| 在线脑机接口中脑电信号的特征提取与分类方法 |
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| 引用本文： | 徐宝国,宋爱国,费树岷.在线脑机接口中脑电信号的特征提取与分类方法[J].电子学报,2011,39(5):1025-1030. |
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| 作者姓名： | 徐宝国 宋爱国 费树岷 |
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| 作者单位： | 徐宝国,宋爱国,XU Bao-guo,SONG Ai-guo(东南大学仪器科学与工程学院,江苏南京,210096);费树岷,FEI Shu-min(东南大学自动化学院,江苏南京,210096) |
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| 基金项目： | 国家863高技术研究发展计划，国家自然科学基金，中国博士后基金面上项目 |
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| 摘 要： | 在脑机接口研究中,针对运动想象脑电信号的特征抽取,提出了一种基于离散小波变换和AR模型的方法.利用Daubechies类小波函数对脑电信号进行3层分解,抽取小波变换系数的统计特征;利用Burg算法提取脑电信号6阶AR模型系数.将这两类特征进行组合后使用神经网络、支持向量机、马氏距离线性判别进行分类并比较分析.采用BCI...
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| 关 键 词： | 在线脑机接口 运动想象 小波变换 |
| 收稿时间： | 2010-06-17 |
Feature Extraction and Classification of EEG in Online Brain-Computer Interface |
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| XU Bao-guo,SONG Ai-guo,FEI Shu-min.Feature Extraction and Classification of EEG in Online Brain-Computer Interface[J].Acta Electronica Sinica,2011,39(5):1025-1030. |
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| Authors: | XU Bao-guo SONG Ai-guo FEI Shu-min |
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| Affiliation: | XU Bao-guo1,SONG Ai-guo1,FEI Shu-min2(1.School of Instrument Science and Engineering,Southeast University,Nanjing,Jiangsu 210096,China,2.School of Automation,China) |
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| Abstract: | In the study of brain-computer interface(BCI),a novel method of extracting electroencephalography(EEG) features based on discrete wavelet transform(DWT) and autoregressive(AR) model was proposed.First,the EEG signal was decomposed to three levels by Daubechies wavelet function and statistics of wavelet coefficients were computed.Also,the sixth-order AR coefficients of the EEG signal were estimated using Burg's algorithm.Then,the combination features were used as an input vector for neural network(NN) classi... |
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| Keywords: | online brain-computer interface motor imagery wavelet transform |
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