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An Entropy-Based Method for Ischemia Diagnosis Using Ecg Signal in Wavelet Domain Publisher



Farahabadi E1 ; Farahabadi A1 ; Rabbani H1 ; Dehnavi AM1 ; Mahjoob MP2
Authors
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Authors Affiliations
  1. 1. Biomedical Engineering Department, Isfahan University of Medical Sciences, Isfahan, Iran
  2. 2. School of Medicine, Jahrom University of Medical Sciences (JUMS), Jahrom, Iran

Source: International Conference on Signal Processing Proceedings, ICSP Published:2010


Abstract

Ischemia means lack of oxygen due to insufficient blood circulation. Cardiac ischemia disease, which is one of the common fatal diseases in advanced countries, is a condition due to imbalance between supply and demand of oxygen. In this study the existence of ischemia is considered using entropy measure. Since signal perturbation in healthy people is less than signal perturbation in patients, generally it is observed that there is higher entropy in patients and lower entropy in healthy ones. In this base, 4 methods (in spatial and wavelet domains) are proposed for comparing entropy of processed electrocardiogram (ECG) signal of healthy and patient people. Our simulations on 20 recorded ECG signal from 10 healthy and 10 patient people show that proposed technique in wavelet domain results in highest discrepancy between healthy and patient subjects in comparison to other methods and specificity and sensitivity of this method are 88.8% and 90% respectively. © 2010 IEEE.
2. Ischemia Detection Via Dynamic Time Warping and Fuzzy Rules, Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012 (2012)
3. Detection of Qrs Complex in Electrocardiogram Signal Based on a Combination of Hilbert Transform, Wavelet Transform and Adaptive Thresholding, Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012 (2012)
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