Abstract
The new method proposed here consists of a combination of two transforms. The hybrid technique consists of Discrete Cosine Transform (DCT) and 1D or 2D discrete wavelet Transform (DWT). The method is suitable for compression of ECG signals. In this research, different records of MIT–BIH data base are used. The performance measure of the technique is done with the help of Compression Ratio (CR) and Percent Root Mean Square Difference (PRD). The threshold based technique is used to achieve better CR. The threshold value is selected based on the R peak. The QRS complex is detected in order to select the R peak. The threshold level is selected as 1, 0.5, and 0.1 % of the R peak. Further improvement in the CR is achieved by the DWT decomposition method. The level of decomposition is carefully selected to achieve improved CR.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Tomkins, W.J.: Biomedical Digital Signal Processing, 1st edn. PHI, USA
Rooijakkers M.J., et.al.: Low complexity R peak detection in ECG signals: a preliminary step towards fetal monitoring. In: IEEE Annual International Conference of the Engineering in Medicine and Biology society, pp. 1761–1764 (2011)
Tang J-h. et.al.: An algorithm of R-peak detection in ECG based on Empirical mode decomposition. In: IEEE Fourth International Conference on Natural Computation, vol. 5, pp. 624–627 (2008)
Khandpur, R.S: Handbook of Biomedical Instrumentation, 6th edn, TMH, New York
Jalaleddine, S.S., Hutchens, C., Strattan, R., Coberly, W.: ECG data compression techniques—a unified approach. IEEE Trans. Biomed. Eng. 37, 329–343 (1990)
Pooyan, M., Taheri, A., Moazami-Goudarzi, M., Saboori, I.: Wavelet compression of ECG signals using SPIHT algorithm. Int. J. Inf. Commun. Eng. 1(4), 219–225 (2005)
Mohammadpour, T.I., Mollaei, M.R.K.: ECG compression with thresholding of 2D—wavelet transform coefficients and run length coding. Euro. J. Sci. Res., ISSN 1450 27(2), 248–257 (2009)
Ktata, S., Ouni, K., Ellouze, N.: A novel compression algorithm for electrocardiogram signals based on wavelet transform and SPIHT. Int J Signal Proc. 5(4), 253–258 (2009)
Moazami-Goudarzi, M., Moradi, M.H.: Electrocardiogram signal compression using multi wavelet transform. Trans. Eng. Comput. Technol. 6, 332–336 (2005)
Dakua1, S.P., Sahambi, J.S.: Lossless ECG compression for event recorder based on burrows-wheeler transformation and move-to-front coder. Int. J. Recent Trends Eng. 1(3), 120–123 (2009)
Aggarwal, V., Patterh, M.S.: Quality controlled ECG compression using discrete cosine transform (DCT) and laplacian pyramid (LP), Multimedia Signal Processing and Communication Technologies, IMPACT 09, 12–15 (2009)
Abu-Zahhad, M., et al.: An efficient technique for compressing ECG signals using QRS detection, estimation, and 2D DWT coefficients thresholding (2012). doi:10.1155/2012/742786, Article ID742786, Hindawi Publishing Corporation (Research Article)
Kumar, R. et.al: Beta wavelet based ECG signal compression using lossless encoding with modified thresholding. Comput. Electr. Eng. J. 39(1): 130–140
Zahhad, M.A., et al.: ECG signal compression technique based on discrete wavelet transform and QRS complex estimation. Sig. Process. Int. J. (SPIJ) 4(2), 138–160 (2010)
Zahhad, M.A. et.al.: Compression of ECG signals based on DWT and exploiting the correlation between ECG signal samples. Int. J. Commun. Netw. Syst. Sci. (Scientific Research), 1, 53–70 (2014)
Abo-Zahhad, M., et al.: A new algorithm for the compression of ECG signals based on mother wavelet parametrization and best threshold level selection. Dig. Sig. Process. J. 23(3), 1002–1011 (2013)
Acknowledgments
The authors would like to thank the Principal, Head of Department & PhD coordinator Sinhgad college of Engineering, for their support & guidance to publish this paper. Also we would like to thank Director and Principal, AIT for the constant support and guidance to publish this research work.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Surekha, K.S., Patil, B.P. (2015). Compression of ECG Signal Using Hybrid Technique. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems in Science and Information 2014. SAI 2014. Studies in Computational Intelligence, vol 591. Springer, Cham. https://doi.org/10.1007/978-3-319-14654-6_24
Download citation
DOI: https://doi.org/10.1007/978-3-319-14654-6_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14653-9
Online ISBN: 978-3-319-14654-6
eBook Packages: EngineeringEngineering (R0)