A study of optimizing ECG signal processing
Corressponding author's email:
nhunglth@hcmute.edu.vnKeywords:
Electrocardiogram, ECG compression, signal de-nosing, Hilbert-Huang transform, empirical mode decompositionAbstract
Today the new biometric data such as electrocardiogram (ECG), electroencephalogram (EEG) is very interesting due to the demand for remote health monitoring. However the volume of ECG data produced by monitoring systems can be quite large, and data compression is needed for efficient transmission over mobile networks. The research investigated to compress ECG signals using JPEG2000. Also proposed is a method of ECG signal de-noising based on Hilbert-Huang transform. This method uses empirical mode decomposition to decompose the signal into several intrinsic mode functions (IMFs) and then the noisy IMFs are removed by using soft-threshold method. Experiments using the MIT-BIH arrhythmia database illustrate that the proposed approach has improved the performance at a high compression ratio and also achieve the desired effect of de-noising.
Downloads: 0
References
N.E.Huang, The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis, Pro.R.Soc, London, 1998.
T. M. Lehman, C. Gonner, and K. Spitzer, Survey: Interpolation methods in medical image processing, IEEE Trans. on Medical Imaging, vol. 18, Nov. 1999.
Wang Chun, Peng Dong-ling, The Hilbert-Huang transform and its application on signal de-noising, China Journal of Scientific Instrument, Vol.25, no.4, 2004.
H.H. Chou, Y.J. Chen, Y.C. Shiau, and T.S. Kuo, An effective and efficient compression algorithm for ECG signals with irregular periods, IEEE Transactions on Biomedical Engineering, vol. 53, no. 6, 2006.
J.-J. Wei, C.-J. Chang, N.-K. Chou, and G.-J. Jan, ECG data compression using truncated singular value decomposition, IEEE Trans. on Information Technology in Biomedicine, vol. 5, Dec. 2001.
Moody GB, Mark RG, The impact of the MIT-BIH Arrhythmia Database, IEEE Eng in Med and Bio, 20(3):45-50 (May-June 2001).
A. Bilgin, M. W. Marcellin, and M. I. Altbach, Compression of electrocardiogram signals using JPEG2000, IEEE Transactions on Consumer Electronics, vol. 49, no. 4, 2003.
Charilaos Christopoulos1, Athanassios, and TouradjEbrahimi, The JPEG2000 still image coding system: An overview, Published in IEEE Transactions on Consumer Electronics, Vol. 46, No. 4, November 2000.
D. Taubman, High performance scalable image compression with EBCOT, IEEE Trans. Image Processing, Vol. 9, No. 7, July 2000.
Chia-Chun Sun, Shen-Chuan Tai, Beat-Based ECG Compression Using Gain-Shape Vector Quantization, IEEE Transactions on Biomedical Engineering, Vol. 52, n. 11, pp. 1882-1888, 2005
Downloads
Published
How to Cite
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright © JTE.
