• DocumentCode
    2673107
  • Title

    Comparison Between Neural-Network-Based Adaptive Filtering and Wavelet Transform for ECG Characteristic Points Detection

  • Author

    Ng, F. ; Mora, F. ; Wong, S. ; Passariello, G. ; Almeida, D.

  • Author_Institution
    Technical University of Budapest, Hungary
  • Volume
    1
  • fYear
    1997
  • fDate
    Oct. 30 1997-Nov. 2 1997
  • Firstpage
    272
  • Lastpage
    274
  • Abstract
    As a physiologic response during exercise, due to tachycardia effects and liberated catecholamines, reduction of left ventricle volume is produced. Based on the Brody effect, R wave amplitude lessening during the stress test is reflected in the electrocardiographic signal. In spite of the previous statements, many researches during the last decades have been unable to find any ability of this parameter to assess Coronary Artery Disease (CAD) patients. The proposed methodology considering trend series analysis allows one to approach several electrocardiographic parameters, hemodynamic responses and symptoms, allowing the correlation among them and to evaluate the behaviour of each parameter. In a sample of 17 CAD patients and 14 healthy subjects assessed by either clustering analysis or McNemar test has shown adequate ability in group discrimination
  • Keywords
    blood vessels; diseases; electrocardiography; medical signal processingcoronary artery disease; Brody effect; McNemar test; clustering analysis; electrocardiographic parameters; group discrimination; healthy subjects; hemodynamic responses; left ventricle volume reduction; stress test; symptoms; trend series analysis; Blood flow; Conductivity; Coronary arteriosclerosis; Heart rate; Hemodynamics; Hospitals; Ischemic pain; Myocardium; Stress; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE
  • Conference_Location
    Chicago, IL, USA
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-4262-3
  • Type

    conf

  • DOI
    10.1109/IEMBS.1997.754522
  • Filename
    754522