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Multichannel Data Compression using Wavelet Subbands Arranging Technique

by Ershad Sharifahmadian, Yoonsuk Choi, Shahram Latifi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 4
Year of Publication: 2014
Authors: Ershad Sharifahmadian, Yoonsuk Choi, Shahram Latifi
10.5120/15869-4814

Ershad Sharifahmadian, Yoonsuk Choi, Shahram Latifi . Multichannel Data Compression using Wavelet Subbands Arranging Technique. International Journal of Computer Applications. 91, 4 ( April 2014), 17-22. DOI=10.5120/15869-4814

@article{ 10.5120/15869-4814,
author = { Ershad Sharifahmadian, Yoonsuk Choi, Shahram Latifi },
title = { Multichannel Data Compression using Wavelet Subbands Arranging Technique },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 4 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number4/15869-4814/ },
doi = { 10.5120/15869-4814 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:11:53.360870+05:30
%A Ershad Sharifahmadian
%A Yoonsuk Choi
%A Shahram Latifi
%T Multichannel Data Compression using Wavelet Subbands Arranging Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 4
%P 17-22
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To reduce the amount of data and preserve necessary signal quality for multichannel data transmission in many applications such as meteorology, or telemedicine, a new technique called WSAT is presented. The proposed technique is designed to deal with the large amount of multichannel data for transmission, and real-time analysis. The proposed approach has exact control on the bit rate in order to achieve the required quality. For different applications, the proposed method is tested. For telemedicine, the method is employed on selected records from the MIT-BIH arrhythmia database. For meteorology, climate data from Nevada climate change database is utilized. From the obtained results, it is concluded that the proposed technique is an appropriate approach to simultaneously compress multichannel data with significant low compressed data rate at low error. As an example, APRD values for multichannel ECG compression is mostly less than 5% which is recommended by the American Heart Association for routine visual readings of compressed and reconstructed ECG signals.

References
  1. Thakor N. V. "Ambulatory arrhythmia monitoring: From holter monitors to automatic implantable defibrillators," IEEE Transaction on Biomedical Engineering, vol. 31, 1984, pp. 770-778.
  2. Chan H. L. , Siao Y. C. , et al. "Wavelet-based ECG compression by bit-field preserving and running length encoding," Computer Methods and Programs in Biomedicine, Elsevier, vol. 90, 2008, pp. 1-8.
  3. Zigel Y. , Cohen A. , and Katz A. "ECG signal compression using analysis by synthesis coding," IEEE Transaction on Biomedical Engineering, vol. 47, Oct. 2000, pp. 1308-1315.
  4. Miaou S. G. , and Chao S. N. , "Wavelet-based lossy to lossless ECG compression in a unified vector quantization framework," IEEE Trans. Biomed. Eng. , vol. 52, Mar. 2005, pp. 539-543.
  5. Hilton M. L. , "Wavelet and wavelet packet compression of electrocardiograms," IEEE Trans. Biomed. Eng, vol. 44, May 1997, pp. 394-402.
  6. Lu Z. , Kim D. Y. , et al. , "Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm," IEEE Trans. Biomed. Eng, vol. 47, July 2000, pp. 849-856.
  7. Thakor N. V. , Webster J. G. , and Tompkins W. J. , "Estimation of QRS complex power spectra for design of a QRS filter," IEEE Trans. Biomed. Eng. , vol. 31, Nov. 1984, pp. 702-706.
  8. Cohen A. , Daubechies I. , and Feauveau J. C. , "Biorthogonal bases of compactly supported wavelets," Communications on Pure and Applied Mathematics, vol. 45, 1992, pp. 485-560.
  9. Sharifahmadian E. , "Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm," 28th IEEE EMBS Annual International Conference, New York City, USA, Sept. 2006, pp. 5238–5243.
  10. Mallat S. G. , "A theory for multiresolution signal decomposition: The wavelet representation," IEEE Transaction on Pattern analysis and machine intelligence, vol. 11, July 1989, pp. 674-693.
  11. Nave G. , and Cohen A. , "ECG compression using long-term prediction", IEEE Trans. Biomed. Eng. , vol. 40, Sept. 1993, pp. 877-885.
  12. Miaou S. G. , and Yen H. L. , "Quality driven gold washing adaptive vector quantization and its application to ECG data compression", IEEE Trans. Biomed. Eng. , vol. 47, Feb. 2000, pp. 209-218.
  13. Jalaleddine S. M. S. , Hutchens C. , et al. , "ECG data compression techniques-A unified approach," IEEE Trans. Biomed. Eng, vol. BME-37, Apr. 1990, pp. 329-343.
  14. Bailey J. J. , Berson A. S. , et al. "Recommendations for standardization and specifications in automated electrocardiography-Bandwidth and digital signal processing," Circulation, vol. 81, Feb. 1990, pp. 730-739.
  15. http://www. physionet. org/physiobank/database/mitdb/
  16. Mammen C. P. , and Ramamurthi B. , "Vector quantization for compression of multichannel ECG," IEEE Trans. Biomed. Eng. , vol. 37, Sept. 1990, pp. 821-825.
  17. Cetin A. E. , Koymen H. , and Aydin M. C. , "Multichannel ECG data compression by multirate signal processing and transform domain coding techniques," IEEE Trans. Biomed. Eng. , vol. 40, May 1993, pp. 495-499.
  18. Cohen A. , and Zigel Y. , "Compression of multichannel ECG through multichannel long-term prediction," IEEE Eng. Med. Biol. Mag. , vol. 16, no. 4, May 1998, pp. 109-115.
  19. Miaou S. G. , and Yen H. L. , "Multichannel ECG compression using multichannel adaptive vector quantization," Communications of IEEE Trans. Biomed. Eng. , vol. 48, no. 10, Oct. 2001, pp. 1203-1207.
  20. Sharma L. N. , Dandapat S. , and Mahanta A. , "Multichannel ECG data compression based on multiscale principal component analysis", IEEE Transactions on Information Technology in Biomedicine, Vol. 16, No. 4, July 2012, pp. 730-736.
  21. Liu B. , Zhang Z. , et al. , "Compression via compressive sensing: A low-power framework for the tele-monitoring of multi-channel physiological signals", IEEE Inter. Conf. on Bioinformatics and Biomedicine (BIBM), China, Dec. 2013, pp. 9-12.
  22. Nave G. , Cohen A. , "ECG compression using long-term prediction," IEEE Trans. Biomed. Eng. , vol. 40, Sept. 1993, pp. 877-885.
  23. http://sensor. nevada. edu/NCCP/Default. aspx
  24. Abdul Karim S. A. , Abdul Karim B. , et al. , "Compression of temperature data by using Daubechies wavelets," Proc. 2nd International Conference on Mathematical Sciences (ICMS2), 2010, pp. 726-734.
Index Terms

Computer Science
Information Sciences

Keywords

Meteorology Multichannel compression Telemedicine Wavelet WSAT.

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