| 不同精神状态下EEG序列复杂性研究(英文) |
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| 引用本文： | 胡晓,尧德中.不同精神状态下EEG序列复杂性研究(英文)[J].电子科技大学学报(社会科学版),1999(3). |
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| 作者姓名： | 胡晓 尧德中 |
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| 作者单位： | 电子科技大学自动化系!成都６１００５４ |
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| 基金项目： | 国家教委霍英东青年基金，国家自然科学基金 |
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| 摘 要： | 构造了与脑电的源熵相同的（０，１）分布随机序列，以及用白噪激励依据脑电构造出的ＡＲ模型而得到的ＡＲ序列来作为伪脑电信号。通过比较这三种序列的复杂度，证明了脑电远非随机信号，而是存在某种模式，这种模式可以由ＡＲ模型部分表示出来。在此基础上，对三种精神状态下的脑电序列的复杂度进行了双因素方差分析，结果表明复杂度可以显著地区分这三种状态。
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| 关 键 词： | 脑电图 精神状态 非线性 复杂度 方差分析 |
Study on Complexity of EEG Time Series Under Different Mental States |
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| Hu Xiao, Yao Dezhong.Study on Complexity of EEG Time Series Under Different Mental States[J].Journal of University of Electronic Science and Technology of China(Social Sciences Edition),1999(3). |
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| Authors: | Hu Xiao Yao Dezhong |
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| Abstract: | in this paper. two kinds of surrogate data are designed according to electroencephalography (EEG)data. They are a binomial random series with the same source entropy as that of EEG and an AR series that is theoutput of AR model constructed from EEG data and driven by white noise. Significant differences among thecomplexity of these three series show that BEG is far from being random and has certain pattern in it which canbe partially modeled by AR. The complexity of EEG series recorded during three different mental states iscomputed and the result of two-way analysis of variance shows that the complexity can discriminate the threemental states significantly. |
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| Keywords: | electroencephalography mental state nonlinear complexity analysis of variance |
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