基于头皮脑电图和近似熵的癫痫病灶定位

Zhen Zhang, Yi Zhou, Tian Mei, Ziyi Chen, Shouhong Du, Xianghua Tian
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引用次数: 4

摘要

为了减少有创检查造成的损伤,节约采集EEG(颅内脑电图)的资源,特别是在大面积开颅手术中,我们将非线性动力学与医学统计方法相结合,通过分析无创采集的头皮EEG(脑电图)进行癫痫病灶定位。首先,测量近似熵(ApEn),定量得到脑电信号的复杂度;其次,从正常脑电图中计算出ApEn的生理参考范围,得到癫痫发作时各电极不同程度的复杂变化;通过以上步骤,最终实现癫痫病灶的初步定位。我们分析了6例被诊断为部分癫痫的患者的头皮脑电图数据,并对这6例患者成功进行了初步定位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Localization of epileptic foci based on scalp EEG and approximate entropy
In order to reduce damage from invasive check and save resources during iEEG (intracranial electroencephalogram) collection, especially when large area of craniotomy is operated, we combined nonlinear dynamics with medical statistical methods to carry out epileptic foci localization by analyzing scalp EEG (electroencephalogram) which can be collected by noninvasive way. Firstly, ApEn (approximate entropy) was measured to get the complexity of EEG quantitatively. Secondly, a physiological reference range of ApEn which was caculated from normal EEG was set up and different degrees of the complexity changes on each electrode during seizures were obtained. Based on the above steps, the preliminary localization of epileptic foci could be finally achieved. We analyzed scalp EEG data for a total of six patients who had been diagnosed as partial epilepsy, and won the success of the preliminary locations on these six patients.
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