| 三类运动想象脑电信号的离线分析研究 |
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| 引用本文： | 林江凯,陈民铀,张莉,张聪誉.三类运动想象脑电信号的离线分析研究[J].微计算机信息,2011(3). |
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| 作者姓名： | 林江凯 陈民铀 张莉 张聪誉 |
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| 作者单位： | 重庆大学电气工程学院输配电装备及系统安全与新技术国家重点实验室; |
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| 摘 要： | 为解决运动想象脑电信号(EEG)的多分类问题,本文提出了一种基于粒子群优化支持向量机(PSO-SVM)的EEG分类方法,采用NEUROSCAN平台设计实验自测数据,对想象左手握握力器,右手握握力器,右脚踩油门三类运动想象任务进行了分类识别研究。采用FFT和IFFT对信号进行预处理,采用离散小波分析(DWT)提取能量值,并结合小波系数作为组合特征,分类效果明显好于BP和自组织神经网络(SOM)分类器。
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| 关 键 词： | 运动想象 脑电信号 离散小波变换 自组织神经网络 粒子群优化支持向量机 |
The research of off-line analysis of three-class motor imagery EEG |
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| LIN Jiang-kai CHEN Min-you ZHANG Li ZHANG Cong-yu.The research of off-line analysis of three-class motor imagery EEG[J].Control & Automation,2011(3). |
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| Authors: | LIN Jiang-kai CHEN Min-you ZHANG Li ZHANG Cong-yu |
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| Affiliation: | LIN Jiang-kai CHEN Min-you ZHANG Li ZHANG Cong-yu(State Key Laboratory of Power Transmission Equipment & System Security and New Technology,School of Electrical Engineering,Chongqing University,Chongqing,40030,P.R.China) |
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| Abstract: | To solve the problem of motor imagery EEG multi-classification,we designed an experiment to get EEG data through NEUROSCAN,and proposed a classification method based on Particle Swarm Optimization-Support Vector Machine to recognize the three kinds of motor imagery tasks,including left hand grip-grasped,right hand grip-grasped and right foot accelerator-stepped.The signal pre-processing was conducted via FFT and IFFT.The discrete wavelet transform was used to extract the feature,The results show that the pr... |
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| Keywords: | motor imagery EEG Discrete Wavelet Transform Self-organizing Map Particle Swarm Optimization-Support Vector Machine |
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