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Combining Wavelet Transform and Hidden Markov Models for ECG Segmentation

EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 056215 (2006) Cite this article

Abstract

This work aims at providing new insights on the electrocardiogram (ECG) segmentation problem using wavelets. The wavelet transform has been originally combined with a hidden Markov models (HMMs) framework in order to carry out beat segmentation and classification. A group of five continuous wavelet functions commonly used in ECG analysis has been implemented and compared using the same framework. All experiments were realized on the QT database, which is composed of a representative number of ambulatory recordings of several individuals and is supplied with manual labels made by a physician. Our main contribution relies on the consistent set of experiments performed. Moreover, the results obtained in terms of beat segmentation and premature ventricular beat (PVC) detection are comparable to others works reported in the literature, independently of the type of the wavelet. Finally, through an original concept of combining two wavelet functions in the segmentation stage, we achieve our best performances.

References

  1. Li C, Zheng C, Tai C: Detection of ECG characteristic points using wavelet transforms. IEEE Transactions on Biomedical Engineering 1995,42(1):21–28. 10.1109/10.362922

    Article  Google Scholar 

  2. Sahambi JS, Tandon SN, Bhatt RKP: Using wavelet transforms for ECG characterization. An on-line digital signal processing system. IEEE Engineering in Medicine and Biology Magazine 1997,16(1):77–83. 10.1109/51.566158

    Article  Google Scholar 

  3. Senhadji L, Carrault G, Bellanger JJ, Passariello G: Comparing wavelet transforms for recognizing cardiac patterns. IEEE Engineering in Medicine and Biology Magazine 1995,14(2):167–173. 10.1109/51.376755

    Article  Google Scholar 

  4. Chazal P, Reilly RB: A comparison of the use of different wavelet coefficients for the classification of the electrocardiogram. Proceedings of the 15th International Conference on Pattern Recognition (ICPR '00), September 2000, Barcelona, Spain 2: 255–258.

    Article  Google Scholar 

  5. Andreão RV, Dorizzi B, Cortez PC, Mota JCM: Efficient ECG multi-level wavelet classification through neural network dimensionality reduction. Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing (NNSP '02), September 2002, Martigny, Switzerland 395–404.

    Chapter  Google Scholar 

  6. Besar R, Eswaran C, Sahib S, Simpson RJ: On the choice of the wavelets for ECG data compression. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '00), June 2000, Istanbul, Turkey 6: 3614–3617.

    Google Scholar 

  7. Castro B, Kogan D, Geva AB: ECG feature extraction using optimal mother wavelet. Proceedings of the 21st IEEE Convention of the Electrical and ELectronic Engineers in Israel, April 2000, Tel-Aviv, Israel 346–350.

    Google Scholar 

  8. Ahmed SM, Al-Shrouf A, Abo-Zahhad M: ECG data compression using optimal non-orthogonal wavelet transform. Medical Engineering and Physics 2000,22(1):39–46. 10.1016/S1350-4533(00)00010-2

    Article  Google Scholar 

  9. Addison PS: Wavelet transforms and the ECG: a review. Physiological Measurement 2005,26(5):R155–R199. 10.1088/0967-3334/26/5/R01

    Article  Google Scholar 

  10. Andreão RV, Dorizzi B, Boudy J: ECG signal analysis through hidden Markov models. IEEE Transactions on Biomedical Engineering 2006,53(8):1541–1549. 10.1109/TBME.2006.877103

    Article  Google Scholar 

  11. Mallat S: A Wavelet Tour of Signal Processing. Academic Press, San Diego, Calif, USA; 1998.

    MATH  Google Scholar 

  12. Bhatia P, Boudy J, Andreão RV: Wavelet transformation and pre-selection of mother wavelets for ECG signal processing. Proceedings of the 24th IASTED International Conference on Biomedical Engineering, February 2006, Innsbruck, Austria 390–395.

    Google Scholar 

  13. Torrence C, Compo GP: A practical guide to wavelet analysis. Bulletin of the American Meteorological Society 1998,79(1):61–78. 10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2

    Article  Google Scholar 

  14. Rabiner LR, Juang B-H: Fundamentals of Speech Recognition. Prentice-Hall, Englewood Cliffs, NJ, USA; 1993.

    Google Scholar 

  15. Rabiner LR, Lee CH, Juang BH, Wilpon JG: HMM clustering for connected word recognition. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '89), May 1989, Glasgow, UK 1: 405–408.

    Google Scholar 

  16. Laguna P, Mark RG, Goldberger A, Moody GB: A database for evaluation of algorithms for measurement of QT and other waveform intervals in the ECG. Proceedings of the 24th Annual Meeting on Computers in Cardiology (CIC '97), September 1997, Lund, Sweden 673–676.

    Google Scholar 

  17. ANSI/AAMI : Testing and reporting performance results of cardiac rhythm and ST segment. ANSI/AAMI EC 57–293. Arlington: AAMI, 1998, 37 p

    Google Scholar 

  18. Martínez JP, Almeida R, Olmos S, Rocha AP, Laguna P: A wavelet-based ECG delineator: evaluation on standard databases. IEEE Transactions on Biomedical Engineering 2004,51(4):570–581. 10.1109/TBME.2003.821031

    Article  Google Scholar 

  19. Coast DA, Stern RM, Cano GG, Briller SA: An approach to cardiac arrhythmia analysis using hidden Markov models. IEEE Transactions on Biomedical Engineering 1990,37(9):826–836. 10.1109/10.58593

    Article  Google Scholar 

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Authors and Affiliations

  1. Departamento de Engenharia Elétrica, Universidade Federal do Espírito Santo, Campus de Goiaberas, Avenue Fernando Ferrari 514, Vitória, 29060-970, Brazil

    Rodrigo Varejão Andreão & Jérôme Boudy

  2. Département Électronique et Physique, Institut National des Télécommunications, 9 rue Charles Fourier, Evry, 91011, France

    Jérôme Boudy

Authors
  1. Rodrigo Varejão Andreão
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  2. Jérôme Boudy
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Correspondence to Rodrigo Varejão Andreão.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Andreão, R.V., Boudy, J. Combining Wavelet Transform and Hidden Markov Models for ECG Segmentation. EURASIP J. Adv. Signal Process. 2007, 056215 (2006). https://doi.org/10.1155/2007/56215

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