• DocumentCode
    2882818
  • Title

    R-wave detection using continuous wavelet modulus maxima

  • Author

    Legarreta, I. Romero ; Addison, Ps ; Grubb, N. ; Clegg, Gr ; Robertson, Ce ; Fox, Kaa ; Watson, Jn

  • Author_Institution
    Fac. of Eng. & Comput., Napier Univ., Edinburgh, UK
  • fYear
    2003
  • fDate
    21-24 Sept. 2003
  • Firstpage
    565
  • Lastpage
    568
  • Abstract
    Modulus maxima derived from the continuous wavelet transform offers an enhanced time-frequency analysis technique for ECG signal analysis. Features within the ECG can be shown to correspond to various morphologies in the continuous modulus maxima domain. This domain has an easy interpretation and offers a good tool for the automatic characterization of the different components observed in the ECG in health and disease. As an application of these properties we have developed an R-wave detector and tested it using patient signals recorded in the Coronary Care Unit of the Royal Infirmary of Edinburgh (attaining a sensitivity of 99.53% and a positive predictive value of 99.73%) and with the MIT/BIH database (attaining a sensitivity of 99.7% and a positive predictive value of 99.68%).
  • Keywords
    electrocardiography; medical signal detection; medical signal processing; time-frequency analysis; wavelet transforms; Coronary Care Unit; ECG signal analysis; MIT/BIH database; R-wave detection; Royal Infirmary of Edinburgh; continuous wavelet transform; disease; enhanced time-frequency analysis; health; modulus maxima; Continuous wavelet transforms; Detectors; Diseases; Electrocardiography; Morphology; Signal analysis; Testing; Time frequency analysis; Wavelet analysis; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers in Cardiology, 2003
  • ISSN
    0276-6547
  • Print_ISBN
    0-7803-8170-X
  • Type

    conf

  • DOI
    10.1109/CIC.2003.1291218
  • Filename
    1291218