CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

ECG Compression using the Three-Level Quantization and Wavelet Transform

by Milad Azarbad, Ataollah Ebrahimzadeh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 59 - Number 1
Year of Publication: 2012
Authors: Milad Azarbad, Ataollah Ebrahimzadeh
10.5120/9515-3916

Milad Azarbad, Ataollah Ebrahimzadeh . ECG Compression using the Three-Level Quantization and Wavelet Transform. International Journal of Computer Applications. 59, 1 ( December 2012), 28-38. DOI=10.5120/9515-3916

@article{ 10.5120/9515-3916,
author = { Milad Azarbad, Ataollah Ebrahimzadeh },
title = { ECG Compression using the Three-Level Quantization and Wavelet Transform },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 59 },
number = { 1 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 28-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume59/number1/9515-3916/ },
doi = { 10.5120/9515-3916 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:04:50.445539+05:30
%A Milad Azarbad
%A Ataollah Ebrahimzadeh
%T ECG Compression using the Three-Level Quantization and Wavelet Transform
%J International Journal of Computer Applications
%@ 0975-8887
%V 59
%N 1
%P 28-38
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Electrocardiogram signals are a very valuable source of data for physicians in diagnosing heart abnormalities. In this paper, we present an efficient technique for compression of electrocardiogram (ECG) signals. A new thresholding method based on the three level of quantization is proposed for encoding samples using an Embedded Zero-tree Wavelet (EZW) and Huffman algorithms. The modified encoding algorithm allows an optimal data compression for a target bit rate and appeared superior to other wavelet-based ECG coders. Also, to improve the efficiency of the proposed method we propose to use different types of wavelet and compare their performances for compression of the ECG signals. Experimental results show that the proposed method has a good performance and less complexity for compression of ECG database from MIT-BIH database different types of wavelet transform.

