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Entropy Measures in Heart Rate Variability Data

  • Niels Wessel
  • Agnes Schumann
  • Alexander Schirdewan
  • Andreas Voss
  • Jürgen Kurths
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1933)

Abstract

Standard parameters of heart rate variability are restricted in measuring linear effects, whereas nonlinear descriptions often suffer from the curse of dimensionality. An approach which might be capable of assessing complex properties is the calculation of entropy measures from normalised periodograms. Two concepts, both based on autoregressive spectral estimations are introduced here. To test the hypothesis that these entropy measures may improve the result of high risk stratification, they were applied to a clinical pilot study and to the data of patients with different cardiac diseases. The study shows that the entropy measures discussed here are useful tools to estimate the individual risk of patients suffering from heart failure. Further, the results demonstrate that the combination of different heart rate variability parameters leads to a better classification of cardiac diseases than single parameters.

Keywords

Heart Rate Variability Shannon Entropy Entropy Measure Heart Rate Variability Parameter Heart Rate Variability Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Niels Wessel
    • 1
  • Agnes Schumann
    • 2
  • Alexander Schirdewan
    • 3
  • Andreas Voss
    • 2
  • Jürgen Kurths
    • 1
  1. 1.University of PotsdamPotsdamGermany
  2. 2.University of Applied Sciences JenaJenaGermany
  3. 3.Franz-Volhard-HospitalHumboldt-University, BerlinBerlinGermany

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