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EN
In this paper multivariate spontaneous EEG signals from three broad groups of human subjects - control, seizure, and mania - were studied with the aim of investigating the possible effect of these pathologies on the degree of phase synchronization between cortical areas. The degree of phase synchrony was measured by two recently developed measures which are more suitable than classical indices like correlation or coherence when dealing with nonlinear and non-stationary signals like the EEG. Signals were reduced to seven frequency bands (delta, theta, alpha-1, alpha-2, beta-1, beta-2 and gamma) which were statistically compared between the normal and the other two groups. It was found that the degree of long-range synchrony was significantly reduced for both pathological groups as compared with the control group. No clear differences were found in the degrees of short-range synchrony.
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Complexity analysis of spontaneous EEG

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EN
The aim of the present paper is the assessment of the overall complexity of spontaneous and non-paroxysmal EEG signals obtained from three groups of human subjects, e.g., healthy, seizure and mania. Linear complexity measure suitable for multi-variate signals, along with nonlinear measures such as approximate entropy (ApEn) and Taken?s estimator are considered. The degree of linear complexity is significantly reduced for the pathological groups compared with healthy group. The nonlinear measures of complexity are significantly decreased in the seizure group for most of the electrodes, whereas a distinct discrimination between the maniac and healthy groups based on these nonlinear measures is not evident.
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