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Expert System of Ischemia Classification Based on Wavelet MLP

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Knowledge Engineering and Management

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 214))

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Abstract

This paper proposes an expert system capable of identifying pathological ECG with signs of ischemia. The system design is based on the knowledge of a team of cardiologists who have been commissioned to identify ECG segments that contain information about the target disease, and subsequently validated the results of the system. The expert system comprises four modules, namely, a pre-processing module which is responsible for improving the SNR, a segmentation module, a DSP module which is responsible for applying the wavelet transform to improve the response of the last module, in charge of the classification. We used a database of about 800 ECG obtained in different clinical and extensively annotated by the team of cardiologists. The system achieves a sensitivity of 87.7 % and a specificity of 82.6 % with the set of ECG testing.

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Acknowledgments

This investigation is allocated in the project TSI-020302-2010-136.

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Authors and Affiliations

  1. Rafaela Regional Faculty, Argentinian Technological University, 2300, Rafaela, Santa Fe, Argentina

    Javier F. Fornari

  2. Department of Languages and Computer Sciences, Malaga University, Malaga, Spain

    José I. Peláez

Authors
  1. Javier F. Fornari
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  2. José I. Peláez
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Corresponding author

Correspondence to Javier F. Fornari .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, China, People's Republic

    Fuchun Sun

  2. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China, People's Republic

    Tianrui Li

  3. Department of Computer Science and Techn, Tsinghua University, Beijing, China, People's Republic

    Hongbo Li

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© 2014 Springer-Verlag Berlin Heidelberg

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Fornari, J.F., Peláez, J.I. (2014). Expert System of Ischemia Classification Based on Wavelet MLP. In: Sun, F., Li, T., Li, H. (eds) Knowledge Engineering and Management. Advances in Intelligent Systems and Computing, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37832-4_39

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  • DOI: https://doi.org/10.1007/978-3-642-37832-4_39

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37831-7

  • Online ISBN: 978-3-642-37832-4

  • eBook Packages: EngineeringEngineering (R0)

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