A Novel Method of De-noising and Classifying on Mental EEG of Imaging Left-Right Hands Movement

被引：0

作者：

Wu, Shaochun ^{[1
]}

Song, Duhong ^{[1
]}

Li, Mingdong ^{[1
]}

Xu, Lingyu ^{[1
]}

机构：

[1] Shanghai Univ, Sch Comp Engn & Sci, Shanghai, Peoples R China

来源：

2009 INTERNATIONAL JOINT CONFERENCE ON BIOINFORMATICS, SYSTEMS BIOLOGY AND INTELLIGENT COMPUTING, PROCEEDINGS | 2009年

关键词：

EEG; De-noising; Warelet transform; ICA;

D O I：

10.1109/IJCBS.2009.87

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

After analyzing the current wavelet threshold denoising methods and independent component analysis (ICA) methods in EEG, this paper proposed a novel method for EEG de-noising which combines the new threshold denoising method with ICA method and implicates it to deal with mental EEG of imaging left-right hands movement, and then classifies the signal by Support Vector Machine (SVM). The correct classification rate of 89.93% is achieved by the approach in this paper

引用

页码：356 / 359

页数：4

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