冠心病患者心脏电-机械活动时间序列的熵分析  

Analysis of cardiac electro-mechanical time-series in patients with coronary artery disease based on entropy

作　　者：纪丽珍[1] 李鹏[1] 李林 刘澄玉[1] 王新沛[1] 李可[1] 刘常春[1] 

机构地区：[1]山东大学控制科学与工程学院,济南250061 [2]哈尔滨工业大学(威海)理学院,山东威海264200

出　　处：《计算机工程与应用》2016年第10期265-270,共6页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61471223;No.61501280;No.31200744)

摘　　要：基于物理模糊隶属度函数的改进模糊熵(refined fuzzy entropy,r FuzzyEn)在算法的稳定性和抗噪声性能上有显著提升。通过分析5分钟心动周期(RR interval,RRI)和收缩间期(systolic time interval,STI)序列,进一步检验了r FuzzyEn用于分析心脏电-机械活动时间序列的性能。同时,将物理模糊隶属度函数引入互模糊熵(cross fuzzy entropy,C-FuzzyEn),提出改进的互模糊熵(refined C-FuzzyEn,r C-FuzzyEn)算法。使用所提出的r C-FuzzyEn算法,分析了冠心病患者和健康志愿者的RRI-STI序列耦合性,并与传统的互样本熵(cross sample entropy,C-Samp En)和互模糊熵(C-FuzzyEn)进行对比。结果表明,相较于C-Samp En和C-FuzzyEn,所提出r C-FuzzyEn算法的区分能力显著提高,可用于区分冠心病患者和健康志愿者。Previous study indicates that refined fuzzy entropy（r Fuzzy En）based on physical fuzzy membership function,improves significantly in terms of both stability and robustness against additive noise. Its performance in analysing cardiac electro-mechanical time series is further examined by the analysis of RR Interval（RRI）and Systolic Time Interval（STI）series in 5 minutes. Meanwhile, a refined cross fuzzy entropy（r C-FuzzyEn） is developed by substituting the physical fuzzy membership function for the ideal fuzzy membership function in cross fuzzy entropy（C-FuzzyEn）measure. It is used to analyse the coupling of RRI and STI between patients with coronary artery disease（CAD）and healthy volunteers,compared with cross sample entropy（C-Samp En）and cross fuzzy entropy（C-FuzzyEn）simutaneously. The results indicate that r C-FuzzyEn can be used to discriminate between CAD patients and healthy volunteers, it performs better than C-Samp En and C-FuzzyEn in discriminating the two groups.

关 键 词：物理模糊隶属度函数 改进模糊熵 改进互模糊熵 耦合性分析 心动周期 收缩间期 

分 类 号：TN911[电子电信—通信与信息系统]