• DocumentCode
    2370062
  • Title

    Optimizing ECG signal sampling frequency for T-wave alternans detection

  • Author

    Burattini, L. ; Zareba, W. ; Couderc, JP ; Konecki, JA ; Moss, Aj

  • Author_Institution
    Rochester Univ., NY, USA
  • fYear
    1998
  • fDate
    13-16 Sep 1998
  • Firstpage
    721
  • Lastpage
    724
  • Abstract
    Computer detection of microvolt T-wave alternans (TWA) is an non-invasive method to identify patients at high risk for ventricular arrhythmias. Since TWA is a transient phenomenon, there is the need for continuous long-term TWA analysis in Holter ECG recordings. TWA detection, usually detected in ECGs sampled at 1000 samples per second (sps), is computationally demanding. The authors determined the ability of their correlation method (CM) to identify TWA in ECGs sampled at lower frequencies. TWA was identified in 39 long QT syndrome patients, whose ECGs were originally acquired at 1000 sps, and then resampled at 100, 250, 500, and 750 sps. Results obtained at different sampling conditions were compared. The authors found that TWA can be effectively detected with the CM using sampling frequencies as low as 250 sps. Such sampling frequency seems to be optimal since it provides high accuracy of TWA measurements and substantial saving of computational time
  • Keywords
    electrocardiography; medical signal detection; signal sampling; ECG signal sampling frequency optimization; Holter ECG recordings; T-wave alternans detection; computational time saving; electrodiagnostics; high risk ventricular arrhythmia patients identification; sampling frequency; transient phenomenon; Correlation; Cutoff frequency; Electrocardiography; Heart rate; Low pass filters; Sampling methods; Signal analysis; Signal sampling; Testing; Transient analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers in Cardiology 1998
  • Conference_Location
    Cleveland, OH
  • ISSN
    0276-6547
  • Print_ISBN
    0-7803-5200-9
  • Type

    conf

  • DOI
    10.1109/CIC.1998.731975
  • Filename
    731975