| 基于FastICA的P300电位快速提取方法 |
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| 引用本文： | 张宇,张建华,王行愚,金晶.基于FastICA的P300电位快速提取方法[J].华东理工大学学报(自然科学版),2009,35(5). |
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| 作者姓名： | 张宇 张建华 王行愚 金晶 |
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| 作者单位： | 华东理工大学信息科学与工程学院,上海,200237 |
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| 基金项目： | 国家自然科学基金项目(60775033,60674089);;上海市浦江人才计划项目(07PJ14031);;上海市重点学科项目(B504) |
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| 摘 要： | 从两个方面研究了快速独立分量分析(Fast Independent Component Analysis,Fast ICA)方法在诱发脑电P300少次提取中的应用,并给出了针对健康和残疾被试的实验结果.首先,利用FastICA对观测信号进行去噪,然后对去噪后的P300分量进行较少次叠加平均,并对提取出的健康和残疾被试的P300特征进行了详细的比较分析;然后,从模式识别的角度出发,逐渐减少叠加次数,分别考察了根据提取出的P300特征进行靶刺激和非靶刺激识别的难易程度.实验结果表明了FastICA方法用于P300较少次提取的有效性.
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| 关 键 词： | 快速独立分量分析 脑电信号EEG 靶刺激 残疾被试 |
A FastICA-based Approach to Extracting P300 Potential |
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| ZHANG Yu,ZHANG Jian-hua,WANG Xing-yu,JIN Jing.A FastICA-based Approach to Extracting P300 Potential[J].Journal of East China University of Science and Technology,2009,35(5). |
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| Authors: | ZHANG Yu ZHANG Jian-hua WANG Xing-yu JIN Jing |
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| Institution: | School of Information Science and Engineering;East China University of Science andTechnology;Shanghai 200237;China |
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| Abstract: | From two aspects,this paper analyzes the application of fast independent component analysis(FastICA) algorithm in the extraction of P300 by a few trials averaging,and presents simulation results for both normal and disabled subjects.Firstly,the noises are removed from the observed signals by using FastICA,and a few P300 trials are averaged.The features of P300 for both normal and disabled subjects are analyzed.Secondly,in terms of pattern recognition,the number of trials is reduced successively,and the diff... |
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