相态距分析和在短时RR-QT间期耦合性评价中的应用研究

Cardiovascular system is characterized by a typical adaptive and feedback control network. Investigating its network properties is of great help for a better understanding of the cardiovascular control mechanism. We proposed to develop an inter-state distance analysis (ISDA) method and a k-order ISDA method in this project. We further proposed to investigate the short-term electrocardiographic RR interval-QT interval coupling (RQC), which is a typical network property, based on the ISDA and k-order ISDA methods, with an aim of exploring the aging and heart failure effects on RQC and k-order RQC. Accomplishment of this project may provide novel ideas and methods for the noninvasive evaluation of cardiovascular risk..Specific aims:.1) To develop a novel ISDA method by mapping inter-state distance series from the original time-series followed by symbolic quantification of inter-state distance series. The mapping of joint inter-state distance series from bivariate or multivariate time-series will also be investigated in order to generalize ISDA to bivariate or multivariate cases..2) To investigate the action time k-mediated mapping method of inter-state distance series and to develop a k-order ISDA method..3) To explore the aging and heart failure effects on RQC based on ISDA. The interaction factor between aging and heart failure will also be investigated..4) To explore the relation of RQC with the action time k and to explore how the immediate effect and long-time memory effect of cardiovascular control can be described by k-order RQC, based on which the aging and heart failure effects on RQC at different action time k will be investigated.

心血管系统呈现典型的自适应反馈网络调节，研究其网络属性有助于理解心血管系统的调控状态。本项目提出相态距和k阶相态距分析，并用于研究短时心电RR-QT间期耦合性这一网络特征，探索年龄和心衰如何影响RR-QT间期耦合性和作用时间k介导的耦合性，为无创评价心血管风险提供创新思路和方法。.主要内容：1)研究时间序列映射相态距序列的方法，研究多变量时间序列的联合相态距序列映射方法，探索相态距序列的符号量化算法，提出相态距分析；2)探索作用时间k介导的相态距序列映射方法，建立k阶相态距分析；3)使用联合相态距分析方法，研究短时心电RR-QT间期耦合性随年龄的变化和在心衰患者中的变化，探索年龄和心衰交互因素对RR-QT间期耦合性的影响；4)探索RR-QT间期耦合性与作用时间k之间的函数关系，探索系统调控的即时和记忆效应在RR-QT间期耦合性上的体现，研究年龄和心衰如何影响不同k时的RR-QT间期耦合性。

健康状态下的心血管系统活动具有高度的复杂特性，呈现典型的网络耦合特征。研究通过心血管系统的输出定量评估其复杂的调控状态，理解其不同的调控节点或系统节点之间的网络耦合属性，有助于理解心血管系统的健康状态，并有助于对潜在心血管疾病和恶性事件作出早期、无创无损的评估和检测。本项目主要研究内容包括：对现有非线性动力学时间序列的熵测度进行了系统严谨的算法仿真和对比，明确了各算法评价心血管自主神经活动中的表现，原创提出了由作用时间k和作用半径δ介导的k-δ相态距分析理论；基于维度为1的相空间重构研究了心电RR间期序列的对称性，提出了基于短时数据度量对称性的稳健算法——面积指标，研究了该参数在心律失常病人和心衰病人中的变化情况，并结合相态距的熵分析，建立了栅格熵指标，研究了一维相态距图的对称性在心衰患者中的变化；发展了双变量相态距的熵分析，分别使用单变量和双变量分析研究了心电信号RR间期、QT间期时间序列和RR-QT耦合性在不同生理状态（静息、运动）和心血管病理状态（心衰和冠心病）下的变化情况，集中研究了QT间期时间序列的相态距熵分析在冠心病合并心肌梗死病人中的变化；攥写了相态距分析开源软件“时间序列熵分析软件”，并取得知识产权登记证书；创新性地提出了电机械延迟时间变异性（Electro-Mechanical Delay Variability, EMDV）的概念，研究了EMDV的相态距分析在冠心病检测中的应用，结合单变量和双变量分析构建了无创检测冠心病的网络模型。项目研究成果为无创评价心血管风险提供了创新思路和方法。