脑电图归一化Gabor熵分析预测癫痫发作

Rui Liu, I. Vlachos, Bharat Karumuri, J. Adkinson, L. Iasemidis
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引用次数: 3

摘要

引入了一种在时频空域分析多变量信号的新方法——归一化Gabor熵(NGE),并将其应用于两例局灶性癫痫患者癫痫发作前数小时的多通道颅内脑电图(iEEG)记录。NGE谱显示,随着癫痫发作时间的临近,致痫灶相关通道的NGE值有统计学意义的逐渐下降。这一结果表明,优势Gabor原子在癫痫发作前数十分钟逐渐出现在脑电图中,对其进行检测和监测可以进一步帮助改善癫痫发作预测算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Normalized Gabor Entropy Analysis of iEEG for Prediction of Epileptic Seizures
A novel measure for analysis of multivariate signals in the time-frequency-space domain, the normalized Gabor entropy (NGE), is introduced and applied to multichannel intracranial EEG (iEEG) recordings hours prior to seizures onset in two patients with focal epilepsy. NGE profiles showed a statistically significant progressive decrease of NGE values at epileptogenic focus-related channels as time for seizures occurrence approached. This result implies the progressive appearance of dominant Gabor atoms in the EEG tens of minutes prior to seizures, the detection and monitoring of which could further assist with improvement of the performance of seizure prediction algorithms.
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