Efficient Algorithm for ECG Coding
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Full Text(PDF, 3000) PP.
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Author(s) |
Ms. Manjari Sharma, Dr. A. K. Wadhwani |
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KEYWORDS |
Compression, Compression ratio, Cosine transform, ECG, Fourier transform, Frequency domain techniques, PRD, Time domain techniques
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ABSTRACT |
Electrocardiogram (ECG) data compression algorithm is needed to reduce the amount of data to be transmitted, stored and analyzed, without losing the clinical information content. This work investigates a set of ECG data compression schemes in frequency domain to compare their performances in compressing ECG signals. These schemes are based on transform methods such as discrete cosine transform (DCT), fast fourier transform (FFT), discrete sine transform (DST), and their improvements. An improvement of a discrete cosine transform (DCT)-based method for electrocardiogram (ECG) compression is also presented as DCT-II. A comparative study of performance of different transforms is made in terms of Compression Ratio (CR) and Percent root mean square difference (PRD).The appropriate use of a block based DCT associated to a uniform scalar dead zone quantiser and arithmetic coding show very good results, confirming that the proposed strategy exhibits competitive performances compared with the most popular compressors used for ECG compression. Each specific transform is applied to a pre-selected data segment from the MIT-BIH database and then compression is performed.
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References |
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[1] Pranob K. Charles and Rajendra Prasad K. (2011): A Contemporary
Approach For ECG Signal Compression Using Wavelet Transforms.
Signal and Image Processing: An International Journal (SIPIJ). Vol. 2,
No. 1, 178-183.
[2] Yucel Kocyigit, Mehmet Korurek and Bekir Karlik (1999): ECG Data
Compression by Artificial Neural Networks. In ELEC0’99 International
Conference On Electrical And Electronics Enginering. E01.44/D-10, 338-339.
[3] S. Jalaleddine, C. Hutchens, R. Stratan, and W. A. Coberly (1990): ECG
data compression techniques-A unified approach. IEEE Trans. Biomed.
Eng., 37, 329-343.
[4] J. R. Cox, F. M. Nolle, H. A. Fozzard and G. C. Oliver (1968), AZTEC: A
preprocessing scheme for real time ECG rhythm analysis. IEEE Tran.
Biomed. Eng., vol-BME-15, 128-129.
[5] M. Sabarimalai Manikandan and S. Danpat (2006): Wavelet Threshold
based ECG Compression using USZZQ and Huffman Coding of DSM.
In Science Direct Biomedical Signal Processing and Control. 261-270.
[6] B. R. S. Reddy and I. S. N. Murthy (1986): ECG data compression using
Fourier descriptors, IEEE Trans. Bio-med. Eng., BME-33, 428-433.
[7] Mrs. S. O. Rajankar and Dr. S. N. Talbar (2010): An Optimized Transform
for ECG Signal Compression. In Proc. Of Int .Conf. on Advances in
Computer Science, 94-96.
[8] Shang-Gang Miaou, Heng-Lin Yen, Chih-Lung Lin (2002): Wavelet
based ECG compression using Dynamic vector Quantization with Tree
Code vectors in single codebook. In IEEE Transaction on Biomedical
Engineering, vol. 49, no. 7, pp. 671-680.
[9] R.shanta selva Kumari, V Sadasivam (2007): A novel algorithm
for wavelet based ECG signal coding. Science Direct Computers
and Electrical Engineering, 33, pp. 186-194.
[10] J. Abenstein and W. Tompkins (1982): A new data-reduction algorithm
for real time ECG analysis. IEEE Tran. On Biomed. Engg., 29(BME-1):4,
3-8.
[11] N. Ahmed, T. Natarajan and K. R. Rao (1974): Discrete Cosine Transform.
IEEE Trans. Trans. On Computers. C-23, 90-93.
[12] K. R. Rao and P. Yip (1990): Discrete cosine transform – algorithms,
advantages, applications, San Diego: Academic Press.
[13] M. Clausen and U. Baum (1993): Fast Fourier Transforms. BI-Wiss.-Verl.
[14] L. Auslander, E. Feig and S. Winograd (1984): Abelian Semi-simple
Algebras and Algorithms for the Discrete Fourier Transform. In Advances
in Applied Mathematics.5, 31-55.
[15] Tinku Acharya and Ajoy K. Roy. Image Processing Principles and
Applications. John Wiley.
[16] S. Chan and K. Ho (1990): Direct Methods for computing discrete sinu-soidal transforms. IEEE Proceedings, 137, 433-442.
[17] G. Steidl and M. Tasche (1991): A Polynomial approach to Fast algorithms
for Discrete Fourier –cosine and Fourier-sine Transforms. In Mathematics
in Computation, 56 (193), 281-296.
[18] E. Feig and S. Winograd (1992): Fast Algorithms for Discrete Cosine
Trnsforms. IEEE Tran. On Signal Processing.vol-40(9), pp 2174-2193.
[19] Xuancheng Shao and Steven G. Johnson (May 10, 2007): Type-II/III
DCT/DST algorithms with reduced number of arithmetic operations.
Preprint submitted to Elsevier.
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