Multiscale entropy analysis of EEG from patients under different pathological conditions

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Multiscale sample entropy (MSE) of human electroencephalogram (EEG) data from patients under different pathological conditions of Alzheimer's disease (AD) was evaluated to measure the complexity of the signal. Quantifying the complexity level with respect to various temporal scales, MSE analysis provides a dynamical description of AD development. When compared to EEG data from normal subjects, EEG data from subjects with mild cognitive impairment (MCI) showed nearly the same complexity profile, but a scale discrepancy which may occur from a spectral abnormality. EEG data from severe AD patients showed a loss of complexity over the wide range of time scales, indicating a destruction of nonlinear structures in brain dynamics. We compare the MSE method and spectral analysis to propose that nonlinear dynamical approach combining a multiscale method is crucial for revealing AD mechanisms.
Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
Issue Date
2007-12
Language
English
Article Type
Article
Keywords

ALZHEIMERS-DISEASE; TIME-SERIES; DYNAMICS; COMPLEXITY; IMPAIRMENT

Citation

FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY, v.15, pp.399 - 404

ISSN
0218-348X
URI
http://hdl.handle.net/10203/92077
Appears in Collection
PH-Journal Papers(저널논문)
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