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Single-trial EEG classification using in-phase average for brain-computer interface

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Frontiers of Electrical and Electronic Engineering in China

Abstract

Communication signals should be estimated by a single trial in a brain-computer interface. Since the relativity of visual evoked potentials from different sites should be stronger than those of the spontaneous electroencephalogram (EEG), this paper adopted the time-lock averaged signals from multi-channels as features. 200 trials of EEG recordings evoked by target or non-target stimuli were classified by the support vector machine (SVM). Results show that a classification accuracy of higher than 97% can be obtained by merely using the 250–550 ms time section of the averaged signals with channel Cz and Pz as features. It suggests that a possible approach to boost communication speed and simplify the designation of the brain-computer interface (BCI) system is worthy of an attempt in this way.

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References

  1. Vaughan T M, Heetderks W J, Trejo L J, et al. Guest editorial brain-computer interface technology: a review of the second international meeting. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2003, 11(2): 94–109

    Article  Google Scholar 

  2. Farwell L A, Donchin E. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalography and Clinical Neurophysiology, 1988, 70(6): 510–523

    Article  Google Scholar 

  3. Cheng M, Gao X, Gao S, et al. Design and implementation of a brain-computer interface with high transfer rates. IEEE Transactions on Biomedical Engineering, 2002, 49(10): 1181–1186

    Article  Google Scholar 

  4. Guan J A, Chen Y G. Single-trial estimation of visual-evoked potentials using SVM with multi-channel feature montages. Journal of Huazhong University of Science and Technology (Nature Science Edition), 2006, 34(8): 19–22 (in Chinese)

    Google Scholar 

  5. Blankertz B, Muller K R, Curio G, et al. The BCI competition 2003: progress and perspectives in detection and discrimination of EEG single trials. IEEE Transactions on Biomedical Engineering, 2004, 51(6): 1044–1051

    Article  Google Scholar 

  6. Chang C C, Lin C J. Training support vector classifiers: theory and algorithms. Neural Computation, 2001, 13(9): 2119–2147

    Article  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. School of Electronic Engineering, South-Central University for Nationalities, Wuhan, 430074, China

    Jin’an Guan & Yaguang Chen

Authors
  1. Jin’an Guan
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  2. Yaguang Chen
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Corresponding author

Correspondence to Jin’an Guan.

Additional information

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Translated from Journal of Huazhong University of Science and Technology (Nature Science Edition), 2007, 35(1): 11–13 [译自: 华中科技大学学报(自然科学版)]

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Guan, J., Chen, Y. Single-trial EEG classification using in-phase average for brain-computer interface. Front. Electr. Electron. Eng. Ch 3, 194–197 (2008). https://doi.org/10.1007/s11460-008-0034-2

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  • DOI: https://doi.org/10.1007/s11460-008-0034-2

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