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Methods for extracting self-similarity properties from Heart Rate Variability signal in Normal and Heart Failure Patients

Author(s):

M. Bellotti
Conference/Journal:

Computers in Cardiology, Hannover, Germany, vol. 26, pp. 527-530
Abstract:

We propose new methods for the extraction of self-similarity characteristics from 24-hour Heart Rate Variability signals (HRV). The first method is deduced from the "Second Order Difference plot": the distribution dispersion obtained by a sequence HRV appears to be an estimation of the lomg-term correlation (H) of the signal. The second method (CYCLES) provides a decomposition of the self-similarity characteristics as function of the time scales. We analyze 10 Normal, 10 Heart Failure (HF) and 2 transplanted subjects. Results show that, in normal subjects, the signal information is only present in very-short and long period (control scales), as pathological group has different and heterogeneous patterns, with a global effect of reduced correlation in control scales.

Further Information
Year:

1999
Type of Publication:

(01)Article
Supervisor:



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% Autogenerated BibTeX entry
@InProceedings { Xxx:1999:IFA_894,
    author={M. Bellotti},
    title={{Methods for extracting self-similarity properties from
	  Heart Rate Variability signal in Normal and Heart Failure
	  Patients}},
    booktitle={Computers in Cardiology},
    pages={527--530},
    year={1999},
    address={Hannover, Germany},
    month=sep,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=894}
}
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