Multiscale probability density function analysis: Non-Gaussian and scale-invariant fluctuations of healthy human heart rate
Multiscale probability density function analysis: Non-Gaussian and scale-invariant fluctuations of healthy human heart rate
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DOI：
10.1109/tbme.2005.859804
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发表时间：
2006-01-01
影响因子：
4.6
通讯作者：
Yamamoto, Y
中科院分区：
文献类型：
--
作者：
Kiyono, K;Struzik, ZR;Yamamoto, Y
为了详细描述人类心率的非线性和非高斯性，我们引入了一种分析方法来研究去趋势增量的概率密度函数（PDF）从细尺度到粗尺度的变形过程。为了表征多尺度概率密度函数的尺度依赖性，我们采用了两种方法：1）计算Kullback-Leibler相对熵; 2）基于Castaing方程（B. Castaing等人，1990年）。我们比较了实际心率波动和人工产生的高斯和非高斯噪声之间的增量PDF的尺度依赖性，包括广泛使用的自回归模型和最近提出的基于随机级联过程的多重分形模型。我们的分析突出了心率波动与其他模型产生的心率波动之间的本质区别。人类心率的突出特征是非高斯PDF的鲁棒尺度不变性，其不仅在静止条件下保持，而且在清醒时间期间的动态状态下也保持，其中心率的平均水平急剧变化。我们的研究结果强烈建议需要修改现有的心率变异性模型，将标度不变性的PDF。
For a detailed characterization of intermittency and non-Gaussianity of human heart rate, we introduce an analysis method to investigate the deformation process of the probability density function (PDF) of detrended increments when going from fine to coarse scales. To characterize the scale dependence of the multiscale PDF, we use two methods: 1) calculation of Kullback-Leibler relative entropy; 2) parameter estimation based on Castaing's equation (B. Castaing et al., 1990). We compare scale-dependence of the increment PDFs between actual heart rate fluctuations and artificially generated Gaussian and non-Gaussian noise, including a widely used autoregressive model and a recently proposed multifractal model based on a random cascade process. Our analysis highlights an essential difference between heart rate fluctuations and those generated by other models. The outstanding feature of human heart rate is the robust scale-invariance of the non-Gaussian PDF, which is preserved not only in a quiescent condition, but also in a dynamic state during waking hours, in which the mean level of heart rate is dramatically changing. Our results strongly suggest the need for revising existing models of heart rate variability to incorporate the scale-invariance in the PDF.