Analysis of the degree of multifractality of various components of electroencephalograms in cardiovascular pathology

Authors

DOI:

https://doi.org/10.33910/2687-1270-2022-3-4-463-473

Keywords:

cardiovascular pathology, atrial fibrillation, EEG frequency components, fractal and oscillatory spectrum components, degree of multifractality

Abstract

The article discusses the application of autospectral analysis with irregular resampling and multifractal analysis based on the search for the maxima of wavelet coefficient modules for detecting changes in the patterns of electrical activity of the human brain in cardiovascular pathology associated with permanent atrial fibrillation compared with the patterns of a healthy person. The article describes possible applications of these methods in quantitative assessment of differences in the dynamics of successive values in the analyzed patterns. This may be useful in diagnosing pathological changes in the functional state of the nervous system under heart rhythm disturbances. The analyzed patterns of electroencephalograms are decomposed into three components corresponding to theta, alpha and beta ranges. Both methods confirm the multifractality of all three studied components. The main differences in the multifractal properties of the healthy brain and the brain with heart rhythm disturbances are found in the alpha and theta components of the EEG. These components are characterized by exceptionally long correlations for the control group for the alpha component, the correlated and anticorrelated dynamics for the group with atrial fibrillation for the same component, and the anticorrelated dynamics for theta components.

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Published

2022-12-30

Issue

Vol. 3 No. 4 (2022)

Section

Experimental articles

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