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Ischemia Detection Via Dynamic Time Warping and Fuzzy Rules Publisher



Farahabadi A1 ; Farahabadi E1 ; Rabbani H2 ; Mahjoub MP3 ; Dehnavi AM1
Authors
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Authors Affiliations
  1. 1. Biomedical Engineering Dept., School of Medicine, Isfahan Univ. of Medical Sciences, Isfahan, Iran
  2. 2. Biomedical Engineering Dept., Medical Image and Signal Processing Research Center, Isfahan Univ. of Medical Sciences, Isfahan, Iran
  3. 3. School of Medicine, Shahid Beheshti Univ. of Medical Sciences, Tehran, Iran

Source: Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012 Published:2012


Abstract

Cardiac ischemia is one of the major causes of mortalities in the world. This disease includes a wide range of temporarily disorders such as insufficient blood circulation to myocardium, which leads to myocardial infarction, and consequently, sudden death. Recording electrocardiogram (ECG) signal has an important role in diagnosis of cardiac disease due to its advantages such as easy recording and suitable cost. Generally using techniques based on extraction of ST segments from ECG signal have been always of interest for ischemia detection. In this study, dynamic time warping (DTW) method is employed as a full-automatic tool in diagnosis of ischemic areas. Then, a fuzzy classifier is applied on the extracted features from the ST segment in order to separate the healthy and ischemic cases. The simulation results show an accuracy of 93% in the output of proposed ischemia detection algorithm. © 2012 IEEE.
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