Engineering analysis of biological variables: An example of blood pressure over 1 day
Engineering analysis of biological variables: An example of blood pressure over 1 day
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DOI：
10.1073/pnas.95.9.4816
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发表时间：
1998-04-28
影响因子：
11.1
通讯作者：
Fung, YC
中科院分区：
文献类型：
--
作者：
Huang, W;Shen, Z;Fung, YC
生物学中几乎所有的变量都是非平稳随机的，对于这些变量，传统的工具给我们留下的感觉是一些有价值的信息被丢弃，复杂的现象被不精确地呈现。在这里，我们应用最初在海浪研究中取得的最新进展来研究肺部的血压波。我们首先注意到，在长波列中，局部均值的处理至关重要。结果表明，信号可以通过一系列固有模式函数的总和来描述，每个固有模式函数始终具有零局部均值。嘲笑这一系列的过程被称为“经验模态分解法”。传统上，傅立叶分析通过正弦和余弦函数表示数据，但无法定义瞬时频率。在新的方式中，数据由固有模式函数表示，可以使用希尔伯特变换。 Titchmarsh [Titchmarsh, E, C, (1948) 傅里叶积分理论简介（牛津大学出版社，牛津）] 表明，信号和 i 次希尔伯特变换一起定义了一个复变量，从该复变量中定义了瞬时频率、瞬时幅度、希尔伯特谱和边际希尔伯特谱，此外还应用了冈贝尔极值统计。我们在这里展示血压记录的所有这些特征，供读者查看它们的外观。将来，我必须了解这些特征如何随着疾病或干预措施而变化。
Almost all variables in biology are nonstationarily stochastic, For these variables, the conventional tools leave us a feeling that some valuable information is thrown away and that a complex phenomenon is presented imprecisely. Here, we apply recent advances initially made in the study of ocean waves to study the blood pressure waves in the lung. We note first that, in a long wave train, the handling of the local mean is of predominant importance. It is shown that a signal can be described by a sum of a series of intrinsic mode functions, each of which has zero local mean at all times. The process of deriding this series is called the "empirical mode decomposition method." Conventionally, Fourier analysis represents the data by sine and cosine functions, but no instantaneous frequency can be defined. In the new way, the data are represented by intrinsic mode functions, to which Hilbert transform can be used. Titchmarsh [Titchmarsh, E, C, (1948) Introduction to the Theory of Fourier Integrals (Oxford Univ. Press, Oxford)] has shown that a signal and i times its Hilbert transform together define a complex variable, From that complex variable, the instantaneous frequency, instantaneous amplitude, Hilbert spectrum, and marginal Hilbert spectrum have been defined, In addition, the Gumbel extreme-value statistics are applied. We present all of these features of the blood pressure records here for the reader to see how they look In the future, me have to learn how these features change with disease or interventions.