基于支持向量机的脑电信号中左右手判别

Distinguishing between left and right finger movement from EEG using SVM

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"BCICompetition2003"第IV数据包上,分类正确率达89%。

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