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计算机工程

• 开发研究与工程应用 • 上一篇    下一篇

运动想象功率谱信号的模糊融合研究

徐鲁强1,2,肖光灿2   

  1. (1. 西南交通大学信息科学与技术学院,成都610031; 2. 西南科技大学计算机科学与技术学院,四川绵阳621010)
  • 收稿日期:2014-06-09 出版日期:2015-06-15 发布日期:2015-06-15
  • 作者简介:徐鲁强(1968 - ),男,教授,主研方向:智能信息处理;肖光灿,教授。
  • 基金资助:

    四川省人社厅留学择优基金资助项目;绵阳网络融合工程实验室开放基金资助项目(12ZXWK07)。

Study on Power Spectrum Signal Fuzzy Fusion for Motor Imagery

XU Luqiang  1,2,XIAO Guangcan  2   

  1. (1. School of Information Science and Technology,Southwest Jiaotong University,Chengdu 610031,China; 2. School of Computer Science and Technology,Southwest University of Science and Technology,Mianyang 621010,China)
  • Received:2014-06-09 Online:2015-06-15 Published:2015-06-15

摘要:

在由容积传导采集的脑电数据中,可用于识别的信号非常模糊。为此,对三通道采集的运动想象脑电数据进行分析,融合多个识别结果以提高识别效果。预处理三通道采集的脑电数据,分别计算每个通道的功率谱,提取运动想象相关的功率谱值作为特征值,应用线性识别方法及Choquet 模糊积分对得到的多个结果进行融合。使用 2003 年国际BCI 竞赛数据和实验室测得的数据验证融合效果,结果显示融合后的识别准确率明显高于单一识别器。

关键词: 脑电数据, 信息融合, 线性识别分析, Choquet 模糊积分, 功率谱, 运动想象

Abstract:

Due to the volume conduction multi-channel Electroencephalogram(EEG)recordings give a rather blurred image of brain activity. Three-channel motor imagery EEG is analyzed. The result of EEG recognition is not satisfactory. It studies multiple classifier fusion to improve the motor imagery EEG classification accuracy,extracts feature from power spectrum calculated from the EEG, and designs classifiers based on the well-known Linear Discriminant Analysis(LDA)method. The fusion of the individual classifiers is realized by means of the Choquet fuzzy integral. BCI competition 2003 dataset III is used to validate fusion method. It demonstrates that the proposed method comes with better performance when compared with single techniques,and shows the effectiveness of the proposed method for dealing with EEG.

Key words: Electroencephalogram ( EEG) data, information fusion, Linear Discriminant Analysis ( LDA), Choquet fuzzy integral, power spectrum, motor imagery

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