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Relative Amplitude based Features of characteristic ECG-Peaks for Identification of Coronary Artery Disease

  • Bakul Gohel
  • U. S. Tiwary
  • T. Lahiri

Abstract

Coronary artery disease or Myocardial Infarction is the leading cause of death and disability in the world. ECG is widely used as a cheap diagnostic tool for diagnosis of coronary artery disease but has low sensitivity with the present criteria based on ST-segment, T wave and Q wave changes. So to increase the sensitivity of the ECG we have introduced relative amplitude based new features of characteristic ‘R’ and ‘S’ ECG-peaks between two leads. Relative amplitude based features shows remarkable capability in discriminating Myocardial Infarction and Healthy pattern using backpropogation neural network classifier yield results with 81.82% sensitivity and 81.82% specificity. Also relative amplitude might be an efficient method in minimizing the effect of body composition on ECG amplitude based features without use of any information from other than ECG

Keywords

Body Composition Relative Amplitude Healthy Pattern Remarkable Capability Minimum Square Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Indian Institute of Information Technology, India 2009

Authors and Affiliations

  • Bakul Gohel
    • 1
  • U. S. Tiwary
    • 1
  • T. Lahiri
    • 1
  1. 1.Indian Institute of Information TechnologyAllahabad, UPIndia

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