• DocumentCode
    591300
  • Title

    Atrial electrical activity detection in the 12-lead ECG using synthetic atrial activity signals

  • Author

    Perlman, Or ; Katz, Al ; Weissman, Nir ; Zigel, Y.

  • Author_Institution
    Dept. of Biomed. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
  • fYear
    2012
  • fDate
    9-12 Sept. 2012
  • Firstpage
    665
  • Lastpage
    668
  • Abstract
    A significant key for the success of arrhythmia diagnosis using ECG is detecting the atrial electrical activity (AEA). Despite extensive research, there is a diagnostic problem in detecting AEA in some arrhythmias, especially when the AEA-wave is hidden in other waves. Our proposed method utilizes the well-known linear combiner usually used for noise reduction, and adapted it for AEA detection. The physician/user marks one prominent AEA segment. Then, a synthetic signal is created that contains an isoelectric line in addition to a Gaussian in the delineated segment. The 6 precordial leads, lead I, and lead II, serve as reference signals, so by finding the appropriate weight coefficients, their linear combination is forced to converge to a signal that is similar to the AEA signal. At the final stage, the resulting signal is band-pass filtered and the peaks higher than a certain threshold are determined to be AEA-waves. Sensitivity of 94.0% and precision of 90.2% were achieved in detecting AEA from the standard 12-lead ECG for various arrhythmia types.
  • Keywords
    Gaussian noise; band-pass filters; bioelectric potentials; electrocardiography; medical signal processing; patient diagnosis; sensitivity; signal denoising; 12-lead ECG; Gaussian delineated segment; arrhythmia diagnosis; atrial electrical activity detection; band-pass filter; electrocardiography; noise reduction; physician-user marks; sensitivity; synthetic atrial activity signals; Atrial fibrillation; Band pass filters; Electrocardiography; Noise; Sensitivity; Standards; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing in Cardiology (CinC), 2012
  • Conference_Location
    Krakow
  • ISSN
    2325-8861
  • Print_ISBN
    978-1-4673-2076-4
  • Type

    conf

  • Filename
    6420481