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生理时间序列复杂波动的自适应数据分析

ADAPTIVE DATA ANALYSIS OF COMPLEX FLUCTUATIONS IN PHYSIOLOGIC TIME SERIES.

作者信息

Peng C-K, Costa Madalena, Goldberger Ary L

机构信息

Margret & H.A. Rey Institute of Nonlinear Dynamics in Physiology and Medicine Division of Interdisciplinary Medicine and Biotechnology Beth Israel Deaconess Medical Center Harvard Medical School 330 Brookline Ave., Boston, MA 02215, USA.

出版信息

Adv Adapt Data Anal. 2009 Jan 1;1(1):61-70. doi: 10.1142/S1793536909000035.

DOI:10.1142/S1793536909000035
PMID:20041035
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2798133/
Abstract

We introduce a generic framework of dynamical complexity to understand and quantify fluctuations of physiologic time series. In particular, we discuss the importance of applying adaptive data analysis techniques, such as the empirical mode decomposition algorithm, to address the challenges of nonlinearity and nonstationarity that are typically exhibited in biological fluctuations.

摘要

我们引入了一个动态复杂性的通用框架，以理解和量化生理时间序列的波动。特别是，我们讨论了应用自适应数据分析技术（如经验模式分解算法）来应对生物波动中典型表现出的非线性和非平稳性挑战的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3a3/2798133/7d12468fd3e4/nihms-132018-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3a3/2798133/7d12468fd3e4/nihms-132018-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3a3/2798133/7d12468fd3e4/nihms-132018-f0001.jpg

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