Volume 2, Issue 6, December 2017, Page: 127-140
Analysis on ECG Data Compression Using Wavelet Transform Technique
Hla Myo Tun, Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar
Win Khaing Moe, Department of Research and Innovation, Ministry of Education, Yangon, Myanmar
Zaw Min Naing, Department of Research and Innovation, Ministry of Education, Yangon, Myanmar
Received: Oct. 8, 2017;       Accepted: Oct. 18, 2017;       Published: Dec. 22, 2017
DOI: 10.11648/j.ijpbs.20170206.12      View  1567      Downloads  84
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.
Keywords
ECG, Compression Technique, Wavelet Transform Technique, Biomedical Engineering, Signal Processing, Biomedical Science
To cite this article
Hla Myo Tun, Win Khaing Moe, Zaw Min Naing, Analysis on ECG Data Compression Using Wavelet Transform Technique, International Journal of Psychological and Brain Sciences. Vol. 2, No. 6, 2017, pp. 127-140. doi: 10.11648/j.ijpbs.20170206.12
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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