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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Automatic Detection Of Electrocardiogram ST Segment: Application In Ischemic Disease Diagnosis

Author 1: Duck Hee Lee
Author 2: Jun Woo Park
Author 3: Jeasoon Choi
Author 4: Ahmed Rabbi

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2013.040222

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 2, 2013.

  • Abstract and Keywords
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Abstract: The analysis of electrocardiograph (ECG) signal provides important clinical information for heart disease diagnosis. The ECG signal consists of the P, QRS complex, and T-wave. These waves correspond to the fields induced by specific electric phenomenon on the cardiac surface. Among them, the detection of ischemia can be achieved by analysis the ST segment. Ischemia is one of the most serious and prevalent heart diseases. In this paper, the European database was used for evaluation of automatic detection of the ST segment. The method comprises several steps; ECG signal loading from database, signal preprocessing, detection of QRS complex and R-peak, ST segment, and other relation parameter measurement. The developed application displays the results of the analysis.

Keywords: Electrocardiogram (ECG); Ischemia; European ST-T database; QRS complex ; ST segment.

Duck Hee Lee, Jun Woo Park, Jeasoon Choi and Ahmed Rabbi, “Automatic Detection Of Electrocardiogram ST Segment: Application In Ischemic Disease Diagnosis” International Journal of Advanced Computer Science and Applications(IJACSA), 4(2), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040222

@article{Lee2013,
title = {Automatic Detection Of Electrocardiogram ST Segment: Application In Ischemic Disease Diagnosis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.040222},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040222},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {2},
author = {Duck Hee Lee and Jun Woo Park and Jeasoon Choi and Ahmed Rabbi}
}


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