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A Review of ECG Data Compression Techniques

by Butta Singh, Amandeep Kaur, Jugraj Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 11
Year of Publication: 2015
Authors: Butta Singh, Amandeep Kaur, Jugraj Singh
10.5120/20384-2644

Butta Singh, Amandeep Kaur, Jugraj Singh . A Review of ECG Data Compression Techniques. International Journal of Computer Applications. 116, 11 ( April 2015), 39-44. DOI=10.5120/20384-2644

@article{ 10.5120/20384-2644,
author = { Butta Singh, Amandeep Kaur, Jugraj Singh },
title = { A Review of ECG Data Compression Techniques },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 11 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 39-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number11/20384-2644/ },
doi = { 10.5120/20384-2644 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:56:52.853235+05:30
%A Butta Singh
%A Amandeep Kaur
%A Jugraj Singh
%T A Review of ECG Data Compression Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 11
%P 39-44
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Electrocardiogram (ECG) data compression reduced the storage requirements to develop a more efficient tele-cardiology system for cardiac analysis and diagnosis. The ECG compression without loss of diagnostic information is based on the fact that consecutive samples of the digitized ECG carry redundant information that can be removed with very less computing effort. This paper focuses on providing a comparison of the major techniques (direct, transform, parameter extraction and 2D approaches) of ECG data compression which are intended to attain a lossless compressed data with relatively high compression ratio (CR) and low percent root mean square difference (PRD). The paper concludes with the presentation of a framework for evaluation and comparison of ECG compression schemes.

