中国组织工程研究

中国组织工程研究 ›› 2010, Vol. 14 ›› Issue (9): 1645-1648.doi: 10.3969/j.issn.1673-8225.2010.09.029

• 数字化骨科 • 上一篇    下一篇

T波交替散点图法：利用非线性动力学系统表示周期性的散点图

徐舫舟1，赵 捷1，王纪奎1，李 群1，田 杰1，唐文涛2   

  1. 1山东师范大学物理与电子科学学院，山东省济南市   250014；
    2荆门理工学院电子信息工程学院，湖北省荆门市 448000
  • 出版日期:2010-02-26 发布日期:2010-02-26
  • 作者简介:徐舫舟，女，1980年生，山东省新泰市人，汉族，2010年山东师范大学毕业，硕士，主要从事智能信号与信息处理方面的研究。 matinaxu@163.com
  • 基金资助:

    课题受山东省科技攻关项目(2007GG 10001018)及山东省自然科学基金(Y2007G05)资助。

Poincare mapping method for T-wave alternans using a nonlinear dynamic system

Xu Fang-zhou1, Zhao Jie1, Wang Ji-kui1, Li Qun1, Tian Jie1, Tang Wen-tao2   

  1. 1School of Physics and Electronics, Shandong Normal University, Jinan   250014, Shandong Province, China;
    2School of Electronics and Information Engineering, Jingmen Technical College, Jingmen   448000, Hubei Province, China
  • Online:2010-02-26 Published:2010-02-26
  • About author:Xu Fang-zhou, Master, School of Physics and Electronics, Shandong Normal University, Jinan 250014, Shandong Province, China matinaxu@163.com
  • Supported by:

    the Science and Technology Development Program of Shandong Province, No. 2007GG1 0001018*; the Natural Science Foundation of Shandong Province, No. Y2007G05*

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摘要：

背景：微伏级T波交替是预测室性心律失常的重要指标，有望发展成为一种优越的无创评定发生恶性室性心率失常及猝死危险性的技术。
目的：介绍一种利用非线性动力学系统表示周期性的散点图法从而进行T波交替检测的算法。
方法：选取连续心跳周期中T波窗口内的采样点序列做散点图，描述T波交替的分布状态。根据奇数序列和偶数序列到原点的距离之和 判断T波交替的存在与否。
结果与结论：将算法应用到美国MIT/BIH标准心律失常数据库和欧洲ST-T心电数据库进行仿真，将所得到离散数据 和谱分析法中表示T波电交替幅值的 进行相关性分析得到相关系数 。证明该算法能够精确简便地判断T波电交替，可为T波电交替散点图法的深入研究提供思路。

关键词: 散点图法, T波交替, 谱分析法, 心电图, 小波变换, 数字化心血管技术

Abstract:

BACKGROUND: The microvolt T-wave alternans (MTWA) is an important index for ventricular arrhythmias prediction and is a promising tool to evaluate non-invasively malignant ventricular arrhythmia and risk of sudden death.
OBJECTIVE: To introduce a algorithm for detecting TWA using Poincare mapping method (PM), which is a technique for dynamics systems to display periodic behavior.
METHODS: Samples series of beat to beat cycles were selected to prepare Poincare mapping to describe TWA distribution.  , which denoted the sum distances between the origin to even and odd series, was used to present the presence and absence of TWA.
RESULTS AND CONCLUSION: This algorithm was applied in MIT/BIH Arrhythmia database and European ECG ST-T database, and  was used for correlation analysis with , which denoted TWA amplitude of Spectrum Method. The cross-correlation coefficient was . The algorithm can identify the absence and presence of TWA accurately and provide idea for further study of TWA-PM.

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