心电图是心肌缺血检测的一种方便、经济、无创的工具,其主要的临床表现为ST-T段变化.鉴于心脏是一个混沌系统,本文从非线性角度出发,对心电图特征参数序列进行分形维数和最大Lyapunov指数分析,其中特征参数序列包括:心电图RR间期,瞬时心率HR(heart rate),ST段的平均幅值STmean,ST段最小幅值STmin,STmean与HR的比值STr,T波峰末间期TpTe,R波峰值Ramp,T波峰值Tamp.利用公共数据库Long-term ST database(LTST)中心肌缺血和非心肌缺血心电数据,通过统计t检验分析,除最大分形维数分析中的TpTe与最大Lyapunov指数分析中的Ramp和Tamp特征参数外,其余参数均有显著性差异.基于心电图的非线性分析为心肌缺血检测与诊断提供另一重要依据.%Electrocardiogram (ECG) is a convenient, economic, and non-invasive detecting tool for myocardial ischemia (MI) , and its clinical appearance is mainly exhibited by ST - T complex changes. In view of the fact that the heart is a chaos system, the nonlinear parameters of fractal dimensions and largest Lyapunov exponents were used to analyze some derived feature sequences in ECG in this paper. These feature sequences included ECG RR interval, transient heart rate (HR) , average amplitude of ST-segment (ST ) , minimum amplitude of ST-segment (STmin), the rate of ST and HR (STr), T apex T end (TpTe), R-wave peak amplitude (Ramp) , and T-wave peak amplitude ( Tamp ). We statistically analyzed the ECG signals of patients with myocardial ischemia and healthy persons from long-term ST data base (LTST) with T test, and as a result,significant differences of all feature sequences were obtained except the feature of TpTe by fractal dimensions analysis, Ramp and Tamp by Lyapunov exponents analysis. Therefore the nonlinear analysis based on ECG provided a reliable basis for detection and diagnosis of myocardial ischemia.
展开▼
