Experiment
ISSN: 17425468
DOI: 10.1088/1742-5468/2010/12/P12021
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