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文章基本信息

  • 标题:Improve EEG Source Localization for an Isotropic Multi-Spherical Head Model
  • 本地全文:下载
  • 作者:Nikita Gupta ; Swapna Devi
  • 期刊名称:International Journal of Soft Computing & Engineering
  • 电子版ISSN:2231-2307
  • 出版年度:2013
  • 卷号:3
  • 期号:2
  • 页码:223-225
  • 出版社:International Journal of Soft Computing & Engineering
  • 摘要:Human head comprises multiple layers and tissues. The aim of this work is to investigate the effect of conductivity variation, due to presence of Gray matter and White matter in Brain, on Source Localization in Electroencephalography (EEG). Particle Swarm Optimization (PSO) Algorithm, a global optimization algorithm, has been used for finding Inverse Solution of EEG. It has been found that a five-spherical head model comprising, Scalp, Skull, CSF, Gray Matter and White Matter give better performance in source localization than a four spherical head model comprising, Scalp, Skull, CSF and Brain.
  • 关键词:EEG; Head Models; PSO; Source;Localization.
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