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ICA and Committee Machine-Based Algorithm for Cursor Control in a BCI System

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3496))

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Abstract

In recent years, brain-computer interface (BCI) technology has emerged very rapidly. Brain-computer interfaces (BCIs) bring us a new communication interface technology which can translate brain activities into control signals of devices like computers, robots. The preprocessing of electroencephalographic (EEG) signal and translation algorithms play an important role in EEG-based BCIs. In this study, we employed an independent component analysis (ICA)-based preprocessing method and a committee machine-based translation algorithm for the offline analysis of a cursor control experiment. The results show that ICA is an efficient preprocessing method and the committee machine is a good choice for translation algorithm.

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References

  1. Li, Y., Wang, J., Zurada, J.M.: Blind Extraction of Singularly Mixed Sources Signals. IEEE Trans. On Neural Networks 11, 1413–(2000)

    Article  Google Scholar 

  2. Li, Y., Wang, J.: Sequential Blind Extraction of Linearly Mixed Sources. IEEE Trans. on Signal Processing 50, 997–1006 (2002)

    Article  Google Scholar 

  3. Cichocki, A., Amari, S.: Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications. John Wiley, New York (2002)

    Book  Google Scholar 

  4. Makeig, S., Bell, A.J., Jung, T.-P., Sejnowski, T.J.: Independent Component Analysis of Electroencephalographic Data. Adv Neural Info Processing Systems 8, 145–151 (1996)

    Google Scholar 

  5. Comon, P.: Independent Component Analysis. A New Concept Signal Procesing 36, 287–314 (1994)

    MATH  Google Scholar 

  6. Bell, A.J., Sejnowski, T.J.: An Information-maximization Approach to Blind Separation and Blind Deconvolution. Neural Computation 7, 1129–1159 (1995)

    Article  Google Scholar 

  7. Amari, S., Chichocki, A., Yang, H.H.: A New Learning Algorithm for Blind Signal Separation. Advances in Neural Information Processing 8, 757–763 (1996)

    Google Scholar 

  8. Choi, S., Chichocki, A., Amari, S.: Flexible Independent Component Analysis. In: Proc. of the 1998 IEEE Workshop on NNSP, pp. 83–92 (1998)

    Google Scholar 

  9. Ramoser, H., Gerking, J.M., Pfurtscheller, G.: Optimal Spatial Filtering of Single Trial EEG during Imagined Hand Movement. IEEE Trans. Rehab. Eng. 8, 441–446 (2000)

    Article  Google Scholar 

  10. McFarland, D.J., McCane, L.M., David, S.V., Wolpaw, J.R.: Spatial Filter Selection for EEG-based Communication. Electroenc. Clin. Neurophys. 103, 386–394 (1997)

    Article  Google Scholar 

  11. Amari, S., Murata, N., Müller, K.-R., Finke, M., Yang, H.: Statistical Theory of Overtraining-Is Cross-Validation Asymptotically Effective. In: Advances in Neural Information Processing Systems, vol. 8, pp. 176–182. MIT Press, Cambridge (1996)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Automation Science and Engineering, South China University of Technology, Guangzhou, 510640, China

    Jianzhao Qin & Yuanqing Li

  2. Institute for Infocomm Research, Singapore, 119613

    Yuanqing Li

  3. Laboratory for Advanced Brain Signal Processing, RIKEN Brain Science Institute, Wako shi, Saitama, 3510198, Japan

    Andrzej Cichocki

Authors
  1. Jianzhao Qin
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  2. Yuanqing Li
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  3. Andrzej Cichocki
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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. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiaofeng Liao

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

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Qin, J., Li, Y., Cichocki, A. (2005). ICA and Committee Machine-Based Algorithm for Cursor Control in a BCI System. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_156

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  • DOI: https://doi.org/10.1007/11427391_156

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25912-1

  • Online ISBN: 978-3-540-32065-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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