• DocumentCode
    2505772
  • Title

    The time-sequenced adaptive algorithm: application to morphological adaptation and arrhythmia onset detection

  • Author

    Finelli, C.J. ; Li, P.C. ; Jenkins, J.M. ; DiCarlo, L.A.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
  • fYear
    1991
  • fDate
    23-26 Sep 1991
  • Firstpage
    205
  • Lastpage
    208
  • Abstract
    An algorithm has been developed for morphologic adaptation and detection of arrhythmia onset. This is a computationally simple and patient-independent technique which adapts to subtle variations in electrogram morphology and promptly detects a change in morphology, as usually occurs at arrythmia onset. This technique also reduces the problem of costly detection time by quickly recognizing the onset of an arrhythmia within a few cardiac cycles. In a pilot study, the algorithm successfully adapted to electrogram morphology and identified the arrhythmia onset in a study of nine cases of onset of ventricular tachycardia during sinus rhythm
  • Keywords
    electrocardiography; waveform analysis; arrhythmia onset detection; cardiac cycles; morphological adaptation; patient-independent technique; sinus rhythm; time-sequenced adaptive algorithm; Adaptive algorithm; Adaptive filters; Algorithm design and analysis; Change detection algorithms; Face detection; Heart rate; Morphology; Rhythm; Robust stability; Strontium;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers in Cardiology 1991, Proceedings.
  • Conference_Location
    Venice
  • Print_ISBN
    0-8186-2485-X
  • Type

    conf

  • DOI
    10.1109/CIC.1991.169081
  • Filename
    169081