ADAPTIVE DATA ANALYSIS OF COMPLEX FLUCTUATIONS IN PHYSIOLOGIC TIME SERIES

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 nonlin...

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Veröffentlicht in:	Advances in adaptive data analysis Jg. 1; H. 1; S. 61
Hauptverfasser:	Peng, C-K, Costa, Madalena, Goldberger, Ary L
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 01.01.2009
ISSN:	1947-9840
Online-Zugang:	Weitere Angaben
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Beschreibung
Zusammenfassung:	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.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1947-9840
DOI:	10.1142/s1793536909000035