Skip to main content
SpringerLink
Log in

ECG segmentation using time-warping

  • Conference paper
  • First Online:
Advances in Intelligent Data Analysis Reasoning about Data (IDA 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1280))

Included in the following conference series:

Abstract

We present a method to segment the electrocardiogram (ECG) using time-warping, a technique commonly used in speech recognition. First, the ECG is transformed to a piecewise linear approximation. Next, the slope amplitude is used to cut the ECG into distinct periods (R-R interval). These periods are then compared to each other using timewarping, and the pair which is most similar is selected. Finally, this pair is segmented into the different subpatterns usually encountered in the ECG, such as the QRS complex, the T wave, and the P wave.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J.P. Abenstein and W.J. Tompkins. A new data-reduction algoritm for real-time ECG analysis. IEEE trans. on Biomedical Eng., 29(1):43–48, 1982.

    Article  Google Scholar 

  2. G. Belforte, R. De Mori, and F. Ferraris. A contribution to the automatic processing of electrocardiograms using syntactic methods. IEEE trans. on Biomedical Eng., 26(3):125–136, 1979.

    Article  Google Scholar 

  3. A. Cohen. Biomedical signal processing, volume 2. CRC Press, Inc., 1986.

    Google Scholar 

  4. P.M.A. de Graaf, G.C. van den Eijkel, H.J.L.M. Vullings, and B.A.J.M. de Mol. A decision-driven design of a decision support system in anesthesia. Artificial Intelligence in Medicine, Admitted to the special issue on “Decision support in the operating theatre and intensive care”, 1997.

    Google Scholar 

  5. G.M. Friesen, T.C. Jannett, M.A. Jadallah, S.L. Yates, S.R. Quint, and H.T. Nagle. A comparison of the noise sensitivity of nine QRS detection algorithms. IEEE trans. on Biomedical Eng., 37(1):85–98, 1990.

    Article  Google Scholar 

  6. B. Furht and A. Perez. An adaptive real-time ECG compression algorithm with variable treshold. IEEE trans. on Biomedical Eng., 35(6):489–494, 1988.

    Article  Google Scholar 

  7. A. Koski, M. Juhola, and M. Meriste. Syntactic recognition of ECG signals by attributed finite automata. Pattern Recognition, 28(12):1927–1940, 1995.

    Article  Google Scholar 

  8. P. Laguna, R. Jané, and P. Caminal. Automatic detection of wave boundaries in multilead ECG signals: validation with the CSE database. Computers and biomedical research, 27:45–60, 1994.

    Article  Google Scholar 

  9. T. Pavlidis and S.L. Horowitz. Segmentation of plane curves. IEEE transacions on Computers, c-23(8):860–870, 1974.

    Article  MathSciNet  Google Scholar 

  10. E. Pietka. Feature extraction in computerized approach to the ECG analysis. Pattern Recognition, 24(2):139–146, 1991.

    Article  Google Scholar 

  11. L.R. Rabiner and B-H. Juang. Fundamentals of speech recognition. Signal Processing series. Prentice Hall, 1993.

    Google Scholar 

  12. H. Sakoe and S. Chiba. Dynamic programming algorithm optimization for spoken word recognition. IEEE trans. on Acoustics, Speech, and Signal Processing, 26(1):43–49, 1978.

    Article  MATH  Google Scholar 

  13. D. Sankoff and J.B. Kruskal. Time warps, string edits, and macromolecules: the theory and practice of sequence comparison, chapter 1 & 4. Addison-Wesley, 1983.

    Google Scholar 

  14. E. Skordalakis. Recognition of the shape of the ST-segment in ECG waveforms. IEEE trans. on Biomedical Eng., 33(10):972–974, 1986.

    Article  Google Scholar 

  15. L. Sörnmo, O. Pahlm, and M-E. Nygàrds. Adaptive QRS detection: A study of performance. IEEE trans. on Biomedical Eng., 32(6):392–401, 1985.

    Article  Google Scholar 

  16. Y. Suzuki. Self-organizing QRS-wave recognition in ECG using neural networks. IEEE trans. on Neural Networks, 6(6):1469–1477, 1995.

    Article  Google Scholar 

  17. P. Trahanias and E. Skordalakis. Syntactic pattern recognition of the ECG. IEEE trans. on pattern analysis and machine intelligence, 12(7):648–657, 1990.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Delft University of Technology, Mekelweg 4, 2628, CD Delft, The Netherlands

    H. J. L. M. Vullings, M. H. G. Verhaegen & H. B. Verbruggen

Authors
  1. H. J. L. M. Vullings
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. H. G. Verhaegen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. H. B. Verbruggen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Xiaohui Liu Paul Cohen Michael Berthold

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag

About this paper

Cite this paper

Vullings, H.J.L.M., Verhaegen, M.H.G., Verbruggen, H.B. (1997). ECG segmentation using time-warping. In: Liu, X., Cohen, P., Berthold, M. (eds) Advances in Intelligent Data Analysis Reasoning about Data. IDA 1997. Lecture Notes in Computer Science, vol 1280. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0052847

Download citation

  • DOI: https://doi.org/10.1007/BFb0052847

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63346-4

  • Online ISBN: 978-3-540-69520-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation