Literature DB >> 7548313

General relation between variance-time curve and power spectral density for point processes exhibiting 1/f beta-fluctuations, with special reference to heart rate variability.

R Scharf1, M Meesmann, J Boese, D R Chialvo, K D Kniffki.   

Abstract

Counting statistics in the form of the variance-time curve provides an alternative to spectral analysis for point processes exhibiting 1/f beta-fluctuations, such as the heart beat. However, this is true only for beta < 1. Here, the case of general beta is considered. To that end, the mathematical relation between the variance-time curve and power spectral density in the presence of 1/f beta-noise is worked out in detail. A modified version of the variance-time curve is presented, which allows us to deal also with the case beta > or = 1. Some applications to the analysis of heart rate variability are given.

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Year:  1995        PMID: 7548313     DOI: 10.1007/bf00201427

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  10 in total

1.  Analysis of long term heart rate variability: methods, 1/f scaling and implications.

Authors:  J P Saul; P Albrecht; R D Berger; R J Cohen
Journal:  Comput Cardiol       Date:  1988

2.  Rate fluctuations and fractional power-law noise recorded from cells in the lower auditory pathway of the cat.

Authors:  M C Teich; D H Johnson; A R Kumar; R G Turcott
Journal:  Hear Res       Date:  1990-06       Impact factor: 3.208

3.  Frequency domain measures of heart period variability and mortality after myocardial infarction.

Authors:  J T Bigger; J L Fleiss; R C Steinman; L M Rolnitzky; R E Kleiger; J N Rottman
Journal:  Circulation       Date:  1992-01       Impact factor: 29.690

4.  An efficient algorithm for spectral analysis of heart rate variability.

Authors:  R D Berger; S Akselrod; D Gordon; R J Cohen
Journal:  IEEE Trans Biomed Eng       Date:  1986-09       Impact factor: 4.538

5.  Alias-free sampling of neuronal spike trains.

Authors:  A S French; A V Holden
Journal:  Kybernetik       Date:  1971-05

6.  Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control.

Authors:  S Akselrod; D Gordon; F A Ubel; D C Shannon; A C Berger; R J Cohen
Journal:  Science       Date:  1981-07-10       Impact factor: 47.728

7.  A new method for analysis of heart rate variability: counting statistics of 1/f fluctuations.

Authors:  M Meesmann; F Grüneis; P Flachenecker; K D Kniffki
Journal:  Biol Cybern       Date:  1993       Impact factor: 2.086

8.  Comparing spectra of a series of point events particularly for heart rate variability data.

Authors:  R W DeBoer; J M Karemaker; J Strackee
Journal:  IEEE Trans Biomed Eng       Date:  1984-04       Impact factor: 4.538

9.  1/f fluctuation of heartbeat period.

Authors:  M Kobayashi; T Musha
Journal:  IEEE Trans Biomed Eng       Date:  1982-06       Impact factor: 4.538

10.  Frequency domain measures of heart period variability to assess risk late after myocardial infarction.

Authors:  J T Bigger; J L Fleiss; L M Rolnitzky; R C Steinman
Journal:  J Am Coll Cardiol       Date:  1993-03-01       Impact factor: 24.094

  10 in total
  5 in total

1.  Dynamics of excitability over extended timescales in cultured cortical neurons.

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Journal:  J Neurosci       Date:  2010-12-01       Impact factor: 6.167

2.  Fractal character of the electrocardiogram: distinguishing heart-failure and normal patients.

Authors:  R G Turcott; M C Teich
Journal:  Ann Biomed Eng       Date:  1996 Mar-Apr       Impact factor: 3.934

3.  Slow dynamics in features of synchronized neural network responses.

Authors:  Netta Haroush; Shimon Marom
Journal:  Front Comput Neurosci       Date:  2015-04-14       Impact factor: 2.380

4.  Synaptic dynamics contribute to long-term single neuron response fluctuations.

Authors:  Sebastian Reinartz; Istvan Biro; Asaf Gal; Michele Giugliano; Shimon Marom
Journal:  Front Neural Circuits       Date:  2014-07-01       Impact factor: 3.492

5.  Presence of a Chaotic Region at the Sleep-Wake Transition in a Simplified Thalamocortical Circuit Model.

Authors:  Kush Paul; Lawrence J Cauller; Daniel A Llano
Journal:  Front Comput Neurosci       Date:  2016-09-01       Impact factor: 2.380

  5 in total

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