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Research Article | Open Access |

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
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 4, No. 2 · Published 2013 · Cited by 14

DOI: https://doi.org/10.14569/IJACSA.2013.040222

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

How to Cite this Article

Lee, D. H., Park, J. W., Choi, J., & Rabbi, A. (2013). Automatic Detection Of Electrocardiogram ST Segment: Application In Ischemic Disease Diagnosis. International Journal of Advanced Computer Science and Applications, 4(2). https://doi.org/10.14569/IJACSA.2013.040222

Lee, Duck Hee, et al.. "Automatic Detection Of Electrocardiogram ST Segment: Application In Ischemic Disease Diagnosis." International Journal of Advanced Computer Science and Applications, vol. 4, no. 2, 2013, https://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},
  volume    = {4},
  number    = {2},
  year      = {2013},
  publisher = {The Science and Information Organization},
  author    = {Duck Hee Lee and Jun Woo Park and Jeasoon Choi and Ahmed Rabbi},
  doi       = {10.14569/IJACSA.2013.040222},
  url       = {https://doi.org/10.14569/IJACSA.2013.040222}
}

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