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Automatic Removal of Artifacts from EEG Data Using ICA and Exponential Analysis

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

Eye movements, cardiac signals, muscle noise and line noise, etc. present serious problems for the accuracy of Electroencephalographic (EEG) analysis. Some research results have shown that independent component analysis (ICA) can separate artifacts from multichannel EEG data. Further, considering the nonlinear dynamic properties of EEG signals, exponential analysis can be used to identify various artifacts and basic rhythms, such as α rhythm, etc., from each independent component (IC). In this paper, we propose an automatic artifacts removal scheme for EEG data by combining ICA and exponential analysis. In addition, the proposed scheme can also be used to detect basic rhythms from EEG data. The experimental results on both the simulated data and the real EEG data demonstrate that the proposed scheme for artifacts removal has excellent performance.

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Author information

Authors and Affiliations

  1. Department of Electronics Engineering, Fudan University, Shanghai, 200433, China

    Ning-Yan Bian, Bin Wang & Liming Zhang

  2. Department of Physiology and Biophysics, School of Life Science, Fudan University, Shanghai, 200433, China

    Yang Cao

Authors
  1. Ning-Yan Bian
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  2. Bin Wang
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  3. Yang Cao
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  4. Liming Zhang
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Bian, NY., Wang, B., Cao, Y., Zhang, L. (2006). Automatic Removal of Artifacts from EEG Data Using ICA and Exponential Analysis. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_106

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  • DOI: https://doi.org/10.1007/11760023_106

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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