Fiducial points extraction and characteristicwaves detection in ECG signal using a model-based bayesian framework

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2013, Pages 1257-1261

  Akhbari, Mahsa ^a,b   Shamsollahi, Mohammad B ^a   Jutten, Christian ^b  

^a SHARIF UNIVERSITY OF TECHNOLOGY   (Iran)

^b INSTITUT UNIVERSITAIRE DE FRANCE   (France)

Author keywords

Characteristic Waves; Electrocardiogram (ECG); Extended Kalman Filter (EKF); Fiducial Point Extraction; Segmentation

Indexed keywords

AUTOMATIC DETECTION; BAYESIAN FRAMEWORKS; DYNAMIC PARAMETERS; EXTRACTION OF CHARACTERISTICS; FIDUCIAL POINTS; MEAN AND STANDARD DEVIATIONS; QUALITATIVE EVALUATIONS; RELIABLE DETECTION;

DIAGNOSIS; ESTIMATION; EXTENDED KALMAN FILTERS; EXTRACTION; IMAGE SEGMENTATION; SIGNAL DETECTION;

ELECTROCARDIOGRAPHY;

EID: 84890527267     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2013.6637852     Document Type: Conference Paper

References (15)

1. B. Kohler, C. Hennig, and R. Orglmeister, "The princi-ples of software QRS detection: Reviewing and compar-ing algorithms for detecting this important ECG wave-form," IEEE Engineering in Medicine and Biology, pp. 42-57, February 2002.
2. C. Lin, C. Mailhes, and J. Y. Tourneret, "P- and T-wave delineation in ECG signals using a bayesian approach and a partially collapsed gibbs sampler," IEEE Trans-action on Biomedical Engineering, vol. 57, no. 12, pp. 2840-2849, December 2010.
3. C. Lin, G. Kail, J. Y. Tourneret, C. Mailhes, and F. Hlawatsch, "P and T wave delineation and waveform estimation in ECG signals using a block gibbs sampler," in Proc. IEEE Int. Conf. on Acoust., Speech and Sig. Proc. (ICASSP), Prague, Czech Republic, May 2011, pp. 537-540.
4. N. P. Hughes, Probabilistic Models for Automated ECG Interval Analysis, Ph.D. thesis, Department of Engineer-ing Science, University of Oxford, 2006.
5. Y. Sun, K. L. Chan, and Sh. M. Krishnan, "Character-istic wave detection in ECG signal using morphological transform," BMC Cardiovascular Disorders, September 2005.
6. P. E. McSharry, G. D. Clifford, L. Tarassenko, and L. A. Smith, "A dynamic model for generating synthetic elec-trocardiogram signals," IEEE Trans. Biomed. Eng., vol. 50, no. 3, pp. 289-294, Mar. 2003.
7. R. Sameni, M. B. Shamsollahi, C. Jutten, and G. D. Clif-ford, "Nonlinear bayesian filtering framework for ECG denoising," IEEE Trans. Biomed. Eng., vol. 54, no. 12, pp. 2172-2185, Dec. 2007.
8. O. Sayadi and M. B. Shamsollahi, "ECG denoising and compression using a modified extended kalman fil-ter structure," IEEE Trans. Biomed. Eng., vol. 55, no. 9, pp. 2240-2248, Sep. 2008.
9. O. Sayadi and M. B. Shamsollahi, "A model-based bayesian framework for ECG beat segmentation," Phys-iol. Meas., vol. 30, pp. 335-352, March 2009.
10. O. Sayadi, M. B. Shamsollahi, and G. Clifford, "Robust detection of premature ventricular contractions using a wave-based bayesian framework," IEEE Trans. Biomed. Eng., vol. 57, pp. 353-362, February 2010.
11. QT Database [online], Available: http://www.physionet.org/physiobank/ database/qtdb/.
12. P. Laguna, R. G. Mark, A. Goldberg, and G. B. Moody, "A database for evaluation of algorithms for measure-ment of QT and other waveform intervals in the ECG," IEEE, Computers in Cardiology, vol. 24, pp. 673-676, 1997.
13. S. M. Kay, Fundamentals of statistical Signal Process-ing:Estimation Theory, Prentice Hall PTR, 2003.
14. M. Akhbari, M. B. Shamsollahi, and C. Jutten, "ECG denoising using angular velocity as a state and an obser-vation in an extended kalman filter framework," in 34th Annual International Conference of the IEEE EMBS, San Diego, California, USA, Aug. 2012, pp. 2897-2900.
15. O. Sayadi, "Model-based ECG processing (denoising, compression and classification)," M.S. thesis, Sharif University of Technology, Faculty of Electrical Engi-neering, August 2007.