摘要
采用近似熵和样本熵,分别对三种不同思维任务产生的脑电信号进行特征提取,并将其特征进行比较分析,结果显示不同思维作业脑电信号的样本熵的变化幅度明显大于近似熵;近似熵和样本熵作为非线性动力学的统计方法为思维作业脑电信号特征提取提供了一种新的途径。
Approximate entropy and sample entropy were used to make feature extraction of EEG signal produced by three different mental tasks respectively and their features were compared and analyzed. The results show that the changing range of sample entropy of EEG signal of different mental tasks is obviously bigger than that of approximate entropy, and approximate entropy and sample entropy, as nonlinear dynamics statistics methods, provide a new way for feature extraction of EEG signal of mental tasks.
出处
《重庆工商大学学报（自然科学版）》
2013年第6期44-47,78,共5页
Journal of Chongqing Technology and Business University:Natural Science Edition
关键词
近似熵
样本熵
思维作业
脑电信号
approximate entropy
sample entropy
mental task
EEG signal
