Skip to main content

Advertisement

Log in

A multi-command SSVEP-based BCI system based on single flickering frequency half-field steady-state visual stimulation

  • Original Article
  • Published:
Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

Steady-state visual evoked potentials (SSVEPs) are widely employed in brain–computer interface (BCI) applications, especially to control machines. However, the use of SSVEPs leads to eye fatigue and causes lower accuracy over the long term, particularly when multi-commands are required. Therefore, this paper proposes a half-field steady-state visual stimulation pattern and paradigm to increase the limited number of commands that can be achieved with existing SSVEP-based BCI methods. Following the theory of vision perception and existing half-field SSVEP-based BCI systems, the new stimulation pattern generates four commands using only one frequency flickering stimulus and has an average classification accuracy of approximately 75 %. According to the proposed stimulus pattern, using only one frequency without requiring users to stare directly at the flickering stimulus allows users to easily focus on the system and experience less visual fatigue compared to existing systems. Furthermore, new half-field SSVEP-based BCI systems are proposed, incorporating our proposed feature extraction and decision-making algorithm. Extracting the signal from the occipital area and using a reference electrode position at the parietal area yielded better results compared to the central area. In addition, we recommend using an LED or LCD as the visual stimulus device (at the recommended size), which yielded comparable results to our proposed feature extraction and decision-making algorithm. Finally, an application of the proposed system is demonstrated for real-time television control.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Malmivuo J, Plonsey R (1995) Electroencephalography in bioelectromagnetism; principles and applications of bioelectric and biomagnetic fields. Oxford University Press, New York

    Book  Google Scholar 

  2. Wolpaw JR et al (2002) Brain-computer interfaces for communication and control. J Clin Neurophysiol 113(6):767–791

    Article  Google Scholar 

  3. Wolpaw JR et al (2000) Brain–computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng 8:164–173

    Article  CAS  PubMed  Google Scholar 

  4. Muller-Putz GR, Pfurtscheller G (2008) Control of an electrical prosthesis with an SSVEP-based BCI. IEEE Trans Biomed Eng 55(1):361–364

    Article  PubMed  Google Scholar 

  5. Pfurtscheller G et al (2010) Self-paced operation of an SSVEP-based orthosis with and without an Imagery-based “brain switch”; a feasibility study towards a hybrid BCI. IEEE Trans Neural Syst Rehabil Eng 18:409–414

    Article  PubMed  Google Scholar 

  6. Parag GP, Dennis AT (2008) The development of brain-machine interface neuroprosthetic devices. J Neurotherapeutics 5(1):137–146

    Article  Google Scholar 

  7. Leow RS, Ibrahim F, Moghavvemi M (2007) Development of a steady state visual evoked potential (SSVEP)-based brain computer interface (BCI) system. International conference on intelligent and advanced systems, ICIAS (2007)

  8. Corralejo R et al (2014) P300-based brain–computer interface aimed at operating electronic devices at home for severely disabled people. Med Biol Eng Comput 52(10):861–872

    Article  PubMed  Google Scholar 

  9. Iturrate I et al (2009) A noninvasive brain-actuated wheelchair based on a P300 neurophysiological protocol and automated navigation. IEEE Trans Rob 25(3):614–627

    Article  Google Scholar 

  10. Hui S et al (2009) Research on SSVEP-based controlling system of multi-DOF manipulator. In: International conference proceedings in neural networks: advances in neural networks—part III. Springer, Wuhan, China

  11. Cecotti H, Volosyak I, Graser A (2009) Evaluation of an SSVEP based brain–computer interface on the command and application levels. In: Annual international conference in neural engineering, NER(2009)

  12. Maggi L et al (2006) A four command BCI system based on the SSVEP protocol. In: Annual international conference of engineering in medicine and biology society, EMBS (2006)

  13. Materka A, Byczuk M (2006) Alternate half-field stimulation technique for SSVEP-based brain-computer interfaces. Electron Lett 42(6):321–322

    Article  Google Scholar 

  14. Zheng Y et al (2009) A half-field stimulation pattern for SSVEP-based brain-computer interface. In: Annual international conference of engineering in medicine and biology society, EMBC (2009)

  15. Delorme A, Makeig S (2004) EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics. J Neurosci Methods 134:9–21

    Article  PubMed  Google Scholar 

  16. Do-Won K et al (2011) A vision-free brain-computer interface (BCI) paradigm based on auditory selective attention. In: Annual international conference of engineering in medicine and biology society, EMBC (2011)

  17. Pires G, Castelo-Branco M, Nunes U (2008) Visual P300-based BCI to steer a wheelchair: a Bayesian approach. In: Annual international conference of engineering in medicine and biology society, EMBS (2008)

  18. Horki P, Solis-Escalante T, Neuper C, Müller-Putz G (2011) Combined motor imagery and SSVEP based BCI control of a 2 DoF artificial upper limb. Med Biol Eng Comput 49(5):567–577

    Article  PubMed  Google Scholar 

  19. Krusienski DJ, Allison BZ (2008) Harmonic coupling of steady-state visual evoked potentials. In: Annual international conference of engineering in medicine and biology society, EMBS (2008)

  20. Ruiping W, Xiaorong G, Shangkai G (2005) Frequency selection for SSVEP-based binocular rivalry. In: International conference proceedings in neural engineering, EMBS (2005)

  21. Yijun W et al (2004) Lead selection for SSVEP-based brain-computer interface. In: Annual international conference of engineering in medicine and biology society, EMBS (2004)

  22. Müller-Putz GR et al (2005) Steady-state visual evoked potential (SSVEP) based communication: impact of harmonic frequency components. J Neural Eng 2:123

    Article  PubMed  Google Scholar 

  23. Bin G et al (2009) An online multi-channel SSVEP-based brain–computer interface using a canonical correlation analysis method. J Neural Eng 6:046002

    Article  PubMed  Google Scholar 

  24. Luo A, Sullivan TJ (2010) A user-friendly SSVEP-based brain–computer interface using a time-domain classifier. J Neural Eng 7:026010

    Article  Google Scholar 

  25. Ng Kian B et al (2012) Stimulus specificity of a steady-state visual-evoked potential-based brain–computer interface. J Neural Eng 9(1):036008

    Article  PubMed  Google Scholar 

  26. Punsawad Y, Wongsawat Y (2011) Multi-command SSVEP-based BCI system via single flickering frequency half-field stimulation pattern. In: Annual international conference of engineering in medicine and biology society, EMBC (2011)

Download references

Acknowledgments

This project is supported in part by the government funding of Mahidol University.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yodchanan Wongsawat.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Punsawad, Y., Wongsawat, Y. A multi-command SSVEP-based BCI system based on single flickering frequency half-field steady-state visual stimulation. Med Biol Eng Comput 55, 965–977 (2017). https://doi.org/10.1007/s11517-016-1560-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-016-1560-3

Keywords

Navigation