EEG feature extraction based on wavelet packet decomposition for brain computer interface

被引：247

作者：

Wu Ting ^{[1
]}

Yan Guo-zheng ^{[1
]}

Yang Bang-hua ^{[1
]}

Sun Hong ^{[2
]}

机构：

[1] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Shanghai 200030, Peoples R China

[2] Anhui Inst Architecture & Ind, Sch Elect & Informat Engn, Hefei 230022, Peoples R China

来源：

MEASUREMENT | 2008年 / 41卷 / 06期

关键词：

brain computer interface (BCI); wavelet packet decomposition (WPD); feature extraction; energy of sub-band;

D O I：

10.1016/j.measurement.2007.07.007

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In the study of brain computer interfaces, a novel method was proposed in this paper for the feature extraction of electroencephalogram (EEG). It was based on wavelet packet decomposition (WPD). The energy of special sub-bands and corresponding coefficients of wavelet packet decomposition were selected as features which have maximal separability according to the Fisher distance criterion. The eigenvector was obtained for classification by combining the effective features from different channels; its performance was evaluated by separability and pattern recognition accuracy using the datasets of BCI 2003 Competition. The classification results have proved the effectiveness of the proposed method. This technology provides another useful way to EEG feature extraction in BCIs. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：618 / 625

页数：8

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