华南理工大学学报(自然科学版) ›› 2008, Vol. 36 ›› Issue (5): 101-105.

• 电子、通信与自动控制 • 上一篇    下一篇

基于运动想象的皮层脑电图频域模式滤波

吕俊 谢胜利   

  1. 华南理工大学 电子与信息学院, 广东 广州 510640
  • 收稿日期:2007-04-23 修回日期:2007-10-14 出版日期:2008-05-25 发布日期:2008-05-25
  • 通信作者: 吕俊(1979-),男,博士生,主要从事机器学习、脑机接口方面的研究. E-mail:rylj@163.com
  • 作者简介:吕俊(1979-),男,博士生,主要从事机器学习、脑机接口方面的研究.
  • 基金资助:

    国家自然科学基金重点项目(U0635001);国家自然科学基金资助项目(60505005)

Frequency-Domain Pattern Filtering of Electrocorticography Based on Motor Imagery

Lü Jun  Xie Sheng-li    

  1. School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2007-04-23 Revised:2007-10-14 Online:2008-05-25 Published:2008-05-25
  • Contact: 吕俊(1979-),男,博士生,主要从事机器学习、脑机接口方面的研究. E-mail:rylj@163.com
  • About author:吕俊(1979-),男,博士生,主要从事机器学习、脑机接口方面的研究.
  • Supported by:

    国家自然科学基金重点项目(U0635001);国家自然科学基金资助项目(60505005)

摘要: 为了提高皮层脑电图(ECoG)脑-机接口(BCI)的分类精度,提出了基于运动想象的ECoG频域模式滤波法.该方法通过联合对角化寻找最具判别力的投影方向作为频域滤波器,抽取滤波后ECoG的均值和标准差作为特征,然后采用核Fisher判别式进行分类.BCI2005数据集Ⅰ的实验结果表明:采用该方法仅用单个电极即可获得92%的测试精度.

关键词: 皮层脑电图, 脑-机接口, 特征提取, 频域模式滤波

Abstract:

In order to improve the classification accuracy of the brain-computer interface(BCI) of electrocortico-graphy(ECoG),a motor imagery-based pattern-filtering method in frequency domain is proposed.In this method,the joint diagonalization is employed to seek the most discriminative projections as the frequency-domain filters,the means and standard deviations of filtered electrocorticograms are extracted as the features,and the kernel Fisher discriminant is applied to the classification.Experimental results of BCI2005 data set Ⅰ show that the proposed method can achieve a classification accuracy of 92% even with a single electrode.

Key words: electrocorticography, brain-computer interface, feature extraction, frequency-domain pattern filtering