Skip to main content
SpringerLink
Log in

Suitable Number of Visual Stimuli for SSVEP-Based BCI Spelling Applications

  • Conference paper
  • First Online:
Advances in Computational Intelligence (IWANN 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10306))

Included in the following conference series:

Abstract

Steady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs) provide a pathway for re-establishing communication to people with severe disabilities. In the presented study, we compared accuracy and speed of three SSVEP-based BCI spelling applications in order to investigate the influence of the number of visual stimuli on the BCI performance. Three systems with four, six and 28 stimulating frequencies were tested. Ten subjects (one female) participated in this study. The highest ITR achieved in the experiment was 51.77 bpm. It is interesting, that it was achieved with the system based on six flickering targets. Our results confirm that the number of stimuli has high impact on classification accuracy and BCI literacy of SSVEP-based BCIs.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bin, G., Gao, X., Yan, Z., Hong, B., Gao, S.: An online multi-channel SSVEP-based brain-computer interface using a canonical correlation analysis method. J. Neural Eng. 6(4), 046002 (2009)

    Article  Google Scholar 

  2. Carvalho, S.N., Costa, T.B., Uribe, L.F., Soriano, D.C., Almeida, S.R., Min, L.L., Castellano, G., Attux, R.: Effect of the combination of different numbers of flickering frequencies in an SSVEP-BCI for healthy volunteers and stroke patients. In: 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 78–81. IEEE (2015)

    Google Scholar 

  3. Friman, O., Volosyak, I., Gräser, A.: Multiple channel detection of steady-state visual evoked potentials for brain-computer interfaces. IEEE Trans. Biomed. Eng. 54(4), 742–750 (2007)

    Article  Google Scholar 

  4. Gao, S., Wang, Y., Gao, X., Hong, B.: Visual and auditory brain-computer interfaces. IEEE Trans. Biomed. Eng. 61(5), 1436–1447 (2014)

    Article  Google Scholar 

  5. Gembler, F., Stawicki, P., Volosyak, I.: Towards a user-friendly BCI for elderly people. In: Proceedings of the 6th International Brain-Computer Interface Conference Graz (2014)

    Google Scholar 

  6. Gembler, F., Stawicki, P., Volosyak, I.: Autonomous parameter adjustment for SSVEP-based BCIs with a novel BCI wizard. Front. Neurosci. 9, 1–12 (2015)

    Article  Google Scholar 

  7. Guger, C., Allison, B.Z., Großwindhager, B., Prückl, R., Hintermüller, C., Kapeller, C., Bruckner, M., Krausz, G., Edlinger, G.: How many people could use an SSVEP BCI? Front. Neurosci. 6, 1–6 (2012)

    Google Scholar 

  8. Hwang, H.J., Lim, J.H., Jung, Y.J., Choi, H., Lee, S.W., Im, C.H.: Development of an SSVEP-based BCI spelling system adopting a QWERTY-style LED keyboard. J. Neurosci. Methods 208(1), 59–65 (2012)

    Article  Google Scholar 

  9. Liu, Y.H., Wang, S.H., Hu, M.R.: A self-paced p300 healthcare brain-computer interface system with SSVEP-based switching control and kernel FDA+ SVM-based detector. Appl. Sci. 6(5), 142 (2016)

    Article  Google Scholar 

  10. Nicolas-Alonso, L.F., Gomez-Gil, J.: Brain computer interfaces, a review. Sensors 12(2), 1211–1279 (2012)

    Article  Google Scholar 

  11. Norcia, A.M., Appelbaum, L.G., Ales, J.M., Cottereau, B.R., Rossion, B.: The steady-state visual evoked potential in vision research: a review. J. Vis. 15(6), 4 (2015)

    Article  Google Scholar 

  12. Nunez, F., Gembler, F., Stawicki, P.: Information transfer rate differences in SSVEP BCI: alphabetical and keyboard layouts in a GUI. In: Volosyak, I. (ed.) EEG-Based Brain-Computer Interfaces for Healthcare Applications, pp. 101–110. Shaker Verlag (2016)

