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International Conference on Information Processing

ICIP 2012: Wireless Networks and Computational Intelligence pp 340–349Cite as

Analysis of Blind Source Separation Techniques for Eye Artifact Removal

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 292))

Abstract

Evaluation of several different eye artifact removal techniques for electroencephalographic data is presented in this paper. Data is taken from an emotion recognition experiment, in which subjects undergo five different emotions (joy, sadness, disgust, fear, and neutral). Preprocessing for the EEG Data includes filtering with a Butterworth band-pass filter and a 60Hz notch filter. Three different types of eye artifact removal techniques are explored using the preprocessed data: EOG based linear regression, Principal Component Analysis, and Independent Component Analysis. All techniques used electrooculographic (EOG) data to determine the criteria for feature extraction and removal. Evaluations from our experiments show that all techniques significantly reduce the effects of eye blinks and eye movements in the EEG. The developed metric used in experimentation shows that Independent Component Analysis reduced eye artifacts the best while keeping EEG portions unchanged (Average SSE of 0.1126 for clean EEG portions).

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Dayton, Dayton, USA

    Theus H. Aspiras & Vijayan K. Asari

Authors
  1. Theus H. Aspiras
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  2. Vijayan K. Asari
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, 560 001, Bangalore, India

    K. R. Venugopal

  2. Indian Institute of Science, Bangalore, India

    L. M. Patnaik

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© 2012 Springer-Verlag Berlin Heidelberg

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Aspiras, T.H., Asari, V.K. (2012). Analysis of Blind Source Separation Techniques for Eye Artifact Removal. In: Venugopal, K.R., Patnaik, L.M. (eds) Wireless Networks and Computational Intelligence. ICIP 2012. Communications in Computer and Information Science, vol 292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31686-9_40

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  • DOI: https://doi.org/10.1007/978-3-642-31686-9_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31685-2

  • Online ISBN: 978-3-642-31686-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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