References
  1. Houghton, A. R. and Gray D. 2003. Making sense of the ECG: A Hands-on Guide. Aold Publishing Company.
  2. Singh B. , Singh D. , Jaryal A. K. and Deepak K. K. 2012. Ectopic beats in approximate entropy and sample entropy-based HRV assessment. International Journal of Systems Science, 43(5), 884-893.
  3. Cox J. R. , Nolle F. M. , Fozzard H. A. , and Oliver G. C. 1968. AZTEC, a preprocessing program for real-time ECG rhythm analysis. IEEE Trans. Biomed. Eng. , 15, 128-129.
  4. Mitra M. , Bera J. N. and Gupta R. 2012. Electrocardiogram compression technique for global system of mobile-based offline telecardiology application for rural clinics in India. IET Sci. Meas. Technol. , 6(6), 412-419.
  5. Kulkarni P. K. , Kumar V. and Verma H. K. 1997. Direct data compression techniques for ECG signals: effect of sampling frequency on performance. International Journal of Systems Science, 28(3), 217-228.
  6. Koski A. 1997. Lossless ECG encoding. Comput. Methods and Programs Biomed. , 52(1), 23–33.
  7. Kumar V. , Saxena S. C. and Giri V. K. 2006. Direct data compression of ECG signal for telemedicine. Int. J. Syst. Sci. , 37(1), 45–63.
  8. Shinde A. and Kanjalkar P. 2011. The comparison of different transform based methods for ECG data compression. Proceedings of International Conference on Signal Processing, Communication, Computing and Networking Technologies, 332-335.
  9. Kumar V. , Saxena S. C. , Giri V. K. and Singh D. 2005. Improved modified AZTEC technique for ECG data compression: Effect of length of parabolic filter on reconstructed signal. Comput. Electr. Eng. , 31,334–344.
  10. Tai S. C. 1991. SLOPE- A real-time ECG data compressor. Int. J. Bio-Med. Comput. , 29(2), 175-179.
  11. Barr R. C. , Blanchard S. M. , and Dipersio D. A. 1985. SAPA-2 Is the Fan. IEEE Trans. Biomed. Eng. , 32, 337.
  12. Reddy B. R. S. and Murthy I. S. N. 1986. ECG data compression using Fourier descriptors. IEEE Trans. Biomed. Eng. , 33(4), 428–434.
  13. Batista L. V. , Melcher E. U. and Carvalho L. C. 2001. Compression of ECG signals by optimized quantization of discrete cosine transform coefficients. Med. Eng. Phys. , 23(2), 127–34.
  14. Lee S. , Kim J. and Lee Jong-Ho. 2011. A real-time ECG data compression and transmission algorithm for an e-health device. IEEE Trans. Biomed. Eng. , 58(9), 2448–2455.
  15. Duarte R. C. M. , Matos F. M. and Batista L. V. 2007. Near-lossless compression of ECG signals using perceptual masks in the DCT domain, IFMBE Proceedings, 18, 229–231.
  16. Lu Z. , Kim D. Y. , and Pearlman W. A. 2000. Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm(SPIHT). IEEE Trans. Biomed. Eng. Wavelet, 47(7), 849–856.
  17. Mamaghanian H. , Khaled N. , Atienza D. , and Vandergheynst P. 2011. Compressed sensing for real-time energy-efficient ECG compression on wireless body sensor nodes. IEEE Trans. Biomed. Eng. , 58(9), 2456–2466.
  18. Iwata A. , Nagasaka Y. , and Suzumura N. 1990. Data compression of the ECG using neural network for digital holter monitor. IEEE Eng. Med. Biol. Mag. , 9(3), 53–57.
  19. Al-Shrouf A. , Abo-Zahhad M. , and Ahmed S. M. 2003. A novel compression algorithm for electrocardiogram signals based on the linear prediction of the wavelet coefficients. Digit. Signal Process. , 13(4), 604–622.
  20. Mukhopadhyay S. K. , Mitra S. and Mitra M. 2011. A lossless ECG data compression technique using ASCII character encoding. Comput. Electr. Eng. , 37(4), 486–497.
  21. Mukhopadhyay S. K. , Mitra S. , and Mitra M. 2012. An ECG signal compression technique using ASCII character encoding. Measurement, 45(6), 1651–1660.
  22. Mukhopadhyay S. K. , Mitra S. and Mitra M. 2013. ECG signal compression using ASCII character encoding and transmission via SMS. Biomed. Signal Process. Control, 8(4), 354–363.
  23. Singh B. , Sharma D. , Singh M. and Singh D. 2014. An improved ASCII character encoding method for lossless ECG compression. Advances in Biomedical Science and Eng. , 1(2), 1-11.
  24. Jalaleddine M. S. , Hutchens C. G. , Strattan R. D. , and Coberly W. A. 1990. ECG data compression techniques-A unified approach. IEEE Trans. Biomed. Eng. , 37(4), 329–343.
  25. Mueller W. C. 1978. Arrhythmia detection program for an ambulatory ECG monitor. Biomed. Sci. Instrument. , 14, 81-85.
  26. Borjesson P. , Einarsson G. , and Pahlm O. 1980. Comments on compression of the ECG by prediction or interpolation and entropy encoding. IEEE Trans. Biomed. Eng. , 27(11), 674-675.
  27. Peric Z. , Denic D. , Nikolic J. , Jocic A. , and Jovanovic A. 2013. DPCM quantizer adaptation method for efficient ECG signal compression. Journal of Communications Technology and Electronics, 58(12), 1241–1250.
