首页> 外文会议>Proceedings of the 2015 International Conference on Green Computing and Internet of Things >Epileptic seizure prediction and identification of epileptogenic region using EEG signal
【24h】

Epileptic seizure prediction and identification of epileptogenic region using EEG signal

机译:癫痫发作的预测和EEG信号识别癫痫发作区域。

获取原文
获取原文并翻译 | 示例

摘要

This paper presents a method to predict an epileptic seizure using synchrony analysis of EEG signals. The topographical map of the brain is divided into different regions and synchrony measures are computed between these different regions to identify the region responsible for epileptic seizure. The molecular and biochemical process of seizure generation during pre-ictal period is essential for seizure to start and this property has been investigated here in EEG signals to predict the onset of epileptic seizure. Particular region of the brain responsible for seizure is identified by pairing the EEG signals from different regions of brain and identifying the changes in synchrony measures corresponding to those regions. Two synchrony measures one from time domain, correlation, and other from frequency domain, coherence, are used in this work to validate the observations. Coherence and correlation increases in pre-ictal state and hence seizure onset can be predicted in advance. The results shows that epileptogenic region of the brain can also be identified.
机译:本文提出了一种利用脑电信号同步分析预测癫痫发作的方法。将大脑的地形图划分为不同的区域,并在这些不同的区域之间计算同步度,以识别引起癫痫发作的区域。发作前癫痫发作的分子和生化过程对于癫痫发作的开始是必不可少的,并且已在EEG信号中对此特性进行了研究,以预测癫痫发作的发作。通过配对来自大脑不同区域的EEG信号并识别与那些区域相对应的同步测量的变化,可以确定负责癫痫发作的大脑特定区域。在这项工作中使用了两个同步度量,一个来自时域相关性,另一个来自频域相干性,以验证观测结果。发作前状态的相干性和相关性增加,因此可以提前预测癫痫发作。结果表明,还可以识别出大脑的致癫痫区域。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号