Generalized Multiscale Entropy Analysis: Application to Quantifying the Complex Volatility of Human Heartbeat Time Series.
Generalized Multiscale Entropy Analysis: Application to Quantifying the Complex Volatility of Human Heartbeat Time Series.
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DOI：
10.3390/e17031197
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发表时间：
2015-03
期刊：
影响因子：
--
通讯作者：
Goldberger AL
中科院分区：
文献类型：
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作者：
Costa MD;Goldberger AL
介绍了多尺度熵(MSE)分析的推广。该方法被称为mSen，其中下标表示用于对时间序列进行粗粒度处理的时刻。MSEμ，如前所述，使用平均值(一阶矩)。这里，我们关注的是，它使用的是二阶矩，即方差。量化信号在多个时间尺度上的波动性(方差)的动态。利用该方法对心跳时间序列的结构进行了分析。我们发现，健康年轻受试者的心跳时间序列的波动性是非常复杂的。此外，我们发现，波动率的多尺度复杂性，而不仅仅是平均心率的多尺度复杂性，随着年龄和病理的变化而降低。动力学的“突发性”行为可能与能量和信息流的间歇性有关，作为多尺度激活和恢复周期的一部分。广义均方误差也可用于量化其他生理学和非生理学时间序列的动力学特性。
We introduce a generalization of multiscale entropy (MSE) analysis. The method is termed MSEn, where the subscript denotes the moment used to coarse-grain a time series. MSEμ, described previously, uses the mean value (first moment). Here, we focus on , which uses the second moment, i.e., the variance. quantifies the dynamics of the volatility (variance) of a signal over multiple time scales. We use the method to analyze the structure of heartbeat time series. We find that the dynamics of the volatility of heartbeat time series obtained from healthy young subjects is highly complex. Furthermore, we find that the multiscale complexity of the volatility, not only the multiscale complexity of the mean heart rate, degrades with aging and pathology. The “bursty” behavior of the dynamics may be related to intermittency in energy and information flows, as part of multiscale cycles of activation and recovery. Generalized MSE may also be useful in quantifying the dynamical properties of other physiologic and of non-physiologic time series.