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Reducing the Computation Time for BCI Using Improved ICA Algorithms

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Advances in Neural Networks – ISNN 2013 (ISNN 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7952))

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Abstract

P300 is a popular characteristic potential for electroencephalogram(EEG) based brain-computer interface(BCI). In P300-BCI, the extraction of P300 is a very crucial operation. Independent component analysis(ICA) technique is suitable for P300 extraction. In this paper, aiming at the current large volume of EEG data, the applications of three ICA algorithms were proposed for P300 extraction and were compared. The experiments ran on real EEG data respectively. PI and recognition accuracy were checked. The results show artificial fish swarm algorithm based ICA(AFSA_ICA) can extract P300 faster, reducing the computation time for BCI with PI remaining better.

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Author information

Authors and Affiliations

  1. Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110819, China

    Lu Huang

  2. Northeastern University, POB 319, 110004, Shenyang, China

    Hong Wang

  3. College of Information Engineering, Dalian Ocean University, Dalian, 116023, China

    Lu Huang

Authors
  1. Lu Huang
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  2. Hong Wang
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Editor information

Editors and Affiliations

  1. School of Information and Communication Engineering, Dalian University of Technology, A 530, Chuangxinyuan Building, 116023, Dalian, China

    Chengan Guo

  2. Institute of Automation, Chinese Academy of Sciences, 100864, Beijing, China

    Zeng-Guang Hou

  3. School of Automation, Huazhong University of Science and Technology, 430074, Wuhan, China

    Zhigang Zeng

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© 2013 Springer-Verlag Berlin Heidelberg

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Huang, L., Wang, H. (2013). Reducing the Computation Time for BCI Using Improved ICA Algorithms. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39068-5_37

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  • DOI: https://doi.org/10.1007/978-3-642-39068-5_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39067-8

  • Online ISBN: 978-3-642-39068-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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