CAJ | 학술논문

脑电信号是一种产生机理相当复杂且非常微弱的随机信号，综合反映了大脑组织的脑电活动及大脑的功能状态。由于脑电信号的微弱性，传统的基本模板方法在脑电信号分析上得到了良好的应用。为进一步提升分析脑电信号的性能，提出了一种新的基于自适应模板的转移熵方法并分析了青少年脑电与成年人脑电信号。结果表明：对于青少年脑电还是成年人脑电，与基本模板法相比，基于自适应模板法的转移熵可以更显著地表示脑电信号的耦合作用，并且具有更好的区分度，这将能更好地捕捉到信号中的动态信息、系统动力学复杂性的改变。同时，该方法将更有利于医学临床诊断的辅助检测，对脑电信号是否处于病理状态的诊断提供了新的更好的判断依据。
뇌전신호시일충산생궤리상당복잡차비상미약적수궤신호，종합반영료대뇌조직적뇌전활동급대뇌적공능상태。유우뇌전신호적미약성，전통적기본모판방법재뇌전신호분석상득도료량호적응용。위진일보제승분석뇌전신호적성능，제출료일충신적기우자괄응모판적전이적방법병분석료청소년뇌전여성년인뇌전신호。결과표명：대우청소년뇌전환시성년인뇌전，여기본모판법상비，기우자괄응모판법적전이적가이경현저지표시뇌전신호적우합작용，병차구유경호적구분도，저장능경호지포착도신호중적동태신식、계통동역학복잡성적개변。동시，해방법장경유리우의학림상진단적보조검측，대뇌전신호시부처우병리상태적진단제공료신적경호적판단의거。
Electroencephalogram (EEG) is a very weak random signal with complex mechanism, which comprehensively reflects the activities and the functional states of brain tissue. Due to the weak characteristic of EEG, the traditional basic template method is a good tool for EEG analysis. In order to further enhance the performance of this method, we propose a new transfer entropy method based on adaptive template. The method improves the symbolization of time series based on the original basic template method. Numerical experiments show that the improved adaptive template method can obtain better dynamic characteristics, and also has better ability to distinguish the results in the analysis of time series. We use the transfer-entropy-based adaptive template method to analyze adolescent and adult EEG. We also study the relationship of the transfer-entropy-based adaptive template method to the total data length L and the data length l of the divided cells. Numerical results show that the transfer entropy value of adult EEG based on adaptive template is significantly higher than that of teenager EEG. This indicates that adult has a more significantly mental activity and the functional status of the brain is more complex. We then apply this method to human EEG signals and investigate their statistical properties. The results show that compared with the result of the basic method, the transfer-entropy-based adaptive template method can significantly show the EEG coupling for adolescents and adults EEG, which has a better discrimination and can better capture dynamic information and the change of the system dynamic complexity. At the same time, it will be more conducive to clinical diagnosis and provides a new and better method to judge whether brain is in a pathological state.