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DOI: 10.14569/IJACSA.2016.070325
PDF

The ECG Signal Compression Using an Efficient Algorithm Based on the DWT

Author 1: Oussama El B’charri
Author 2: Rachid Latif
Author 3: Wissam Jenkal
Author 4: Abdenbi Abenaou

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 3, 2016.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: The storage capacity of the ECG records presents an important issue in the medical practices. These data could contain hours of recording, which needs a large space for storage to save these records. The compression of the ECG signal is widely used to deal with this issue. The problem with this process is the possibility of losing some important features of the ECG signal. This loss could influence negatively the analyzing of the heart condition. In this paper, we shall propose an efficient method of the ECG signal compression using the discrete wavelet transform and the run length encoding. This method is based on the decomposition of the ECG signal, the thresholding stage and the encoding of the final data. This method is tested on some of the MIT-BIH arrhythmia signals from the international database Physionet. This method shows high performances comparing to other methods recently published.

Keywords: ECG compression; wavelet transform; lossy compression; hard thresholding

Oussama El B’charri, Rachid Latif, Wissam Jenkal and Abdenbi Abenaou, “The ECG Signal Compression Using an Efficient Algorithm Based on the DWT” International Journal of Advanced Computer Science and Applications(IJACSA), 7(3), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070325

@article{B’charri2016,
title = {The ECG Signal Compression Using an Efficient Algorithm Based on the DWT},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070325},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070325},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {3},
author = {Oussama El B’charri and Rachid Latif and Wissam Jenkal and Abdenbi Abenaou}
}



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.

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