Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (15): 209-212.DOI: 10.3778/j.issn.1002-8331.2009.15.061

• 工程与应用 • Previous Articles     Next Articles

Removing EOG artifacts from EEG signal based on ICA

LI Ying,AI Ling-mei   

  1. College of Computer Science,Shaanxi Normal University,Xi’an 710062,China
  • Received:2008-03-28 Revised:2008-06-10 Online:2009-05-21 Published:2009-05-21
  • Contact: LI Ying

基于独立分量分析的脑电信号的眼电伪迹消除

李 营,艾玲梅   

  1. 陕西师范大学 计算机科学学院,西安 710062
  • 通讯作者: 李 营

Abstract: This paper introduces a new technology Independent Component Analysis(ICA),including its basic concepts,principles,and some representative algorithms,such as Fast Independent Component Analysis(FICA) and Kernel Independent Component Analysis(KICA).The method of removing EOG artifact from EEG Data was proposed.Simulation results show that KICA algorithm can remove EOG artifact from the EEG signal better,and it is also more accurate and robust than FICA.

摘要: 介绍了独立分量分析技术的基本概念和原理,及其具有代表性的基于负熵最大的快算独立分量分析算法和基于核空间的独立分量分析算法,并分别对脑电中的眼电伪迹进行去除。通过仿真实验表明了独立分量分析算法较快速独立分量分析算法能更好去除眼电伪迹,具有较好准确性和鲁棒性。