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
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© 2009 Indian Institute of Information Technology, India
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Gohel, B., Tiwary, U.S., Lahiri, T. (2009). Relative Amplitude based Features of characteristic ECG-Peaks for Identification of Coronary Artery Disease. In: Tiwary, U.S., Siddiqui, T.J., Radhakrishna, M., Tiwari, M.D. (eds) Proceedings of the First International Conference on Intelligent Human Computer Interaction. Springer, New Delhi. https://doi.org/10.1007/978-81-8489-203-1_12
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DOI: https://doi.org/10.1007/978-81-8489-203-1_12
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-8489-404-2
Online ISBN: 978-81-8489-203-1
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