全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于小波包法与CSSD的P300特征提取方法

Keywords: P300电位,特征提取,小波包,AR模型功率谱,共空域子空间

Full-Text   Cite this paper   Add to My Lib

Abstract:

针对P300电位信号微弱、抗干扰能力差、识别率低等问题,提出一种小波包变换(waveletpackettransform,WPT)与共空域子空间分解法(spatialsubspacedecomposition,CSSD)相结合的特征提取方法,即WPCSSD法.首先,对脑电信号进行叠加平均以提高信号的信噪比;其次,使用小波包法对脑电信号进行滤波,并依据P300电位的有效时频信息重构脑电信号;然后,求取其AR模型功率谱,并基于CSSD法构造空间滤波器,获得能体现P300电位时-频-空特征的特征向量;最后,以支持向量机为分类器进行分类.实验结果表明:本方法具有较强的抗干扰能力和自适应能力,在国际BCI竞赛数据集上获得了95.22%的分类正确率,证明了本方法的正确性和有效性.

References

[1]  李金亮.脑-机接口中P300识别算法的研究[D].济南:山东大学控制科学与工程学院,2007.LI Jin-liang.The recognition algorithm of P300 in brain computer interface[D].Jinan:College of Control Science and Engineering,Shangdong University,2007.(in Chinese)
[2]  黄漫玲,吴平东,殷罡,等.基于稳态视觉诱发电位的脑-机接口实验研究[J].北京理工大学学报,2008,28(11):957-961.HUANG Man-ling,WU Ping-dong,YIN Gang,et al.An experimental research on brain-computer interface based on steady state visual evoked potential[J].Transactions of Beijing Institute of Technology,2008,28(11):957-961.(in Chinese)
[3]  郑军.基于稳态视觉诱发电位的脑-机接口研究[J].科学技术与工程,2011,33(11):8149-8154.ZHENG Jun.An research on brain-computer interfaces based on the steady state visual evoked potentials[J].Science Technology and Engineering,2011,33(11):8149-8154.(in Chinese)
[4]  李晓鸥,乐建威.基于小波预处理和贝叶斯分类器的P300识别算法[J].数据采集与处理,2011,26(4):420-424.LI Xiao-ou,YUE Jian-wei.P300 detection algorithm based on wavelet preprocessing and bayesian classification[J].Journal of Data Acquisition&Processing,2011,26(4):420-424.(in Chinese)
[5]  吴婷,颜国正,杨帮华.基于小波包分解的脑电信号特征提取[J].仪器仪表学报,2007,25(12):2230-2234.WU Ting,YAN Guo-zheng,YANG Bang-hua.EEG feature extraction in brain computer interface based on wavelet packet decomposition[J].Chinese Journal of Scientific Instrument,2007,25(12):2230-2234.(in Chinese)
[6]  ZANDI A S,JAVIDAN M,DUMONT G A,et al.Automated real-time epileptic seizure detection in scalp EEG recordings using an algorithm based on wavelet packet transform[J].IEEE Transactions on Biomedical Engineering,2010,57(7):1639-1651.
[7]  MOUSAVI S R,NIKNAZAR M,VAHDAT B V,et al.Epileptic seizure detection using AR model on EEG signals[C]∥Proceeding of International Biomedical Engineering Conference.Cairo:[s.n.],2008:1-4.
[8]  姚文俊.自相关法和Burg法在AR模型功率谱估计中的仿真研究[J].计算机与数字工程,2007,35(10):32-34.YAO Wen-jun.Research on AR model power spectrum estimation based on the algorithm and burg algorithm[J].Computer&Digital Engineering,2007,35(10):32-34.(in Chinese)
[9]  WANG Y,BERG P,SCHERG M.Common spatial subspace decomposition applied to analysis of brain responses under multiple task conditions:a simulation study[J].Clinical Neurophysiology,1999,110(4):604-614.
[10]  丁世飞,齐丙娟,谭红艳.支持向量机理论与算法研究综述[J].电子科技大学学报,2011,40(1):1-10.DING Shi-fei,QI Bing-juan,TAN Hong-yan.An overview on theory and algorithm of support vector machines[J].Journal of University of Electronic Science and Technology of China,2011,40(1):1-10.(in Chinese)
[11]  KRUSIENSKI D J,SELLERS E W,MCFARLAND D J,et al.Toward enhanced P300 speller performance[J].Journal of Neuroscience Methods,2008,167(1):15-21.
[12]  KRUSIENSKI D J,SELLERS E W,CABESTAING F,et al.A comparison of classification techniques for the P300speller[J].Journal of Neural Engineering,2006,3(4):299-305.
[13]  王斐,张育中,宁廷会,等.脑-机接口研究进展[J].智能系统学报,2011,6(3):189-199.WANG Fei,ZHANG Yu-zhong,NING Ting-hui,et al.Research progress in a brain-computer interface[J].Transactions on Intelligent Systems,2011,6(3):189-199.(in Chinese)
[14]  MING D,AN X,XI Y,et al.Time-locked and phaselocked features of P300 event-related potentials(ERPs)for brain-computer interface speller[J].Biomedical Signal Processing and Control,2010,5(4):243-251.
[15]  李窦哲.脑-机接口系统中脑电信号采集于特征识别[D].太原:山西大学物理电子工程学院,2010.LI Dou-zhe.EEG signal acquisition and feature reorganization for BCI system[D].Taiyuan:College of Engineering of Physics and Electronics,Shanxi University,2010.(in Chinese)
[16]  KHAN O I,KIM S H,RASHEED T,et al.Extraction of P300 using constrained independent component analysis[C]∥Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society:Engineering the Future of Biomedicine,EMBC.Minneapolis:[s.n.],2009:4031-4034.
[17]  LI K,SANKAR R,ARBEL Y,et al.P300 based single trial independent component analysis on EEG signal[C]∥5th International Conference on Foundations of Augmented Cognition:Neuroergonomics and Operational Neuroscience.San Diego:[s.n.],2009:404-410.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133