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Real-Time Embedded EEG-Based Brain-Computer Interface

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Advances in Neuro-Information Processing (ICONIP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5507))

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Abstract

Online artifact rejection, feature extraction, and pattern recognition are essential to advance the Brain Computer Interface (BCI) technology so as to be practical for real-world applications. The goals of BCI system should be a small size, rugged, lightweight, and have low power consumption to meet the requirements of wearability, portability, and durability. This study proposes and implements a moving-windowed Independent Component Analysis (ICA) on a battery-powered, miniature, embedded BCI. This study also tests the embedded BCI on simulated and real EEG signals. Experimental results indicated that the efficacy of the online ICA decomposition is comparable with that of the offline version of the same algorithm, suggesting the feasibility of ICA for online analysis of EEG in a BCI. To demonstrate the feasibility of the wearable embedded BCI, this study also implements an online spectral analysis to the resultant component activations to continuously estimate subject’s task performance in near real time.

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Author information

Authors and Affiliations

  1. Brain Research Center, National Chiao Tung University, 1001 University Road, Hsinchu, 30010, Taiwan, R.O.C.

    Li-Wei Ko, I-Ling Tsai, Fu-Shu Yang, Jen-Feng Chung, Shao-Wei Lu, Tzyy-Ping Jung & Chin-Teng Lin

  2. Department of Electrical and Control Engineering, National Chiao Tung University, 1001 University Road, Hsinchu, 30010, Taiwan, R.O.C.

    Li-Wei Ko, I-Ling Tsai, Jen-Feng Chung & Chin-Teng Lin

  3. Swartz Center for Computational Neuroscience, University of California San Diego, Suite 320, 4150 Regents Park Row, La Jolla, CA 92037-1417, USA

    Tzyy-Ping Jung

Authors
  1. Li-Wei Ko
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  2. I-Ling Tsai
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  3. Fu-Shu Yang
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  4. Jen-Feng Chung
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  5. Shao-Wei Lu
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  6. Tzyy-Ping Jung
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  7. Chin-Teng Lin
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Editor information

Editors and Affiliations

  1. Network Design and Research Center, Kyushu Institute of Technology,, 680-4, Kawazu, Iizuka,, 820-8502, Fukuoka, Japan

    Mario Köppen

  2. Knowledge Engineering and Discovery Research Institute (KEDRI), School of Computing and Mathematical Sciences, Auckland University of Technology, 350 Queen Street, 10110, Auckland, New Zealand

    Nikola Kasabov

  3. Department of Electrical and Computer Engineering, Robotics Laboratory, Auckland University of Technology, 38 Princes Street,, 1142, Auckland, New Zealand

    George Coghill

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© 2009 Springer-Verlag Berlin Heidelberg

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Ko, LW. et al. (2009). Real-Time Embedded EEG-Based Brain-Computer Interface. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03040-6_126

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  • DOI: https://doi.org/10.1007/978-3-642-03040-6_126

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03039-0

  • Online ISBN: 978-3-642-03040-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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