• Title of article

    Ventricular activity cancellation in electrograms during atrial fibrillation with constraints on residuals’ power

  • Author/Authors

    Corino، نويسنده , , Valentina D.A. and Rivolta، نويسنده , , Massimo W. and Sassi، نويسنده , , Roberto and Lombardi، نويسنده , , Federico and Mainardi، نويسنده , , Luca T.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    8
  • From page
    1770
  • To page
    1777
  • Abstract
    During atrial fibrillation (AF), cancellation of ventricular activity from atrial electrograms (AEG) is commonly performed by template matching and subtraction (TMS): a running template, built in correspondence of QRSs, is subtracted from the AEG to uncover atrial activity (AA). However, TMS can produce poor cancellation, leaving high-power residues. In this study, we propose to modulate the templates before subtraction, in order to make the residuals as similar as possible to the nearby atrial activity, avoiding high-power ones. The coefficients used to modulate the template are estimated by maximizing, via Multi-swarm Particle Swarm Optimization, a fitness function. The modulated TMS method (mTMS) was tested on synthetic and real AEGs. Cancellation performances were assessed using: normalized mean squared error (NMSE, computed on simulated data only), reduction of ventricular activity (VDR), and percentage of segments (PP) whose power was outside the standard range of the atrial power. All testings suggested that mTMS is an improvement over TMS alone, being, on simulated data, NMSE and PP significantly decreased while VDR significantly increased. Similar results were obtained on real electrograms (median values of CS1 recordings PP: 2.44 vs. 0.38 p < 0.001; VDR: 6.71 vs. 8.15 p < 0.001).
  • Keywords
    Atrial electrograms , Ventricular interference , atrial fibrillation , Multi-swarm Particle Swarm Optimization
  • Journal title
    Medical Engineering and Physics
  • Serial Year
    2013
  • Journal title
    Medical Engineering and Physics
  • Record number

    1732384