Model-based ECG denoising using empirical mode decomposition

2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009

Volumn , Issue , 2009, Pages 191-196

  Lu, Yan ^a   Yan, Jingyu ^a   Yam, Yeung ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

DE-NOISING; ECG DATA; EMPIRICAL MODE DECOMPOSITION; MODEL FIT; MODEL-BASED; MORPHOLOGICAL FEATURES; NOISE COMPONENTS; QRS COMPLEXES; RESIDUAL SIGNALS;

BIOINFORMATICS; ELECTROCHROMIC DEVICES; SIGNAL PROCESSING;

ELECTROCARDIOGRAPHY;

EID: 74549161494     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIBM.2009.14     Document Type: Conference Paper

References (17)

1. D. Zhang, "Wavelet Approach for ECG baseline wander correction and noise reduction," in Proc. 27th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. (EMBS), Shanghai, China, 2005, pp. 1212-1215.
2. I. I. Christov and I. K. Daskalov, "Filtering of electromyogram artifacts from the electrocardiogram," Med. Eng. Phys., vol. 21, pp. 731-736, 1999.
3. A. Gotchev, N. Nikolaev, and K. Egiazarian, "Improving the transform domain ECG denoising performance by applying interbeat and intrabeat decorrelating transforms," in Proc. 2001 IEEE Int. Symp. Circuits Syst. (ISCAS), Sydney, 2001, pp. 17-20.
4. G. Moody and R. Mark, "QRS morphology representation and noise estimation using the Karhunen-Loève transform," Comput. Cardiology, vol. 16, pp. 269-272, 1989.
5. A. Barros, A. Mansour, and N. Ohnishi, "Removing artifacts from ECG signals using independent components analysis," Neurocomputing, vol. 22, pp. 173-186, 1998.
6. G. D. Clifford and L. Tarassenko, "One-pass training of optimal architecture auto-associative neural network for detecting ectopic beats," Electron. Lett., vol. 37, no. 18, pp. 1126-1127, Aug. 2001.
7. P. M. Agante and J. P. M. de Sá, "ECG noise filtering using wavelets with soft-thresholding methods," in Proc. Comput. Cardiology 1999, 1999, pp. 535-542.
8. P. E. McSharry, G. D. Clifford, L. Tarassenko, and L. A. Smith, "A dynamic model for generating synthetic electrocardiogram signals," IEEE Trans. Biomed. Eng., vol. 50, no. 3, pp. 289-294, Mar. 2003.
9. G. D. Clifford, A. Shoeb, P. E. McSharry, and B. A. Janz, "Model-based filtering, compression and classification of the ECG," Int. J. Bioelectromagnetism, vol. 7, no. 1, pp. 158-161, 2005.
10. N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N.-C. Yen, C. C. Tung, and H. H. Liu, "The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis," Proc. Roy. Soc. Lond., vol. A 454, pp. 903-995, 1998.
11. B. Weng, M. Blanco-Velasco, and K. E. Barner, "ECG denoising based on the empirical mode decomposition," in Proc. 28th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., New York, 2006, pp. 1-4.
12. The MIT-BIH Arrhythmia Database [Online]. Available: http:// www.physionet.org/physiobank/database/mitdb/
13. R. Sameni,M. B. Shamsollahi, C. Jutten, and M. Babaie-Zadeh, "Filtering noisy ECG signals using the extended Kalman filter based on a modified dynamic ECG model," in Proc. 32nd Annu. Int. Conf. Comput. Cardiol., Lyon, France, 2005, pp. 1017-1020.
14. H. Liang, Q.-H. Lin, and J. D. Z. Chen, "Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease," IEEE Trans. Biomed. Eng., vol. 52, no. 10, pp. 1692-1701, October 2005.
15. P. Flandrin and P. Gonçalves, "Empirical mode decompositions as data-driven wavelet-like expansions," Int. J. Wavelets, Multires., Inf. Process., vol. 2, no. 4, pp. 477-496, 2004.
16. Y. Kopsinis, S. McLaughlin, "Empirical mode decomposition based denoising techniques," in Proc. 1st IAPR Workshop on Cog. Inf. Process. (CIP), Santorini, Greece, 2008, pp. 42-47.
17. ECGSYN-A realistic ECG waveform generator [Online]. Available: http://www.physionet.org/physiotools/ecgsyn/