• DocumentCode
    765849
  • Title

    A wavelet-based heart rate variability analysis for the study of nonsustained ventricular tachycardia

  • Author

    Szi-Wen Chen

  • Author_Institution
    Dept. of Electron. Eng., Chang Gung Univ., Kwei-Shan, Taiwan
  • Volume
    49
  • Issue
    7
  • fYear
    2002
  • fDate
    7/1/2002 12:00:00 AM
  • Firstpage
    736
  • Lastpage
    742
  • Abstract
    It has been reported that the sympathovagal balance (SB) can be quantified by heart rate (HR) via the low-frequency (LF) to high-frequency (HF) spectral power ratio LF/HF. In this paper, an investigation of the relationship between the autonomic nervous system (ANS) and nonsustained ventricular tachycardia (NSVT) is presented. A wavelet transform (WT)-based approach for short-time heart rate variability (HRV) assessments is proposed for this aspect of analysis. The study was conducted on an RR-interval database consisting of 87 NSVT, 61 ischemic and five normal episodes. First, instantaneous SB estimates were generated by the proposed method. Then, waveforms of the WT-based SB evolutions were quantitatively examined. Numerical results showed that while a majority of SB waveforms (about 71%) derived from the non-NSVT population (i.e., ischemic and normal) appeared to come near oscillating with certain fixed levels, approximate 75% of SB evolutions underwent significantly rapid increases prior to the onset of NSVT, suggesting that an abrupt sympathovagal imbalance might partly account for the occurrence of NSVT.
  • Keywords
    biocontrol; electrocardiography; feature extraction; medical signal processing; neurophysiology; wavelet transforms; RR-interval database; abrupt sympathovagal imbalance; autonomic nervous system; ischemic episodes; low-frequency to high-frequency spectral power ratio; nonsustained ventricular tachycardia; normal episodes; short-time heart rate variability; sympathovagal balance; wavelet-based heart rate variability analysis; Autonomic nervous system; Cardiac disease; Databases; Frequency; Hafnium; Heart rate; Heart rate variability; Signal resolution; Wavelet analysis; Wavelet transforms; Algorithms; Coronary Artery Disease; Heart Rate; Humans; Models, Cardiovascular; Myocardial Ischemia; ROC Curve; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Tachycardia, Ventricular;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2002.1010859
  • Filename
    1010859