• DocumentCode
    541614
  • Title

    A new and fast index for the quantification of short range self-similarity in RR time series

  • Author

    García-González, M.A. ; Fernández-Chimeno, M. ; Ramos-Castro, J.

  • Author_Institution
    Dept. of Electron. Eng., Tech. Univ. of Catalonia (UPC), Barcelona, Spain
  • fYear
    2010
  • fDate
    26-29 Sept. 2010
  • Firstpage
    581
  • Lastpage
    584
  • Abstract
    We propose a new and very fast index (the frequency of sign changes of the mirrored differences or fscmd) with good correlation with the short range scaling exponent (αl) estimated among scales 4 to 16 of the DFA. fscmd computes the relative number of sign changes of the difference of the RR time series minus their corresponding reversed RR time series after a moving average detrending procedure is applied using a window of 30 samples. Linear regression results with simulated time series with Fractional Brownian Noise and with actual time series using the Fantasia (FT), Normal Sinus Rhythm RR time series (NSR) and Congestive Heart Failure RR interval (CHF) databases after artifact correction show good agreement between fscmd and αl. Finally, Mann-Whitney Rank Sum tests applied to αl and fscmd when comparing NSR and CHF databases show very significant differences (p<;0.001) between groups for both indices.
  • Keywords
    cardiology; fractals; medical signal processing; moving average processes; noise; regression analysis; time series; CHF; Mann-Whitney Rank Sum test; NSR; congestive heart failure RR interval databases; detrended fluctuation analysis; fantasia database; fractional Brownian noise; frequency of sign changes of the mirrored differences; fscmd; linear regression; normal sinus rhythm RR time series; short range self-similarity; Computational modeling; Doped fiber amplifiers; Indexes; Linear regression; Power capacitors; Time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing in Cardiology, 2010
  • Conference_Location
    Belfast
  • ISSN
    0276-6547
  • Print_ISBN
    978-1-4244-7318-2
  • Type

    conf

  • Filename
    5738039