Although digital storage media is not expensive and computational power has exponentially increased in past few years, the possibility of electrocardiogram (ECG) compression still attracts the attention, due to the huge amount of data that has to be stored and transmitted. ECG compression methods can be classified into two categories; direct method and transform method. A wide range of compression techniques were based on different transformation techniques. In this work, transform based signal compression is proposed. This method is used to exploit the redundancy in the signal. Wavelet based compression is evaluated to find an optimal compression strategy for ECG data compression. The algorithm for the one-dimensional case is modified and it is applied to compress ECG data. A wavelet ECG data code based on Run-length encoding compression algorithm is proposed in this research. Wavelet based compression algorithms for one-dimensional signals are presented along with the results of compression ECG data. Firstly, ECG signals are decomposed by discrete wavelet transform (DWT). The decomposed signals are compressed using thresholding and run-length encoding. Global and local thresholding are employed in the research. Different types of wavelets such as daubechies, haar, coiflets and symlets are applied for decomposition. Finally the compressed signal is reconstructed. Different types of wavelets are applied and their performances are evaluated in terms of compression ratio (CR), percent root mean square difference (PRD). Compression using HAAR wavelet and local thresholding are found to be optimal in terms of compression ratio.
| Published in | International Journal of Psychological and Brain Sciences (Volume 2, Issue 6) |
| DOI | 10.11648/j.ijpbs.20170206.12 |
| Page(s) | 127-140 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2017. Published by Science Publishing Group |
ECG, Compression Technique, Wavelet Transform Technique, Biomedical Engineering, Signal Processing, Biomedical Science
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APA Style
Hla Myo Tun, Win Khaing Moe, Zaw Min Naing. (2017). Analysis on ECG Data Compression Using Wavelet Transform Technique. International Journal of Psychological and Brain Sciences, 2(6), 127-140. https://doi.org/10.11648/j.ijpbs.20170206.12
ACS Style
Hla Myo Tun; Win Khaing Moe; Zaw Min Naing. Analysis on ECG Data Compression Using Wavelet Transform Technique. Int. J. Psychol. Brain Sci. 2017, 2(6), 127-140. doi: 10.11648/j.ijpbs.20170206.12
AMA Style
Hla Myo Tun, Win Khaing Moe, Zaw Min Naing. Analysis on ECG Data Compression Using Wavelet Transform Technique. Int J Psychol Brain Sci. 2017;2(6):127-140. doi: 10.11648/j.ijpbs.20170206.12
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Download@article{10.11648/j.ijpbs.20170206.12,
author = {Hla Myo Tun and Win Khaing Moe and Zaw Min Naing},
title = {Analysis on ECG Data Compression Using Wavelet Transform Technique},
journal = {International Journal of Psychological and Brain Sciences},
volume = {2},
number = {6},
pages = {127-140},
doi = {10.11648/j.ijpbs.20170206.12},
url = {https://doi.org/10.11648/j.ijpbs.20170206.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijpbs.20170206.12},
abstract = {Although digital storage media is not expensive and computational power has exponentially increased in past few years, the possibility of electrocardiogram (ECG) compression still attracts the attention, due to the huge amount of data that has to be stored and transmitted. ECG compression methods can be classified into two categories; direct method and transform method. A wide range of compression techniques were based on different transformation techniques. In this work, transform based signal compression is proposed. This method is used to exploit the redundancy in the signal. Wavelet based compression is evaluated to find an optimal compression strategy for ECG data compression. The algorithm for the one-dimensional case is modified and it is applied to compress ECG data. A wavelet ECG data code based on Run-length encoding compression algorithm is proposed in this research. Wavelet based compression algorithms for one-dimensional signals are presented along with the results of compression ECG data. Firstly, ECG signals are decomposed by discrete wavelet transform (DWT). The decomposed signals are compressed using thresholding and run-length encoding. Global and local thresholding are employed in the research. Different types of wavelets such as daubechies, haar, coiflets and symlets are applied for decomposition. Finally the compressed signal is reconstructed. Different types of wavelets are applied and their performances are evaluated in terms of compression ratio (CR), percent root mean square difference (PRD). Compression using HAAR wavelet and local thresholding are found to be optimal in terms of compression ratio.},
year = {2017}
}
TY - JOUR T1 - Analysis on ECG Data Compression Using Wavelet Transform Technique AU - Hla Myo Tun AU - Win Khaing Moe AU - Zaw Min Naing Y1 - 2017/12/22 PY - 2017 N1 - https://doi.org/10.11648/j.ijpbs.20170206.12 DO - 10.11648/j.ijpbs.20170206.12 T2 - International Journal of Psychological and Brain Sciences JF - International Journal of Psychological and Brain Sciences JO - International Journal of Psychological and Brain Sciences SP - 127 EP - 140 PB - Science Publishing Group SN - 2575-1573 UR - https://doi.org/10.11648/j.ijpbs.20170206.12 AB - Although digital storage media is not expensive and computational power has exponentially increased in past few years, the possibility of electrocardiogram (ECG) compression still attracts the attention, due to the huge amount of data that has to be stored and transmitted. ECG compression methods can be classified into two categories; direct method and transform method. A wide range of compression techniques were based on different transformation techniques. In this work, transform based signal compression is proposed. This method is used to exploit the redundancy in the signal. Wavelet based compression is evaluated to find an optimal compression strategy for ECG data compression. The algorithm for the one-dimensional case is modified and it is applied to compress ECG data. A wavelet ECG data code based on Run-length encoding compression algorithm is proposed in this research. Wavelet based compression algorithms for one-dimensional signals are presented along with the results of compression ECG data. Firstly, ECG signals are decomposed by discrete wavelet transform (DWT). The decomposed signals are compressed using thresholding and run-length encoding. Global and local thresholding are employed in the research. Different types of wavelets such as daubechies, haar, coiflets and symlets are applied for decomposition. Finally the compressed signal is reconstructed. Different types of wavelets are applied and their performances are evaluated in terms of compression ratio (CR), percent root mean square difference (PRD). Compression using HAAR wavelet and local thresholding are found to be optimal in terms of compression ratio. VL - 2 IS - 6 ER -
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