物理学报Issue(23)：238701-1-238701-6,6.DOI:10.7498/aps.62.238701
基于改进的符号转移熵的心脑电信号耦合研究
Coupling analysis of electrocardiogram and electroencephalogram based on improved symbolic transfer entropy
摘要
Abstract
Exploration of the coupling relationship in dynamical system has always been a hot topic of many scholars at home and abroad, the traditional symbolic dynamics analysis method may lead to the results from the serious effect of non-stationary time series. This paper employs coarse graining extraction based on research of original transfer entropy. Through theoretical and experimental analysis, we find that the results of transfer entropy have different distribution trend under different extraction conditions in the coupling analysis of electroencephalogram and electrocardiogram. We choose the best effect of signal data extraction method and apply it to the later application analysis. Furthermore, this paper proposes improvement on the method of time series symbolization, using dynamic adaptive segmentation method. The experimental results show that the whether waking period or sleeping stage, coupling between electroencephalogram and electrocardiogram is more significant when using improved symbolic transfer entropy algorithm. It is also better to capture the dynamic information of the signal and the change of complexity of system dynamics, which is more conductive to clinical testing in practical application and has a better effect on the analysis of non-stationary time series.关键词
心脑电信号/粗粒化/符号转移熵/基本尺度Key words
electrocardiogram and electroencephalogram/coarse graining/symbolic transfer entropy/basic scale引用本文复制引用
吴莎,李锦,张明丽,王俊..基于改进的符号转移熵的心脑电信号耦合研究[J].物理学报,2013,(23):238701-1-238701-6,6.基金项目
国家自然科学基金(批准号:61271082,61201029,61102094)和江苏省自然科学基金(批准号:BK2011759, BK2011565)资助的课题.*Project supported by the National Natural Science Foundation of China (Grant Nos.61271082,61201029,61102094), and the Natural Science Founda-tion of Jiangsu Province (Grant Nos. BK2011759, BK2011565) （批准号:61271082,61201029,61102094）
