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Normalized correlation dimension for heart rate variability analysis

  • Corinna Raab , Jürgen Kurths , Alexander Schirdewan und Niels Wessel
Veröffentlicht/Copyright: 25. Oktober 2006
Veröffentlichen auch Sie bei De Gruyter Brill
Biomedical Engineering / Biomedizinische Technik
Aus der Zeitschrift Band 51 Heft 4

Abstract

In this paper we use the concept of large-scale dimension densities to analyze heart rate variability data. This method uses a normalized Grassberger-Procaccia algorithm and estimates the dimension in the rather large scales of the system. This enables us to analyze very short data. First we reanalyze data from the CIC 2002 challenge and can completely distinguish between real data and computer-generated data using only one parameter. We then analyze unfiltered data for 15 patients with atrial fibrillation (AF), 15 patients with congestive heart failure (CHF), 15 elderly healthy subjects, and 18 young healthy subjects. This method can completely separate the AF group from the other groups and the CHF patients show significant differences compared to the young and elderly healthy volunteers. Furthermore, differences are evident in the dimensionality between day and night for healthy persons, but not for the CHF patients. Finally, the results are compared to standard heart rate variability parameters.


Corresponding author: Dr. Niels Wessel, Universität Potsdam, Institut für Physik, AG NLD–Kardiovaskuläre Physik, Postfach 601553, 14415 Potsdam, Germany Phone: +49-331-9771639 or +49-30-94172450 Fax: +49-331-977-1142

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Published Online: 2006-10-25
Published in Print: 2006-10-01

©2006 by Walter de Gruyter Berlin New York

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