• DocumentCode
    471793
  • Title

    Noise Sensitivity of a Principal Component Regression Based RT Interval Variability Estimation Method

  • Author

    Tarvainen, Mika P. ; Niskanen, Juha-Pekka ; Karjalainen, Pasi A. ; Laitinen, Tomi ; Lyyra-Laitinen, Tiina

  • Author_Institution
    Dept. of Phys., Kuopio Univ.
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    3098
  • Lastpage
    3101
  • Abstract
    Ventricular repolarization duration (VRD) is controlled by neural regulatory system same way as heart rate and, thus, also VRD varies in time. Traditionally, VRD variability is assessed by determining the time differences between successive R and T-waves, i.e. RT intervals. We have recently proposed a method based on principal component regression (PCR) for quantifying RT variability. The main benefit of the method is that it does not necessitate T-wave detection. In this paper, the noise sensitivity of the PCR based method is evaluated by examining the effect of simulated Gaussian noise on the spectral characteristics of the estimated RT variability series
  • Keywords
    Gaussian noise; cardiovascular system; electrocardiography; principal component analysis; regression analysis; RT interval variability estimation method; heart rate; neural regulatory system; noise sensitivity; principal component regression; simulated Gaussian noise; spectral characteristics; ventricular repolarization duration variability; Cities and towns; Control systems; Electrocardiography; Gaussian noise; Heart rate; Heart rate interval; Noise level; Noise measurement; Physics; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.260020
  • Filename
    4462452