Skip to main content
SpringerLink
Log in

A Multi-valued Coarse Graining of Lempel-Ziv Complexity and SVM in ECG Signal Analysis

  • Conference paper
  • First Online:
Intelligent Computing Theories and Methodologies (ICIC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9225))

Included in the following conference series:

  • 1751 Accesses

Abstract

Lempel-Ziv (LZ) complexity method has been widely applied to detection ventricular tachycardia (VT) and ventricular fibrillation (VF). The coarse-graining process (Quantization levels, \( L \)) plays an important role in the LZ complexity measure analysis. In this paper, we present a multi-valued coarse-graining process approaches (\( L > 2 \)), our test shows that this algorithm is superior to the two-valued coarse-graining of LZ complexity approaches (\( L = 2 \)) in VT and VF separation. Furthermore, we used support vector machine (SVM) classifier to discriminate VF and VT. Using the complexity as a feature to input classifiers can significantly improve the classification results. Particularly, optimum performance is achieved at a 4-second length.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

References

  1. Lempel, A., Ziv, J.: On the complexity of finite sequences. IEEE Trans. Inform. Theory 22, 75–81 (1976)

    Article  MathSciNet  Google Scholar 

  2. Zhang, X.S., Zhu, Y.S., Thakor, N.V., Wang, Z.Z.: Detecting ventricular tachycardia and fibrillation by complexity measure. IEEE Trans. Biomed. Eng. 46, 548–555 (1999)

    Article  Google Scholar 

  3. Zhang, X., Roy, R.J., Weber, E.: EEG complexity as a measure of depth of anesthesia for patients. IEEE Trans. Biomed. Eng. 12, 1424–1433 (2001)

    Article  Google Scholar 

  4. Nagarajan, R.: Quantizing physiological data with Lempel-Ziv complexity-certain issues. IEEE Trans. Biomed. Eng. 49(11), 1371–1373 (2002)

    Article  Google Scholar 

  5. Otu, H.H.: K. Sayood.: Sequence analyses. Bioinformatics 19, 2122–2130 (2003)

    Article  MATH  Google Scholar 

  6. Xu, Y., Ma, Q.D.Y., Schmitt, D.T., et al.: Effects of coarse-graining on the scaling behavior of long-range correlated and anti-correlated signals. Fuel Energy Abstr. 390, 4057–4059 (2011)

    Google Scholar 

  7. Zhang, H.X., Zhu, Y.S., Wang, Z.M.: Complexity measure and complexity rate information based detection of ventricular tachycardia and fibrillation. Med. Biol. Eng. Comput. 38, 553–557 (2000)

    Article  Google Scholar 

  8. Zhou, S., Zhang, Z., Gu, J.: Interpretation of coarse-graining of Lempel-Ziv complexity measure in ECG signal analysis. In: 33rd Annual International Conference of the IEEE EMBS Boston, Massachusetts, USA, August 30–September 3 2011

    Google Scholar 

  9. Cortes, C.: V. Vapnik.: Support-vector networks. Mach. Learn. 20(3), 273–297 (1995)

    MATH  Google Scholar 

  10. Pontil, M., Verri, A.: Support vector machines for 3D object recognition. IEEE Trans. Pattern Anal. Mach. Intell. 20(6), 637–646 (1998)

    Article  Google Scholar 

  11. Li, S., Zhou, W., QiYuan, S.G., Cai, D.: Feature extraction and recognition of ictal EEG using EMD and SVM. Comput. Biol. Med. 43, 807–816 (2013)

    Article  Google Scholar 

  12. Luo, Z., Cao, M.: EEG feature analysis of motor imagery based on Lempel-Ziv complexity at multi-scale. Chin. J. Sens. Actuators 24(7), 1033–1037 (2011)

    Google Scholar 

  13. Sarlabous, L., Torres, A., Fiz, J.A., Morera, J., Jané, R.: Index for estimation of muscle force from mechanomyography based on the Lempel-Ziv algorithm. J. Electromyogr. Kinesiol. 23, 548–557 (2013)

    Article  Google Scholar 

  14. Aboy, M., Hornero, R., Abásolo, D., Álvarez, D.: Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis. IEEE Trans. Biomed. Eng. 53(11), 2282–2288 (2006)

    Article  Google Scholar 

  15. Gómez, C., Hornero, R., Abásolo, D., Fernández, A., López, M.: Complexity analysis of the magnetoencephalogram background activity in Alzheimer’s disease patients. Med. Eng. Phys. 28, 851–859 (2006)

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 61201428, 61302090), the Natural Science Foundation of Shandong Province, China (Grant No. ZR2010FQ020, ZR2013FL002), the Shandong Distinguished Middle-aged and Young Scientist Encourage and Reward Foundation, China (Grant No. BS2009SW003, BS2014DX015), the Graduate Innovation Foundation of University of Jinan (Grant No. YCX13011).

Author information

Authors and Affiliations

  1. The School of Information Science and Engineering, University of Jinan, Jinan, 250022, China

    Deling Xia, Qingfang Meng & Yuehui Chen

  2. Shandong Provincial Key Laboratory of Network Based Intelligent Computing, Jinan, 250022, China

    Deling Xia, Qingfang Meng & Yuehui Chen

  3. CET Shandong Electronics Co., Ltd., Jinan, 250101, China

    Zaiguo Zhang

Authors
  1. Deling Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qingfang Meng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yuehui Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zaiguo Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qingfang Meng .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Polytecnic of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Xia, D., Meng, Q., Chen, Y., Zhang, Z. (2015). A Multi-valued Coarse Graining of Lempel-Ziv Complexity and SVM in ECG Signal Analysis. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9225. Springer, Cham. https://doi.org/10.1007/978-3-319-22180-9_51

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-22180-9_51

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22179-3

  • Online ISBN: 978-3-319-22180-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation