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首页> 外文期刊>IEEE Transactions on Biomedical Engineering >Extraction of spatio-temporal signatures from depth EEG seizure signals based on objective matching in warped vectorial observations
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Extraction of spatio-temporal signatures from depth EEG seizure signals based on objective matching in warped vectorial observations

机译:基于变形矢量观测中目标匹配的深度脑电信号发作信号时空特征提取

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摘要

In the field of epilepsy, the analysis of stereoelectroencephalographic (SEEG) signals recorded with depth electrodes provides major information on interactions between brain structures during seizures. A comprehensive methodology of comparing SEEG seizure recordings is presented. It proceeds in three steps: 1) segmentation of SEEG signals; 2) characterization and labeling of segments; and 3) comparison of observations coded as sequences of symbol vectors. The third step reports a vectorial extension of the Wagner and Fischer's algorithm to first, quantify similarities between observations and second, extract invariant sequences of events, referred to as spatio-temporal signatures. The study shows that two observations of nonequal duration can be matched by deforming the first one to optimally fit the second, under cost constraints. Results show that the methodology allows to exhibit signatures occurring during epileptic seizures and to point out different types of seizure patterns. The study brings objective results on reproducible interactions between brain structures during ictal periods and may help in the understanding of epileptogenic networks.
机译:在癫痫领域,用深度电极记录的立体脑电图(SEEG)信号分析为癫痫发作期间大脑结构之间的相互作用提供了重要信息。提出了比较SEEG癫痫发作记录的综合方法。它分为三个步骤:1)SEEG信号的分割; 2)段的表征和标记; 3)比较观察结果,将其编码为符号向量序列。第三步报告了Wagner和Fischer算法的向量扩展,以首先量化观察之间的相似性,其次,提取事件的不变序列,称为时空签名。研究表明,在成本约束下,可以通过使第一个观测值变形以最佳地适合第二个观测值来匹配两个不等长的观测值。结果表明,该方法可以显示癫痫发作期间的特征,并指出不同类型的癫痫发作模式。这项研究带来了在发作期大脑结构之间可重现相互作用的客观结果,可能有助于了解癫痫发生网络。

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