基于振幅-周期二维特征的脑电样本熵分析  

Sample entropy analysis of electroencephalogram based on the two-dimensional feature of amplitude and period

作　　者：郭家梁[1,2,3,4] 钟宁[1,2,3,4,5] 马小萌[1,2,3,4] 张明辉[1,2,3,4] 周海燕[1,2,3,4] 

机构地区：[1]北京工业大学,北京未来网络科技高精尖创新中心,北京100124 [2]北京工业大学,国际WIC研究院,北京100124 [3]磁共振成像脑信息学北京市重点实验室,北京100124 [4]脑信息智慧服务北京市国际科技合作基地,北京100124 [5]前桥工业大学生命科学与信息工程系,前桥371-0816

出　　处：《物理学报》2016年第19期10-18,共9页Acta Physica Sinica

基　　金：国家重点基础研究发展计划(批准号:2014CB744600);国家国际科技合作专项(批准号:2013DFA32180);国家自然科学基金(批准号:61420106005,61272345)资助的课题~~

摘　　要：样本熵可以有效反映一维时间序列中新模式的生成概率,但缺乏对二维序列复杂度的表征能力.基于对传统样本熵方法的改进,提出一种在振幅-周期二维空间描述波形复杂度的方法,二维样本熵反映了波形振动在振幅-周期空间中新模式的生成概率.通过仿真实验证明了这种方法描述波形复杂度的有效性,当波形的复杂度特征表现为振幅-周期的交互作用时,二维样本熵对复杂度的描述比一维条件下的样本熵更加有效.基于二维样本熵对抑郁症组和对照组的脑电复杂度进行分析,结果表明,抑郁症组在Alpha频段左侧顶区和左侧枕区的二维样本熵显著低于对照组,表明在上述频段和位置,抑郁症患者脑电中新模式的生成概率显著低于正常人,这一特征可能成为抑郁症的潜在生物标记.Sample entropy, a complexity measure that quantifies the new pattern generation rate of time series, has been widely applied to physiological signal analysis. It can effectively reflect the pattern complexity of one-dimensional sequences,such as the information contained in amplitude or period features. However, the traditional method usually ignores the interaction between amplitude and period in time series, such as electroencephalogram（EEG） signals. To address this issue, in this study, we propose a new method to describe the pattern complexity of waveform in a two-dimensional space. In this method, the local peaks of the signals are first extracted, and the variation range and the duration time between the adjacent peaks are calculated as the instantaneous amplitude and period. Then the amplitude and period sequences are combined into a two-dimensional sequence to calculate the sample entropy based on the amplitude and period information. In addition, in order to avoid the influence of the different units in the two dimensions, we use the Jaccard distance to measure the similarity of the amplitude-period bi-vectors in the waveforms, which is different from the one-dimensional method. The Jaccard distance is defined as the ratio of the different area to the combined area of two rectangles containing the amplitude-period bi-vectors in the Cartesian coordinate system. To verify the effectiveness of the method, we construct five sets of simulative waveforms in which the numbers of patterns are completely equal in one-dimensional space of amplitude or period but the numbers in two-dimensional space are significantly different（P 〈0.00001）. Simulation results show that the two-dimensional sample entropy could effectively reflect the different complexities of the five signals（P 〈0.00001）, while the sample entropy in one-dimensional space of amplitude or period cannot do. The results indicate that compared with the one-dimensional sample entropy, the two-dimensional sample entropy is very effective to

关 键 词：样本熵 二维 脑电 抑郁症 

分 类 号：R749.4[医药卫生—神经病学与精神病学] O211.61[医药卫生—临床医学]