摘要
目的利用基于复杂网络理论的心率变异性(heart rate variability,HRV)分析方法来探索高血压所致的心搏动力学变化,为评估高血压患者的心血管系统功能提供新思路。方法分析了来自于中国人民解放军第414医院的17例原发性高血压患者以及17例健康老年人的HRV数据:首先利用相空间重构、内组合排列和替代数据方法将高血压患者组和健康对照组的极短时心率变异性序列(50点)从时间域转换至网络域,然后分析网络拓扑特性,计算了4个基本的网络特征参数,即效率、聚类系数、平均度和度分布熵。结果高血压组的3个网络特征参数,即效率、平均度、度分布熵的值相比对照组存在着显著下降(P<0.05),其中尤以度分布熵参数最为明显;聚类系数相比对照组存在着接近显著的下降(P=0.055)。结论高血压患者的心跳动力系统可能发生了两个改变:一是既可以整体协作又能局部专注的经济型工作模式遭到破坏;二是在不同时刻之间的非线性耦合性减弱。
Objective We adopt heart rate variability （HRV） analysis method based on complex network theory to explore the variability of heartbeat kinetic caused by hypertension, which provides new thoughts to evaluate the cardiovascular system function for hypertensive patients. Methods This paper analyzes the HRV data from 17 cases of primary hypertension patients （from the 414th Hospital of Chinese People＇ s Liberation Army） and 17 cases of healthy older people. Firstly, by adopting phase space reconstruction, internal combined arrangement and surrogate data method, the very short-term heart rate variability sequence （50 points） of hypertension patients group and healthy control group are converted from time domain to network domain. Then we analyze the topological characteristic of network, and calculate the four fundamental network characteristic parameters ： efficiency, clustering coefficient, average degrees and distribution entropy value. Results Three network character parameters of hypertension group, namely efficiency, average degree and distribution entropy values, significantly decrease in comparison with the healthy control group （ P 〈 0. 05 ）, especially for the distribution entropy parameter. The decrease of clustering coefficient in hypertension group isclose to significant in comparison with the healthy control group （P = 0. 055 ）. Conclusions Two changes may occur for the heartbeat dynamic systems of hypertensive patients： one is that the economic operation mode, which allows system both in overall collaboration and local focus,is destroyed;second is that the nonlinear and coupling of system at different times is weakened.
出处
《北京生物医学工程》
2016年第3期272-276,共5页
Beijing Biomedical Engineering
基金
国家自然科学基金(61401518)
江苏省自然科学基金(BK20141432)
中国药科大学中央高校基本科研业务费专项资金资助
关键词
心血管系统
复杂网络
非线性动力学
高血压
心率变异性
cardiovascular system
complex network
nonlinear dynamics
hypertension
heart ratevariability