    Google Scholar 

  13. Stawicki, P., Gembler, F., Volosyak, I.: Evaluation of suitable frequency differences in SSVEP-based BCIs. In: Blankertz, B., Jacucci, G., Gamberini, L., Spagnolli, A., Freeman, J. (eds.) Symbiotic 2015. LNCS, vol. 9359, pp. 159–165. Springer, Cham (2015). doi:10.1007/978-3-319-24917-9_17

    Chapter  Google Scholar 

  14. Stawicki, P., Gembler, F., Volosyak, I.: Driving a semi-autonomous mobile robotic car controlled by a SSVEP-based BCI. Comput. Intell. Neurosci. 2016, 5 (2016). Hindawi

    Article  Google Scholar 

  15. Treder, M.S., Schmidt, N.M., Blankertz, B.: Gaze-independent brain-computer interfaces based on covert attention and feature attention. J. Neural Eng. 8(6), 066003 (2011)

    Article  Google Scholar 

  16. Vilic, A., Kjaer, T.W., Thomsen, C.E., Puthusserypady, S., Sorensen, H.B.D.: DTU BCI speller: an SSVEP-based spelling system with dictionary support. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 2212–2215. IEEE (2013)

    Google Scholar 

  17. Volosyak, I.: SSVEP-based Bremen-BCI interface - boosting information transfer rates. J. Neural Eng. 8(3), 036020 (2011)

    Article  Google Scholar 

  18. Volosyak, I., Cecotti, H., Gräser, A.: Steady-state visual evoked potential response - impact of the time segment length. In: Proceedings of the 7th International Conference on Biomedical Engineering BioMed2010, Innsbruck, Austria, 17–19 February, pp. 288–292 (2010)

    Google Scholar 

  19. Volosyak, I., Gembler, F., Stawicki, P.: Age-related differences in SSVEP-based BCI performance. Neurocomputing (2017, in press)

    Google Scholar 

  20. Volosyak, I., Moor, A., Gräser, A.: A dictionary-driven SSVEP speller with a modified graphical user interface. In: Cabestany, J., Rojas, I., Joya, G. (eds.) IWANN 2011. LNCS, vol. 6691, pp. 353–361. Springer, Heidelberg (2011). doi:10.1007/978-3-642-21501-8_44

    Chapter  Google Scholar 

  21. Wang, Y., Wang, Y.T., Jung, T.P.: Visual stimulus design for high-rate SSVEP BCI. Electron. Lett. 46(15), 1057–1058 (2010)

    Article  Google Scholar 

  22. Wei, Q., Feng, S., Lu, Z.: Stimulus specificity of brain-computer interfaces based on code modulation visual evoked potentials. PloS One 11(5), e0156416 (2016)

    Article  Google Scholar 

  23. Wolpaw, J., Birbaumer, N., McFarland, D., Pfurtscheller, G., Vaughan, T.: Brain-computer interfaces for communication and control. Clin. Neurophysiol. 113, 767–791 (2002)

    Article  Google Scholar 

  24. Xing, S., McCardle, R., Xie, S.: Reading the mind: the potential of electroencephalography in brain computer interfaces. In: 2012 19th International Conference Mechatronics and Machine Vision in Practice (M2VIP), pp. 275–280. IEEE (2012)

    Google Scholar 

Download references

Acknowledgment

This research was supported by the European Fund for Regional Development under Grant GE-1-1-047. We also thank the participants of this study.

Author information

Authors and Affiliations

  1. Faculty of Technology and Bionics, Rhine-Waal University of Applied Sciences, 47533, Kleve, Germany

    Felix Gembler, Piotr Stawicki & Ivan Volosyak

Authors
  1. Felix Gembler
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Piotr Stawicki
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ivan Volosyak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ivan Volosyak .

Editor information

Editors and Affiliations

  1. Universidad de Granada, Granada, Spain

    Ignacio Rojas

  2. University of Malaga, Malaga, Spain

    Gonzalo Joya

  3. Polytechnic University of Catalonia, Vilanova i la Geltrú, Barcelona, Spain

    Andreu Catala

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Gembler, F., Stawicki, P., Volosyak, I. (2017). Suitable Number of Visual Stimuli for SSVEP-Based BCI Spelling Applications. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2017. Lecture Notes in Computer Science(), vol 10306. Springer, Cham. https://doi.org/10.1007/978-3-319-59147-6_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-59147-6_38

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59146-9

  • Online ISBN: 978-3-319-59147-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation