Literature DB >> 8127277

Time series analysis of complex dynamics in physiology and medicine.

L Glass1, D Kaplan.   

Abstract

A variety of mathematical methods have been developed to characterize complex rhythms that are observed in physiological systems. These methods include classical techniques such as the mean, standard deviation, and power spectrum, as well as newer methods suggested by nonlinear dynamics including the dimension, Lyapunov number, and entropy. This paper reviews the various ways in which these measures have been applied to analyze physiological dynamics with emphasis on the potential advantages and pitfalls of the various approaches. We conclude that these methods may be useful to help characterize complex time series, but only rarely is it possible to use these methods to establish deterministic chaos in a given time series.

Mesh:

Year:  1993        PMID: 8127277

Source DB:  PubMed          Journal:  Med Prog Technol        ISSN: 0047-6552


  14 in total

1.  The "Chaos Theory" and nonlinear dynamics in heart rate variability analysis: does it work in short-time series in patients with coronary heart disease?

Authors:  Goran Krstacic; Antonija Krstacic; Anton Smalcelj; Davor Milicic; Mirjana Jembrek-Gostovic
Journal:  Ann Noninvasive Electrocardiol       Date:  2007-04       Impact factor: 1.468

2.  Low doses of ethanol reduce evidence for nonlinear structure in brain activity.

Authors:  C L Ehlers; J Havstad; D Prichard; J Theiler
Journal:  J Neurosci       Date:  1998-09-15       Impact factor: 6.167

3.  Lineage correlations of single cell division time as a probe of cell-cycle dynamics.

Authors:  Oded Sandler; Sivan Pearl Mizrahi; Noga Weiss; Oded Agam; Itamar Simon; Nathalie Q Balaban
Journal:  Nature       Date:  2015-03-11       Impact factor: 49.962

Review 4.  Optimal Perioperative Blood Pressure Management.

Authors:  Senthil Packiasabapathy K; Balachundhar Subramaniam
Journal:  Adv Anesth       Date:  2018-09-24

5.  Loss of adaptive capacity in asthmatic patients revealed by biomarker fluctuation dynamics after rhinovirus challenge.

Authors:  Anirban Sinha; René Lutter; Binbin Xu; Tamara Dekker; Barbara Dierdorp; Peter J Sterk; Urs Frey; Edgar Delgado Eckert
Journal:  Elife       Date:  2019-11-05       Impact factor: 8.140

6.  Correlation dimension analysis of Doppler signals in children with aortic valve disorders.

Authors:  Derya Yılmaz; N Fatma Güler
Journal:  J Med Syst       Date:  2009-05-15       Impact factor: 4.460

Review 7.  Oscillatory serotonin function in depression.

Authors:  Ronald M Salomon; Ronald L Cowan
Journal:  Synapse       Date:  2013-05-21       Impact factor: 2.562

8.  Detecting epileptic seizure with different feature extracting strategies using robust machine learning classification techniques by applying advance parameter optimization approach.

Authors:  Lal Hussain
Journal:  Cogn Neurodyn       Date:  2018-01-25       Impact factor: 5.082

9.  NETGEM: Network Embedded Temporal GEnerative Model for gene expression data.

Authors:  Vinay Jethava; Chiranjib Bhattacharyya; Devdatt Dubhashi; Goutham N Vemuri
Journal:  BMC Bioinformatics       Date:  2011-08-08       Impact factor: 3.169

Review 10.  Complex systems and the technology of variability analysis.

Authors:  Andrew J E Seely; Peter T Macklem
Journal:  Crit Care       Date:  2004-09-22       Impact factor: 9.097

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