东北大学学报（自然科学版）

东北大学学报:自然科学版 ›› 2014, Vol. 35 ›› Issue (11): 1525-1529.DOI: 10.12068/j.issn.1005-3026.2014.11.002

• 信息与控制 • 上一篇    下一篇

基于粒子滤波的多导心电信号的T波交替分析算法

佘黎煌，王鸿雁，王明全，张石   

  1. (东北大学 信息科学与工程学院， 辽宁 沈阳110819)
  • 收稿日期:2013-05-23 修回日期:2013-05-23 出版日期:2014-11-15 发布日期:2014-07-03
  • 通讯作者: 佘黎煌
  • 作者简介:佘黎煌(1980-)，男，福建莆田人，东北大学讲师，博士;张石(1963-)，男，辽宁抚顺人，东北大学教授.
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(N110404003，N130404005)；辽宁省自然科学基金资助项目(20102057)；国家高技术研究发展计划项目(2012AA062201)；辽宁省博士启动基金资助项目(20131028).

Multilead Analysis of T Wave Alternans in the ECG Using Particle Filtering

SHE Lihuang， WANG Hongyan， WANG Mingquan， ZHANG Shi   

  1. School of Information Science & Engineering， Northeastern University， Shenyang 110819， China.
  • Received:2013-05-23 Revised:2013-05-23 Online:2014-11-15 Published:2014-07-03
  • Contact: SHE Lihuang
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摘要： 对于多导心电信号中非稳态和非高斯的T波交替(Twavealternans，TWA)现象的分析，现有的方法都存在稳健性差的问题.提出了一种基于粒子滤波的多导联TWA分析方法，根据多导联TWA的分析框架，对经过预处理后得到的多导联ST-T段数据首先进行主成分分析，然后采用粒子滤波的方法对变换后每个通道进行TWA检测和对重构后的各导联进行TWA幅值估计，从而实现多导联T波交替的分析.仿真实验结果表明，当交替信号与噪声的比小于-15dB，多导联的粒子滤波方法的估计TWA幅值准确度高，并且没有出现TWA的漏检和误检情况.同时，对非稳态和非高斯的TWA具有很好的稳健性和抗噪性能.

关键词: 多导联心电信号, T波交替, 粒子滤波, 主成分分析, 拉普拉斯噪声

Abstract: The current methods for analyzing the nonstationary and nongaussian TWA of automatically detecting and estimating T wave alternans (TWA) in multilead ECG have poor sensitivity to nonstationary and lowamplitude. The particle filtering (PF) method combined with joint analysis information was proposed to detect and estimate multilead TWA. According to a multilead TWA analysis scheme， a linear transformation using principal component analysis was processed on the preprocessed multilead STT complex. Then PFbased method was applied to each lead for TWA detection and estimation. To evaluate the proposed method， multilead PF method was compared to single lead PF and spectral method. The simulation results showed that the proposed method had the best performance on detection and estimation of TWA when the alternanssignaltonoise ratio was lower than -15dB. For nonstationary and nongaussian TWA， the proposed method had good robustness and high antinoise ability.

Key words: multilead ECG, T wave alternans, particle filtering, PCA, Laplacian noise

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