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International Conference on Intelligent Computing

ICIC 2014: Intelligent Computing in Bioinformatics pp 322–329Cite as

Classification of Ventricular Tachycardia and Fibrillation Based on the Lempel-Ziv Complexity and EMD

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 8590))

Abstract

Detection of ventricular tachycardia (VT) and ventricular fibrillation (VF) in electrocardiography (ECG) has clinical research significance. The complexity of the heart signals has changed significantly, when the heart state switches from normal sinus rhythm to VT or VF. With the consideration of the non-stationary of VT and VF, we proposed a novel method for classification of VF and VT in this paper, based on the Lempel-Ziv (LZ) complexity and empirical mode decomposition (EMD). The EMD first decomposed ECG signals into a set of intrinsic mode functions (IMFs). Then the complexity of each IMF was used as a feature in order to discriminate between VF and VT. A public dataset was utilized for evaluating the proposed method. Experimental results showed that the proposed method could successfully distinguish VF from VT with the highest accuracy up to 97.08%.

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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
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  2. Qingfang Meng
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  3. Yuehui Chen
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  4. Zaiguo Zhang
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer Science and Engineering Inha University, Incheon, South Korea

    Kyungsook Han

  3. Department of Biotechnology, Indian Institute of Technology Madras, 600 036, Chennai, Tamilnadu, India

    Michael Gromiha

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© 2014 Springer International Publishing Switzerland

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Xia, D., Meng, Q., Chen, Y., Zhang, Z. (2014). Classification of Ventricular Tachycardia and Fibrillation Based on the Lempel-Ziv Complexity and EMD. In: Huang, DS., Han, K., Gromiha, M. (eds) Intelligent Computing in Bioinformatics. ICIC 2014. Lecture Notes in Computer Science(), vol 8590. Springer, Cham. https://doi.org/10.1007/978-3-319-09330-7_39

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  • DOI: https://doi.org/10.1007/978-3-319-09330-7_39

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09329-1

  • Online ISBN: 978-3-319-09330-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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