• DocumentCode
    674498
  • Title

    The effect of automated preprocessing of RR interval tachogram on discrimination capability of Heart Rate Variability parameters

  • Author

    Marzbanrad, Faezeh ; Jelinek, Herbert ; Ng, Ethan ; Tamayo, Mikhail ; Hambly, Brett ; McLachlan, Craig ; Matthews, Slade ; Palaniswami, Marimuthu ; Khandoker, Ahsan

  • Author_Institution
    Univ. of Melbourne, Parkville, VIC, Australia
  • fYear
    2013
  • fDate
    22-25 Sept. 2013
  • Firstpage
    483
  • Lastpage
    486
  • Abstract
    Heart Rate Variability (HRV) has been extensively investigated for characterizing the autonomic nervous system (ANS) in controlling heart rate. Since ectopic beats, artefacts and noise of the ECG can affect the estimation of HRV features, pre-processing of the RR tachogram can improve the accuracy of HRV analysis and discriminatory power. This paper investigates the effect of different automated preprocessing methods on discriminatory capability of HRV analysis with an example of comparison between different groups of normal and type II diabetic patients with different Angiotensin-Converting Enzyme (ACE) gene polymorphism. Results show that smaller p-values and therefore higher discriminatory capability are found when preprocessing is used, while none of the features can show significant difference if they are estimated from the raw R-R sequence. Secondly, the preprocessing methods do not have the same effect for all HRV features.
  • Keywords
    biochemistry; bioelectric potentials; diseases; electrocardiography; enzymes; feature extraction; genetics; medical signal processing; molecular biophysics; statistical analysis; ACE gene polymorphism; ECG artefacts; ECG noise; HRV analysis; HRV feature estimation; R-R sequence estimation; RR interval tachogram; angiotensin-converting enzyme; automated preprocessing methods; autonomic nervous system characterization; ectopic beats; electrocardiography; heart rate variability parameters; type II diabetic patients; Abstracts; Heart rate variability; Myocardium; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing in Cardiology Conference (CinC), 2013
  • Conference_Location
    Zaragoza
  • ISSN
    2325-8861
  • Print_ISBN
    978-1-4799-0884-4
  • Type

    conf

  • Filename
    6713419