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Steady-State VEP-Based Brain-Computer Interface Control in an Immersive 3D Gaming Environment


This paper presents the application of an effective EEG-based brain-computer interface design for binary control in a visually elaborate immersive 3D game. The BCI uses the steady-state visual evoked potential (SSVEP) generated in response to phase-reversing checkerboard patterns. Two power-spectrum estimation methods were employed for feature extraction in a series of offline classification tests. Both methods were also implemented during real-time game play. The performance of the BCI was found to be robust to distracting visual stimulation in the game and relatively consistent across six subjects, with 41 of 48 games successfully completed. For the best performing feature extraction method, the average real-time control accuracy across subjects was 89%. The feasibility of obtaining reliable control in such a visually rich environment using SSVEPs is thus demonstrated and the impact of this result is discussed.

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Correspondence to E. C. Lalor.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Lalor, E.C., Kelly, S.P., Finucane, C. et al. Steady-State VEP-Based Brain-Computer Interface Control in an Immersive 3D Gaming Environment. EURASIP J. Adv. Signal Process. 2005, 706906 (2005).

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Keywords and phrases

  • EEG
  • BCI
  • online classification
  • overt attention