利用Lyapunov指数提取心电动态生理及病理信息的研究

Lyapunov Exponent for Extracting Heart Dynamics

对心电信号的研究，一般都集中在对个别异常波形进行检测和识别从而判断心脏病变方面。而心电波形及其Ｒ－Ｒ间期序列的Ｌｙａｐｕｎｏｖ指数反映了心脏的总体动态特征。利用ＭＩＴ－ＢＩＨ数据库进行的初步研究表明：１）正常人、室性失常病人和束支传导阻滞病人的心电波形的Ｌｙａｐｕｎｏｖ指数有显著差别；２）正常人和室性失常病人的Ｒ－Ｒ间期序列的Ｌｙｓｐｕｎｏｖ指数有显著差别，正常人和束支传导阻滞病人的Ｒ－Ｒ间期序列的Ｌｙａｐｕｎｏｖ指数没有显著差别。值得指出的是，这一研究的前景在于，当心电信号中的异常波形还不足以被识别时，有可能利用Ｌｙａｐｕｎｏｖ指数进行早期诊断。

Research of human electrocardiogram (ECG) has been generally concentrated on the detection and recognition of individual abnormal waveform. In fact, the abnormal ECG is not only abnormal 'at the abnormal heart beats, but also abnormal as a whole. It has been shown that the heart is a chaotic oscillator. Therefore, it is appropriate to use the Lyapunov exponent, an important parameter to identify the nature of non-linear dynamical systems, for identifying the state of human heart. Preliminary results are obitained in this paper using Wolf's algorithm for 10 normal and 10 abnormal ECG recordings selected from the MIT-BIH database.1)Significant differences are found between the Lyapunov exponents of normal ECG, ECG with premature ventricular contraction(PVC), and ECG with bundle branch block (BBB).2)Significant difference is also found between the Lyapunov exponents of R-R interval series of normal ECG and ECG with PVC. But there is no significant difference between the Lyapunov exponents of tEe R-R interval series of normal ECG and ECG with BBB.It is apparent that the Lyapunov exPOnents of ECG and R-R interval series are the appropriate parameters for the identification of the physiological or pathological states of human heart. The attractive prospect of the research is that it is possible to use Lyapunov exponent for early diagnosis of heart diseases.