信号域中癫痫区域定位-一个智能装置

O. K. Fasil, R. Rajesh, T. M. Thasleema
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引用次数: 4

摘要

癫痫区定位是内科难治性癫痫患者术前评估的关键阶段(这比任何其他类型的癫痫更繁重)。一种常用的分析癫痫发病区域的方法是利用脑电图从人的头皮捕捉电位。本文提出了一种基于信号域特征分析脑电图信号的有效癫痫区域定位方法。从信号及其微分信号中提取信号平均能量和平均对数能量熵等特征。实验结果表明,所提出的特征能够通过对癫痫信号和非癫痫信号进行分类来定位癫痫区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Epilepsy region localization in signal domain — A smart getup
Epilepsy region localization is a key stage in pre-surgical evaluation of patients with medical refractory epilepsy (which is more burdensome than any other types of epilepsy). A common way of analyzing regions which are affected with epilepsy is using electroencephalogram by capturing electric potential from human scalp. In this article, a method is presented for the effective epilepsy region localization by analyzing electroencephalogram signals based on signal domain features. Features such as average signal energy and average log-energy entropy are extracted from signals and their differential signals in the signal domain. The experimental results show the ability of the proposed features to localize the epileptic regions by classifying the epileptic signals from non epileptic signals.
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