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Fast, Accurate Localization of Epileptic Seizure Onset Zones Based on Detection of High-Frequency Oscillations Using Improved Wavelet Transform and Matching Pursuit Methods

机译:基于改进小波变换和匹配追踪方法的高频振荡检测,快速准确地定位癫痫发作区

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摘要

This letter describes the improvement of two methods of detecting high-frequency oscillations (HFOs) and their use to localize epileptic seizure onset zones (SOZs). The wavelet transform (WT) method was improved by combining the complex Morlet WT with Shannon entropy to enhance the temporal-frequency resolution during HFO detection. And the matching pursuit (MP) method was improved by combining it with an adaptive genetic algorithm to improve the speed and accuracy of the calculations for HFO detection. The HFOs detected by these two methods were used to localize SOZs in five patients. A comparison shows that the improved WT method provides high specificity and quick localization and that the improved MP method provides high sensitivity.
机译:这封信描述了两种检测高频振荡(HFO)的方法的改进,以及它们用于定位癫痫发作区(SOZ)的方法。通过将复杂的Morlet WT与Shannon熵结合起来以改进HFO检测期间的时频分辨率,改进了小波变换(WT)方法。通过与自适应遗传算法相结合改进了匹配追踪(MP)方法,以提高HFO检测的计算速度和准确性。通过这两种方法检测到的HFO被用于定位五名患者中的SOZ。比较表明,改进的WT方法提供了高特异性和快速定位,改进的MP方法提供了高灵敏度。

著录项

  • 来源
    《Neural computation》 |2017年第1期|194-219|共26页
  • 作者单位

    School of Automation, China University of Geosciences, Wuhan, Hubei 430074, China wumin@cug.edu.cn;

    School of Automation, China University of Geosciences, Wuhan, Hubei 430074, China 1094466142@qq.com;

    School of Automation, China University of Geosciences, Wuhan, Hubei 430074, China xbwan23@cug.edu.cn;

    School of Automation, Guangdong University of Technology, Guangzhou, Guangdong 510006, China yuxiaodu@gdut.edu.cn;

    School of Automation, China University of Geosciences, Wuhan, Hubei 430074, China & School of Engineering, Tokyo University of Technology, Hachioji, Tokyo 192-0982, Japan she@stf.teu.ac.jp;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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