Application of DFA to heart rate variability

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Presentation transcript:

Application of DFA to heart rate variability Mariusz Sozański*, Jan Żebrowski*, Rafał Baranowski+ Application of DFA to heart rate variability *Faculty of Physics, Warsaw University of Technology +National Institute of Cardiology, Warsaw

1. Intro – overview of DFA 1. Intro – overview of DFA RR

1. Intro – overview of DFA

1. Intro – overview of the method If we observe scaling: We may conclude that: For a=0.5 fluctuations are not self-correlated; For 0.5<a<1 long-range correlations exist; For 0<a<0.5 long-range anticorrelations exist; a=1 corresponds to flicker (1/f) noise; a=1.5 corresponds to Brownian noise; In other words: the „smoother” the time series, the bigger a is obtained.

2. Scale-independent DFA *Goldberger,Peng et al., PNAS 99, supp.1, 2466(2002)

2. Scale-dependent version *K. Saermark et al., Fractals 8, 4, 315-322 (2000).

3. coronary disease scale-independent scale-dependent

3. cardiomiopathy scale-independent scale-dependent

3. cardiac infarction scale-independent scale-dependent

3. cardiac infarction window length=16 RR window length=8 RR

4. Comparison with SDNN

THANK YOU FOR YOUR ATTENTION!