Localization of epileptic foci from preictal EEG data using standardized shrinking LORETA-FOCUSS algorithm

Wu Wei, Jia Wenyan, Liu Hesheng, G. Xiaorong, Zhang Guojun, W. Yuping
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引用次数: 2

Abstract

To localize epileptic foci, EEG source localization methods are often applied to interictal or ictal EEG data. However, ictal epileptiform is often interfered with artifacts caused by the movement of the patient. In this paper, we use an algorithm called Standardized Shrinking LORETA-FOCUSS (SSLOFO) with a three-shell head model to reconstruct the sources from the EEG data of an epileptic patient during four subperiods, with three preictal and one ictal. The results demonstrate that using preictal EEG, SSLOFO can accurately localize the epileptic foci in the left frontal lobe, as has been confirmed by intracranial recordings. The present study also suggests that we may use the trends of the estimated source energy with time to predict epileptic seizures.
基于标准化loreta - focus算法的癫痫病灶定位
为了定位癫痫病灶,EEG源定位方法常应用于间歇期或间歇期的EEG数据。然而,癫痫病发作时往往会受到由患者运动引起的伪影的干扰。本文采用一种基于三壳头模型的标准化loreta - focus (SSLOFO)算法,对一个癫痫患者的脑电图数据进行了4个亚期(3个前峰期和1个前峰期)的源重构。结果表明,颅侧脑电图显示,SSLOFO能准确定位左额叶的癫痫病灶,颅内记录也证实了这一点。本研究还表明,我们可以利用估计的源能量随时间的变化趋势来预测癫痫发作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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