Cumulant analysis in wavelet space for studying effects of aging on electrical activity of the brain

被引：7

作者：

Guyo, G. A. ^{[1
,2
]}

Pavlov, A. N. ^{[1
,2
]}

Pitsik, E. N. ^{[3
,4
]}

Frolov, N. S. ^{[3
,4
]}

Badarin, A. A. ^{[3
,4
]}

Grubov, V. V. ^{[3
,4
]}

Pavlova, O. N. ^{[1
]}

Hramov, A. E. ^{[3
,4
]}

机构：

[1] Saratov NG Chernyshevskii State Univ, Astrakhanskaya Str 83, Saratov 410012, Russia

[2] Reg Sci & Educ Math Ctr Math Future Technol, Saratov 410012, Russia

[3] Innopolis Univ, Univ Skaya Str 1, Innopolis 420500, Russia

[4] Immanuel Kant Baltic Fed Univ, Kaliningrad 236041, Russia

来源：

CHAOS SOLITONS & FRACTALS | 2022年 / 158卷

基金：

俄罗斯基础研究基金会; 中国国家自然科学基金; 俄罗斯科学基金会;

关键词：

Wavelet; Signal processing; Cumulant analysis; EEG; Aging effects; ALZHEIMERS-DISEASE; FUNCTIONAL CONNECTIVITY; COMPENSATORY MECHANISMS; BEHAVIORAL VARIANT; DECOMPOSITION; PERFORMANCE; NETWORKS; WHITE;

D O I：

10.1016/j.chaos.2022.112038

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Multiresolution wavelet analysis with thorough processing of decomposition coefficients using a set of cumulants is proposed as a way to improve the characterization of complex dynamics based on experimental data. The application of this approach for quantification the effects of aging in the responses of the electrical activity of the brain to fine motor tasks (clenching the fist) is considered. It is shown that young and elderly adults have significant differences in reactions to this type of movements carried out by the dominant and nondominant hand. The characterization of inter-group distinctions using the skewness and kurtosis of the probability distribution of the wavelet decomposition coefficients outperforms the diagnostics of age-related differences based on standard deviation of this distribution. (C) 2022 Elsevier Ltd. All rights reserved.

引用

页数：5

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