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Detecting epileptic electroencephalogram by Recurrence Quantification Analysis

Authors: Xiangtao Yan; Siyuan Feng; Jiafei Dai; Jun Wang 0031;

Detecting epileptic electroencephalogram by Recurrence Quantification Analysis

Abstract

Aiming at studying the influences of epilepsy on brain's nonlinear characteristics, we analyzed the difference between the normal EEG (electroencephalogram) and epileptic EEG from the perspective of nonlinear dynamics. Two sets of data used in this paper, including 16 cases of normal EEG and the same quantity of epileptic EEG, were from General Hospital of Nanjing Military Region. Firstly, on the basis of the Recurrence Plot (RP), the Order Recurrence Plot (ORP) was adopted to analyze two different kinds of EEG qualitatively. Then Average Diagonal Length, a parameter coming from Recurrence Quantification Analysis (RQA), was calculated to analyze the difference between normal EEG and epileptic EEG in nonlinear character, quantitatively. Compared with the healthy control subjects, the epileptic EEG is more regular and more certain, meanwhile, it's Average Diagonal Length is longer. Epilepsy makes patients' EEG become weaker in nonlinear chaotic characteristics but stronger in regularity and certainty.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
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