References
  1. J. R. Cox, F. M. Nolle, H. A. Fozzard, and G. C. Oliver. ''AZTEC, a preprocessing program for real time ECG rhythm analysis '' IEEE Trans. Biomed. Eng. Vol, BME-15, pp. 128-129, 1968.
  2. J. P. Aberstein and W. J. Tompkins,"A new data reduction algorithm for real time ECG analysis" IEEE Trans. Biomed. Eng. Vol. BME-29, pp. 43-48, 1982.
  3. Z. Lu, D. Y. Kim, and W. A. Pearlman, "Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm," IEEE Trans. Biomed. Eng. , vol. 47, pp. 849-856, July 2000.
  4. S. G. Miaou, H. L. Yen and C. L. Lin, "Wavelet-based ECG compression using dynamic vector quantization with tree codevectors in single codebook," IEEE Trans. Biomed. Eng. , vol. 49, pp. 671-680, July 2002.
  5. S. G. Miaou and S. N. Chao, "Wavelet-based lossy-to-lossless ECG compression in a unified vector quantization framework," IEEE Trans. Biomed. Eng. , vol. 52, pp. 539-543, March 2005.
  6. A. Al-Shroufa, M. Abo-Zahhad and Sabah M. Ahmedc, "A novel compression algorithm for electrocardiogram signals based on the linear prediction of the wavelet coefficients," Digital Signal Processing, Elsevier, vol. 13, pp. 604-622, October 2003.
  7. A. Alshamali and A. S. Al-Fahoum, "Comments on "An efficient coding algorithm for the compression of ECG signals using the wavelet transform," IEEE Trans. Biomed. Eng. , vol. 50, pp. 1034-1037, August 2003.
  8. J. Chen, J. Ma, Y. Zhang and X. Shi, "ECG compression based on wavelet transform and Golomb coding," Electron. Lett. , vol. 42, no. 6, pp. 322-324, March 2006
  9. R. Benzid, F. Marir and N. E. Bouguechal, "Electrocardiogram Compression Method Based on the Adaptive Wavelet Coefficients Quantization Combined to a Modified Two-Role Encoder," IEEE Signal Pro, Lett, vol. 14, pp. 373-376, June 2007.
  10. P. S. Hamilton, "Adaptive compression of the ambulatory electrocardiogram," Biomed. Inst. Technol. , vol. 27, no. 1, pp. 56-63, Jan. 1993.
  11. A. Al-shrouf, M. Abo-Zahhad, S. M. Ahmed. '' A novel compression algorithm for electrocardiogram signal based on the linear prediction of the wavelet coefficients '' Digital Signal Processing, Vol. 13, 2003, pp. 604-622.
  12. M. Blanco-Velasco, F. Cruz-Roldan, J. I. Godino-Llorente and K. E. Barner, "Wavelet Packets Feasibility Study for the Design of an ECG Compressor," IEEE Trans. Biomed. Eng. , vol. 54, pp. 766-769, April 2007.
  13. J. M. Shapiro,"Embedded Image Coding Using Zero-Trees of wavelet Coefficients", IEEE Trans. On Signal Processing, vol. 41. NO. 12. pp. 3445-3462, 1993.
  14. Said A, Pearlman WA. A new, fast, and efficient image codec based on set partitioning in hierarchical tree. IEEE Trans. CSVT 1996;6(3):243-50.
  15. Gersho A, Gray RM. Vector Quantization and Signal Compression. New York: Kluwer Academic Press, 1992.
  16. Sang Joon Lee and Myoung ho Lee 30th Annual International IEEE Conference Vancouver, British Columbia, Canada , August 20-24, 2008
  17. H. L. Chan, Y. C. Siao, S. W. Chen and S. F. Yu, "Wavelet-based ECG compression by bit-field preserving and running length encoding", Computer Methods and Prog. in Biomedicine, vol. 90, pp. 1-8, 2008.
  18. C. M. Fira and L. Goras, "An ECG signals Compression Method and its Validation using NNs", IEEE Trans Biomed. Eng, vol. 55, No. 4, pp. 1319-1326, 2008.
  19. H. Kim, R. F. Yazicioglu, P. Mercen, C. V. Hoog and H. J. Yoo, "ECG signal compression and classification with Quad Level Vector for ECG Holter system", IEEE Trans. Inf. Tech. in Biomed, vol. 14, No. 1, pp. 93100, 2010.
  20. C. S. Burrus. R. A. Gopinath. H. Guo, introduction to Wavelets and Wavelet Transforms, Prentice-Hall, 1997.
  21. S. G. Mallat,"A Theory of Multiresolution signal decompression; The Wavelet Representation", IEEE Trans. Image Processing, vol. 1, no. 2, pp. 205-220, April 1992.
  22. J. M. Shapiro,"Embedded Image Coding Using Zero-Trees of wavelet Coefficients", IEEE Trans. On Signal Processing, Vol. 41. NO. 12. pp. 3445-3462, 1993.
  23. P. Wellig, Z. Cheng, M. Semling, and G. S. Moschytz, " Electromyogram Data Compression Using Signal-Tree and Modified Zero-Tree Wavelet Encoding ", Proceeding of the 20th Annual International Conference of the IEEE Engineering in medicine and biology society, Vol. 20, No. 3, pp. 1303-1306, 1998.
  24. L. M. Ang, H. N. Cheung, and K. Eshraghian, "EZW Algorithm Using Depth-First Representation of the Wavelet Zero-Tree" , 5th International Symposium on Signal Processing and its Applications, pp. 75-78, 1999.
  25. Ali Bilgin, Michael W. Marcellin, Maria I. Altbach," Compression of Electrocardiogram Signals Using JPEG2000 " , IEEE Transactions on Consumer Electronics, Vol. 49, No. 4, November, 2003, pp. 833-840.
  26. I. M. Rezazadeh. M. H. Moradi, A. M. Nasrabadi, "Implementing of SPIHT and subband Energy Compression (SEC) Method on Two-Dimensional ECG Compression: A Novel Approach". Engineering in medicine and biology, 27th annual conference, IEEE, China, 2005.
  27. S. M. E Sahraeian and E. Fatemizadeh. "Wavelet-Based 2-D ECG Data Compression Method Using SPIHT and VQ Coding ". IEEE Int. Conf on " Computer as a tool" . EUOROCON 2007.
  28. Z. Lu, D. Y. Kim, and W. A. Pearlman, "Wavelet Compression of ECG signal by the Set Partitioning in Hierarchical Trees (SPIHT) algorithm" IEEE Transactions on Biomedical Engineering, Vol. 47, July 2000 , pp. 849-856.
  29. Ranjeet Kumar, A. Kumar, Rajesh K. Pandey "Beta wavelet based ECG signal compression using lossless encoding with modi?ed thresholding" Computers and Electrical Engineering (Elsevier 2012)
  30. S. K. Mukhopadhyay, S. Mitra, , M. Mitra "An ECG signal compression technique using ASCII character encoding" Measurement (Elsevier) 45, 2012, pp. 1651–1660
  31. Eddie B . L . Filho, Nuno M. M. Rodrigues , Eduardo A. B . da Silva, S ´ ergio M . M . d e Faria , Vitor M . M . da S ilva, and M urilo B. de Carvalh," ECG Signal Compression Based on Dc Equalization and Complexity Sorting" IEEE TRANSAC TIONS ON BIOMEDICAL ENGINEERING, VOL. 55, NO. 7, JULY 2008
  32. Jianhua Chen, Fuyan Wang, Yufeng Zhang, Xinling Shi "ECG compression using uniform scalar dead-zone quantization and conditional entropy coding" Medical Engineering & Physics (Elsevier), 30-2008, pp. 523–530
  33. R. Benzid, A. Messaoudi, A. Boussaad "Constrained ECG compression algorithm using the block-based discrete cosine transform" Digital Signal Processing 18 (2008) 56–64
  34. Jin Wang, Xiaomei Lin and Kebing Wu "ECG Data Compression Research Based on Wavelet Neural Network" 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering (CMCE)
  35. Hilton ML. Wavelet and Wavelet Packet compression of electrocardiograms. IEEE Transactions on Biomedical Engineering 1997;44(5):394-402.
  36. Djohan, A. , Nguyen, T. Q. , Tompkins, w. J. , ECG compression using discrete symmetric wavelet transform, IEEE 17th annual Conference, Engineering in Medicine and Biology Society, vol. 1, pp. 167-168, 1997.
Index Terms

Computer Science
Information Sciences

Keywords

Discrete Wavelet Transform (DWT) EZW Huffman Coding Three-Level Quantization

Powered by PhDFocusTM