基于估计熵确定心率变异信号中动力噪声强度

ESTIMATING STRENGTH OF DYNAMICAL NOISES IN HEART RATEVARIABILITY BASED ON APPROXIMATE ENTROPY

目前普遍的观点认为心率变异信号是确定性低维混沌系统产生的，同时该系统受到大量生理噪声的影响。研究了观测噪声和动力噪声对低维混沌系统的影响，提出了一种基于复杂性度量动力噪声强度刻划方法，表明随着动力噪声强度的增加，系统的复杂程度增加。该方法不需要对动力学系统完全重建，并对观测噪声具有一定鲁棒性。最后利用３类共５３只狗的心电图，每只狗的心电数据为１０００个Ｒ－Ｒ间期的微分序列检验了该算法。分析表明。

It is by now widely appreciated that normal heart rhythms show features of deterministic chaos. Which is also corrupted by a great deal of physiological noises from surroundings. We study the effects of measurement and dynamical noises on low-dimensional chaotic systems, and present a numerical algorithm for estimating to what extent, heart rhythm is dynamical noise corrupted based on complexity. Further analysis shows that adding increasing amounts of dynamical noise increasingly develops the complexity of cardiac dynamics. The method dose not need to fully reconstruct an attractor. So it is robust to measurement noise. Finally Electrocardiograms were recorded of 53 dogs falling into three groups and used to test the algorithm. From the measured R-R intervals, a time series of 1000 first differential was constructed for each subject. Further analysis reveals that the estimated strength of dynamical noises appears to be correlated with different case.