Skip to main content

A Subarea-Location Joint Spelling Paradigm for the BCI Control

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8261))

Abstract

Brain computer interface (BCI) speller is an important issue in BCI research. In this paper, we propose a novel spelling paradigm for enhancing the performance of BCI speller. In our approach, the target character is detected by the combination of the P300 potential and the steady-state visual evoked potential (SSVEP). Specifically, the P300 detection mechanism and the SSVEP detection mechanism are employed as two sub-spellers for identifying the number of the subarea and location of target character, respectively and simultaneously. The experimental results show that the information transfer rate (ITR) of our BCI system was significantly improved compared to the traditional BCI approaches, i.e. P300 speller and SSVEP speller.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-Computer Interfaces for Communication and Control. Clin. Neurophysiol. 113, 767–791 (2002)

    Article  Google Scholar 

  2. Mak, J.N., Arbel, Y., Minett, J.W., McCane, L.M., Yuksel, B., Ryan, D., Thompson, D., Bianchi, L., Erdogmus, D.: Optimizing the P300-Based Brain-Computer Interface: Current Status, Limitations and Future Directions. J. Neural Eng. 8, 025003 (2011)

    Article  Google Scholar 

  3. Cecotti, H.: Spelling with Non-invasive Brain Computer Interfaces-Current and Future Trends. Journal of Physiology-Paris 105, 106–114 (2011)

    Article  Google Scholar 

  4. Farwell, L.A., Donchin, E.: Talking off the Top of Your Head: Toward a Mental Prosthesis Utilizing Event-Related Brain Potentials Electroencephalogr. Clin. Neurophysiol. 70, 510–523 (1988)

    Article  Google Scholar 

  5. Vialatte, F.B., Maurice, M., Dauwels, J., Cichocki, A.: Steady-State Visually Evoked Potentials: Focus on Essential Paradigms and Future Perspectives. Prog. Neurobiol. 90, 418–438 (2010)

    Article  Google Scholar 

  6. Jin, J., Allison, B.Z., Sellers, E.W., Brunner, C., Horki, P., Wang, X., Neuper, C.: An Adaptive P300-Based Control System. J. Neural Eng. 8, 036006 (2011)

    Article  Google Scholar 

  7. Allison, B.Z., Pineda, J.A.: Effects of SOA and Flash Pattern Manipulations on ERPs, Performance, and Preference: Implications for a BCI System. Int. J. Psychophysiol. 59, 127–140 (2006)

    Article  Google Scholar 

  8. Townsend, G., LaPallo, B.K., Boulay, C.B., Krusienski, D.J., Frye, G.E., Hauser, C.K., Schwartz, N.E., Vaughan, T.M., Wolpaw, J.R., Sellers, E.W.: A Novel P300-Based Brain-Computer Interface Stimulus Presentation Paradigm: Moving Beyond Rows and Columns. Clin. Neurophysiol. 121, 1109–1120 (2010)

    Article  Google Scholar 

  9. Gonsalvez, C.L., Polich, J.: P300 Amplitude is Determined by Target-to-Target Interval. Psychophysiology 39, 388–396 (2002)

    Article  Google Scholar 

  10. Gao, X., Xu, D., Cheng, M., Gao, S.: A BCI-Based Environmental Controller for the Motion-Disabled. IEEE Trans. Neural Syst. Rehabil. Eng. 11, 137–140 (2003)

    Article  Google Scholar 

  11. 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, 46002 (2009)

    Article  Google Scholar 

  12. Hwang, H., Lim, J., Jung, Y., Choi, H., Lee, S., Im, C.: Development of an SSVEP-Based BCI Spelling System Adopting a QWERTY-Style LED Keyboard. J. Neurosci. Methods 208, 59–65 (2012)

    Article  Google Scholar 

  13. Allison, B.Z., Brunner, C., Kaiser, V., Muller-Putz, G.R., Neuper, C., Pfurtscheller, G.: Toward a Hybrid Brain-Computer Interface Based on Imagined Movement and Visual Attention. J. Neural Eng. 7, 026007 (2010)

    Article  Google Scholar 

  14. Brunner, C., Allison, B.Z., Altstatter, C., Neuper, C.: A Comparsion of Three Brain-Computer Interfaces Based on Event-Related Desynchronization, Steady State Visual Evoked Potentials, or a Hybrid Approach Using both Signals. J. Neural Eng. 8, 025010 (2011)

    Article  Google Scholar 

  15. Long, J.Y., Li, Y.Q., Yu, T.Y., Gu, Z.H.: Target Selection with Hybrid Feature for BCI-Based 2-D Cursor Control. IEEE Trans. Biomed. Eng. 59, 132–140 (2012)

    Article  Google Scholar 

  16. Yin, E., Zhou, Z., Jiang, J., Chen, F., Liu, Y., Hu, D.: A Novel Hybrid BCI Speller Based on the Incorporation of SSVEP into the P300 Paradigm. J. Neural Eng. 10, 026012 (2013)

    Article  Google Scholar 

  17. Schalk, G., McFarland, D.J., Hinterberger, T., Birbaumer, N., Wolpaw, J.R.: BCI2000: A General-Purpose Brain-Computer Interface (BCI) System. IEEE Trans. Biomed. Eng. 51, 1034–1043 (2004)

    Article  Google Scholar 

  18. Krusienski, D.J., Sellers, E.W., Cabestaing, F., Bayoudh, S., McFarland, D.J., Vaughan, T.M., Wolpaw, J.R.: A Comparison of Classification Techniques for the P300 Speller. J. Neural Eng. 3, 299–305 (2006)

    Article  Google Scholar 

  19. Lin, Z., Zhang, C., Wu, W., Gao, X.: Frequency Recognition Based on Canonical Correlation Analysis for SSVEP-Based BCIs. IEEE Trans. Biomed. Eng. 53, 2610–2614 (2006)

    Article  Google Scholar 

  20. Wolpaw, J.R., Birbaumer, N., Heetderrks, W.J., McFarland, D.J., Peckham, P.H., Schalk, G., Donchin, E., Quatrano, L.A., Robinson, C.J., Vaughan, T.M.: Brain-Computer Interface Technology: A Review of the First International Meeting. IEEE Trans. Rehabil. Eng. 8, 161–173 (2000)

    Google Scholar 

  21. Pires, G., Nunes, U., Castelo-Branco, M.: Comparison of A Row-Column Speller Vs. A Novel Lateral Single-Character Speller: Assessment of BCI for Severe Motor Disabled Patients. Clin. Neurophysiol. 123, 1168–1181 (2012)

    Article  Google Scholar 

  22. Lenhardt, A., Kaper, M., Ritter, H.J.: An Adaptive P300-Based Online Brain-Computer Interface. IEEE Trans. Neural Syst. Rehabil. Eng. 16, 121–130 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yin, E., Jiang, J., Yu, Y., Tang, J., Zhou, Z., Hu, D. (2013). A Subarea-Location Joint Spelling Paradigm for the BCI Control. In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_47

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-42057-3_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42056-6

  • Online ISBN: 978-3-642-42057-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics