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Representation of epileptic discharge dynamics in EEGs on the basis of multiscale correlative signal dynamics analysis

机译:基于多尺度相关信号动力学分析的脑电图癫痫放电动力学表现

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摘要

This paper presents the latest results in the application of developed multiscale correlative signal dynamics analysis to epileptic discharge investigations. The basic principle of the approach proposed is in detecting the epileptic discharge time intervals and controlling the signal dynamics in such intervals by means of some signal quasi-periodicity features. These features are determined by the structure of a measure of self-similarity calculated for different scales. The graphical temporal representation based on this measure is at the center of the discussion. Interpretations of typical epileptic discharge dynamics patterns in the representation proposed are put into practice; typical patterns are illustrated by experimental representation examples.
机译:本文介绍了已开发的多尺度相关信号动力学分析在癫痫放电研究中的最新结果。所提出的方法的基本原理是检测癫痫放电时间间隔并通过一些信号准周期性特征来控制这种间隔中的信号动态。这些特征由针对不同尺度计算的自相似性度量的结构决定。基于此度量的图形时间表示是讨论的重点。拟议表示中典型的癫痫放电动力学模式的解释已付诸实践;典型的模式通过实验表示示例进行说明。

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