  28. Kuklinski W. S. 1983. Fast Walsh transform data-compression algorithm ECG applications. Med. & Biol. Eng. Comput. , 21, 465-472.
  29. Benzid R. , Messaoudi A. and Boussaad A. 2008. Constrained ECG compression algorithm using the block-based discrete cosine transform. Digital Signal Processing, 18(1), 56–64.
  30. Bendifallah A. , Benzid R. and Boulemden M. 2011. Improved ECG compression method using discrete cosine transform. Electronics Letters, 47 (2), 87-89.
  31. Fira C. M. and Goras L. 2008. An ECG signals compression method and its validation using NNs. IEEE Transactions on Biomedical Engineering, 55(4), 1319 - 1326.
  32. Byung S. , Yoo S. K. , and Lee M. H. 2006. Wavelet-based low-delay ECG compression algorithm for continuous ECG transmission. IEEE Transactions on Information Technology in Biomedicine, 10(1), 77-83.
  33. Sabarimalai M. M and Dandapat S. 2006. Wavelet threshold based ECG compression using USZZQ and Huffman coding of DSM. Biomedical Signal Processing and Control, 1(4), 261–270.
  34. Benzid, R. , Marir, F. , and Bouguechal N. E. 2007. Electrocardiogram compression method based on the adaptive wavelet coefficients quantization combined to a modified two-role encoder. IEEE Signal Processing Letters, 14(6), 373–376.
  35. Blanco-Velasco M. , Cruz-Roldan F. , Godino-Llorente J. I. , and Barner K. E. 2007. Wavelet packets feasibility study for the design of an ECG compressor. IEEE Transactions on Biomedical Engineering, 54(4), 766–769.
  36. Aggarwal V. and Patterh M. S. 2013. ECG compression using slantlet and lifting wavelet transform with and without normalisation. International Journal of Electronics, 100(5), 626-636.
  37. Xingyuan W. J. 2008. A 2-D ECG compression algorithm based on wavelet transform and vector quantization. Digit. Signal Process. , 18(2), 179–188.
  38. Xingyuan W. and Juan M. 2009. Wavelet-based hybrid ECG compression technique. Analog Integrated Circuits and Signal Processing 59(3), 301–308.
  39. Hilton M. L. 1997. Wavelet and wavelet packet compression of electrocardiograms. IEEE Trans. Biomed. Eng. , 44(5), 394–402.
  40. Johan D. , Nguyen T. Q. , and Tompkins W. J. 1995. ECG compression using discrete symmetric wavelet transform. 17th Int. Conf. IEEE Medicine and Biology, 1, 167-168.
  41. Taubman D. S. , Marcellin M. W. , and Rabbani M. 2002. JPEG2000: Image compression fundamentals, standards and practice. Journal of Electronic Imaging, 11. 286.
  42. Bilgin A. , Marcellin M. W. and Altbach M. I. 2003. compression of electrocardiogram signals using JPEG2000. IEEE Transactions on Consumer Electronics, 49(4), 833-840.
  43. Filho E. B. L. and N. M. M. Rodrigues. 2008. ECG signal compression based on DC equalization and complexity sorting. IEEE Trans. Biomed. Eng. , 55(7), 1923–1926.
  44. Nave G. and Cohen A. 1993. ECG compression using long-term prediction. IEEE Trans. Biomed. Eng. , 40(9), 877–885.
  45. Ruttimann U. E and Pipberger H. V. 1979. Compression of the ECG by prediction or interpolation and entropy encoding. IEEE Trans. Biomed. Eng. , 26(11), 613-623.
  46. Furht B. and Perez A. 1988. An adaptive real-time ECG compression algorithm with variable threshold. IEEE Trans. Biomed. Eng. , 35(6), 489-494.
  47. Trahanias P. and Skordalakis E. 1990. Syntactic pattern recognition of ECG. IEEE Trans. Pattern Anal. Machine Intell. , 12, 648-657.
  48. Abenstein J. P. and Tompkins W. J. 1982. New data-reduction algorithm for real-time ECG analysis. IEEE Trans. Biomed. Eng. , 29, 43-48.
  49. Imai H. , Kimura N. , and Yoshida Y. 1985. An efficient encoding method for electrocardiography using spline functions. Syst. Comput. Japan, 16(3), 85-94.
  50. Chou H. H. , Chen Y. J. , Shiau Y. C. , and Kuo T. S. 2006. An effective and efficient compression algorithm for ECG signals with irregular periods. IEEE Trans. Biomed. Eng. , 53 (6), 1198–1205.
  51. Wei J. , Chang C. , Chou N. and Jan G. 2001. ECG data compression using truncated singular value decomposition. IEEE Trans. Inf. Technol. Biomed. , 5(4), 290–299.
  52. Lee H. and Buckley K. M. 1999. ECG data compression using cut and align beats approach and 2-D transforms. IEEE Trans. Biomed. Eng. , 46(5), 556–564.
  53. Abo-Zahhad M. , Al-Ajlouni A. F. , Ahmed S. M. and Schilling R. J. 2013. A new algorithm for the compression of ECG signals based on mother wavelet parameterization and best-threshold levels selection. Digital Signal Processing, 23(3), 1002–1011.
Index Terms

Computer Science
Information Sciences

Keywords

Electrocardiogram ECG Compression CR PRD PRDN QS

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