计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (34): 204-206.

• 工程与应用 • 上一篇    下一篇

基于支持向量机的脑电信号中左右手判别

唐 艳,汤井田   

  1. 中南大学 信息物理学院 生物医学研究所,长沙 410083
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-12-01 发布日期:2007-12-01
  • 通讯作者: 唐 艳

Distinguishing between left and right finger movement from EEG using SVM

TANG Yan,TANG Jing-tian   

  1. Biomedical Engineering School of Info-Physics Engineering,Central South University,Changsha 410083,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-12-01 Published:2007-12-01
  • Contact: TANG Yan

摘要: 在脑-机接口的研究中分类识别技术占有重要地位。介绍了一种方法,用于对单次信号的分类。这种方法主要思想是将共空域子空间分解和支持向量机相结合,以便提取信号特征。该方法被用于“BCI Competition 2003”第IV数据包上,分类正确率达89%。

关键词: 脑电信号, 脑-机接口, 支持向量机, 共空域子空间分解

Abstract: Identification and classification technology plays an important part in study of the BCI system.Presents an algorithm for classifying single-trial electroencephalogram(EEG).It combines common spatial subspace decomposition with support vector machine to extract features from multichannel EEG.This algorithm is applied to the data set IV of “BCI Competition 2003” with a classification accuracy of 89% on the test set.

Key words: electroencephalogram, Brain-Computer Interface(BCI), Support Vector Machine(SVM), Common Spatial Subspace Decomposition(CSSD)