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Nonlinear time series analysis of electrocardiograms.
MedLine Citation:
PMID:  12780161     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
In recent years there has been an increasing number of papers in the literature, applying the methods and techniques of Nonlinear Dynamics to the time series of electrical activity in normal electrocardiograms (ECGs) of various human subjects. Most of these studies are based primarily on correlation dimension estimates, and conclude that the dynamics of the ECG signal is deterministic and occurs on a chaotic attractor, whose dimension can distinguish between healthy and severely malfunctioning cases. In this paper, we first demonstrate that correlation dimension calculations must be used with care, as they do not always yield reliable estimates of the attractor's "dimension." We then carry out a number of additional tests (time differencing, smoothing, principal component analysis, surrogate data analysis, etc.) on the ECGs of three "normal" subjects and three "heavy smokers" at rest and after mild exercising, whose cardiac rhythms look very similar. Our main conclusion is that no major dynamical differences are evident in these signals. A preliminary estimate of three to four basic variables governing the dynamics (based on correlation dimension calculations) is updated to five to six, when temporal correlations between points are removed. Finally, in almost all cases, the transition between resting and mild exercising seems to imply a small increase in the complexity of cardiac dynamics. (c) 1995 American Institute of Physics.
Authors:
A. Bezerianos; T. Bountis; G. Papaioannou; P. Polydoropoulos
Publication Detail:
Type:  JOURNAL ARTICLE    
Journal Detail:
Title:  Chaos (Woodbury, N.Y.)     Volume:  5     ISSN:  1089-7682     ISO Abbreviation:  Chaos     Publication Date:  1995 Mar 
Date Detail:
Created Date:  2003-Jun-3     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100971574     Medline TA:  Chaos     Country:  -    
Other Details:
Languages:  ENG     Pagination:  95-101     Citation Subset:  -    
Affiliation:
University of Patras, 261 10 Patras, Greece.
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