动态心电图中R波峰序列的Lyapunov指数谱

LYAPUNOV SPECTRUM OF R-PEAKS SERIES IN DYNAMIC ELECTROCARDIOGRAM

本文介绍了计算机Lyapunov指数谱的方法 ,利用MIT BIH心电数据库 ,计算了其中正常心律、起搏心律、室早搏心律和束支传导阻滞心律四组共 2 4例心电图数据中R波峰序列的Lyapunov指数谱 ,提出了收敛发散比的定义 ,并以此来衡量系统整体特性。研究结果表明 ,正常心律和异常心律以及异常心律之间 ,R波峰序列的Lyapunov指数谱和收敛发散比有差异 ,这显示了不同状态下 ,心脏R波峰序列具有不同动力学特征。为进一步结合其他分析方法全面研究心脏活动状态的特征提供理论基础 ,对将来在临床上应用于早期诊断心脏疾病具有重要意义。

Selected 24 data files of ECG from MITBIH database and divided these data files into four groups. They were normal ECG, pacing ECG, ECG with premature ventricular contraction, and ECG with bundle branch block. Series of Rpeaks extracted from these electrocardiograms were analyzed with Lyapunov spectrum. Define CD as the Ratio of ConvergencyDivergency, which scaled the integral dynamic characterizations of systems. The results showed that the Lyapunov exponents spectrum and Ratio of ConvergencyDivergency were different between the normal ECG and other three abnormal ECG. The CD of series of Rpeaks from normal hearts were smal ler than that of other three abnormal ECG. This implied the normal health hearts had more physiological adaptabilities than abnormal hearts. Used the methods of Lyapunov exponents spectrum to extract dynamic characteristics from Rpeaks series of ECG so as to research active states of heart and might help doctors clinical applications for early diagnosis of diseases of heart in future.