• DocumentCode
    510149
  • Title

    An Extra-Systole Arrhythmia Lowers the Scaling Exponent: DFA as a Beneficial Biomedical Tool

  • Author

    Yazawa, Toru ; Katsuyama, Tomoo

  • Author_Institution
    Dept. of Biol. Sci., Tokyo Metropolitan Univ., Hachioji, Japan
  • Volume
    1
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    601
  • Lastpage
    605
  • Abstract
    We made our own DFA (detrended fluctuation analysis) program. We applied it for checking characteristics for the heartbeat of various individuals. Healthy subjects showed a normal scaling exponent, which is near 1.0 (ranging 0.9 to 1.19 in our own temporary guideline). This is in agreement with the original report by Peng et al. long time ago. In the present study, we investigated the person who has an extra-systole heartbeat, which is so called as PVCs (premature ventricular contractions), and revealed that their arrhythmic heartbeat exhibited a low scaling exponent (around 0.7). Alternans, which is the heart beating in period-2 rhythms, exhibited a much low scaling exponent (around 0.6). We may conclude that if it would be possible to make a device that equips a DFA program, it might be useful to check the heart condition, and contribute not only in nonlinear physics but also in biomedical fields; especially as a device for health check, which is applicable for people who are spending an ordinary life, before they get seriously heart sick.
  • Keywords
    medical signal processing; patient diagnosis; time series; arrhythmic heartbeat; biomedical tool; detrended fluctuation analysis; extra-systole arrhythmia; premature ventricular contractions; scaling exponent; Artificial intelligence; Computational intelligence; Doped fiber amplifiers; DFA; extras systole; heartbeat; scaling exponent; time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.19
  • Filename
    5376320