A new hybrid BCI paradigm based on P300 and SSVEP

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Wang, M., Daly, I., Allison, B. Z., Jin, J., Zhang, Y., Chen, L. and Wang, X. (2015) A new hybrid BCI paradigm based on P300 and SSVEP. Journal of Neuroscience Methods, 244. pp. 16-25. ISSN 01650270

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To link to this item DOI: 10.1016/j.jneumeth.2014.06.003

Abstract/Summary

Background: P300 and steady-state visual evoked potential(SSVEP) approaches have been widely used for brain–computer interface (BCI) systems. However, neither of these approaches can work for all subjects. Some groups have reported that a hybrid BCI that combines two or more approaches might provide BCI functionality to more users. Hybrid P300/SSVEP BCIs have only recently been developed and validated, and very few avenues to improve performance have been explored. New method: The present study compares an established hybrid P300/SSVEP BCIs paradigm to a new paradigm in which shape changing, instead of color changing, is adopted for P300 evocation to decrease the degradation on SSVEP strength. Result: The result shows that the new hybrid paradigm presented in this paper yields much better performance than the normal hybrid paradigm. Comparison with existing method: A performance increase of nearly 20% in SSVEP classification is achieved using the new hybrid paradigm in comparison with the normal hybrid paradigm.Allthe paradigms except the normal hybrid paradigm used in this paper obtain 100% accuracy in P300 classification. Conclusions: The new hybrid P300/SSVEP BCIs paradigm in which shape changing, instead of color changing, could obtain as high classification accuracy of SSVEP as the traditional SSVEP paradigm and could obtain as high classification accuracy of P300 as the traditional P300 paradigm. P300 did not interfere with the SSVEP response using the new hybrid paradigm presented in this paper, which was superior to the normal hybrid P300/SSVEP paradigm.

Item Type:	Article
Refereed:	Yes
Divisions:	Life Sciences > School of Biological Sciences > Department of Bio-Engineering
ID Code:	39892
Uncontrolled Keywords:	Brain–computer interface (BCI) Hybrid paradigm P300 SSVEP
Publisher:	Elsevier

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References

Allison BZ, McFarland DJ, Schalk G, Zheng SD, Moore Jackson M, Wolpaw JR. Towards an independent SSVEP brain computer interface using steady state visual evoked potentials. Clin Neurophysiol 2008;119(2):399–408. Allison BZ, Brunner C, Kaiser V, Müller-Putz GR, Neuper C, Pfurtscheller G. Toward a hybrid brain–computer interface based on imagined movement and visual attention. J Neural Eng 2010a;7(2):026007–26016. Allison BZ, Luth T, Valbuena D, Teymourian A, Volosyak I, Graser A. BCI demographics: how many (and what kinds of) people can use an SSVEP BCI? IEEE Trans Neural Syst Rehabil Eng 2010b;18(2):107–16. Allison BZ, Wolpaw EW, Wolpaw JR. Brain–computer interface systems: progress and prospects. Expert Rev Med Devices 2007;4(4):463–74. Allison BZ, Brunner C, Altstätter C, Wagner IC, Grissmann S, Neuper C. A hybrid ERD/SSVEP BCI for continuous simultaneous two dimensional cursor control. J Neurosci Methods 2012;209(2):299–307. Allison BZ, Jin J, Zhang Y, Wang XY. Brain–computer interfaces (2014): a four-choice hybrid P300/SSVEP BCI for improved accuracy. Brain–Computer Interfaces 2014;1(1):17–26. Bakardjian H, Tanaka T, Cichocki A. An optimization of SSVEP brain responses with application to eight-command brain–computer interface. Neurosci Lett 2010;469(1):34–8. 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 2009;6(4):046002. Brunner C,Allison BZ,Altstaetter C, Neuper C.Acomparison ofthree brain–computer interfaces based on event-related desynchronization, steady state visual evoked potentials, or a hybrid approach using both signals. J Neural Eng 2011;8(2):025010. Brunner C, Allison Bz, Krusienski DJ, Kaiser V, Müller-Putz GR, Pfurtscheller H, et al. Improved signal processing approaches in an offline simulation of hybrid brain–computer interface. J Neurosci Methods 2010;188(1):165–73. Cheng M, Gao X, Gao S, Xu D. Design and implementation of a brain–computer interface with high transfer rates. IEEE Trans Biomed Eng 2002;49(10):1181–6. Daly I, Billinger M, Laparra-Hernández J, Aloise F, García ML, Faller J, et al. On the control of brain–computer interface by users with cerebral palsy. Clin Neurophysiol 2013;124(9):1787–97. Edlinger G, Holzner C, Guger C. A hybrid brain–computer interface for smart home control. Lect Notes Comput Sci 2011;6762:417–26. Farwell LA, Donchin E. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potential. Electroencephalogr Clin Neurophysiol 1988;70(6):510–23. Fazel-Rezai R, Allison BZ, Guger C, Sellers EW, Kleih SC, Kübler A. P300 brain computer interface: current challenges and emerging trends. Front Neuroeng 2012;5:14. Guger C, Daban S, Sellers E, Holzner C, Lrausz G, Carabalona R, et al. How many people are able to control a P300-based brain–computer interface (BCI)? Neurosci Lett 2009;462(1):94–8. Guo F, Hong B, Gao X, Gao S. A brain–computer interface using motion-onset visual evoked potential. J Neural Eng 2008;5(4):477–85. Hammer EM, Halder S, Blankertz B, Sannelli C, Dickhaus T, Kleih S, et al. Psycholigical predictors of SMR-BCI performance. Biol Psychol 2012;89(1):80–6. Hoffmann U, Vesin JM, Ebrahimi T, Diserens K. An efficient P300-based brain–computer interface for disabled subjects. J Neurosci Methods 2008;167(1):115–25. Hong B, Guo F, Liu T, Gao X, Gao S. N200-speller using motion-onset visual response. Clin Neurophysiol 2009;120(9):1658–66. Jin J, Allison BZ, Sellers EW, Brunner C, Horki P, Wang XY, et al. An adaptive P300- based control system. J Neural Eng 2011a;8(3):036006. Jin J, Allison BZ, Sellers EW, Brunner C, Horki P, Wang XY, et al. Optimized stimulus presentation patterns for an event-related potential EEG-based brain–computer interface. Med Biol Eng Comput 2011b;49(2):181–91. Jin J, Allison BZ, Wang XY, Neuper C. A combined brain–computer interface based on P300 potentials and motion-onset visual evoked potentials. J Neurosci Methods 2012a;205(2):265–76. Jin J, Allison BZ, Kaufmann T, Kübler A, Zhang Y, Wang XY, et al. The changing face of P300 BCIs: a comparison of stimulus changes in a P300 BCI involving faces, emotion, and movement. PLOS ONE 2012b;7(11):0049688, http://dx.doi.org/10.1371/journal.pone, e49688. Lalor EC, Kelly SP, Finucane C, Burke R, Smith R, Reilly RB, et al. Steady-state VEP-based brain–computer interface control in an immersive 3D gaming environment. Eurasp J Appl Signal Process 2005;1:3156–64. Li YQ, Long JY, Yu TY, Yu ZL, Wang CC, Zhang HL, et al. An EEG-based BCI system for 2-D cursor control by combining Mu/beta rhythm and P300 potential. IEEE Trans Biomed Eng 2010;57(10):2495–505. Li YQ, Pan J, Wang F, Yu Z. A hybrid BCI system combining P300 and SSVEP and its application to wheelchair control. IEEE Trans Biomed Eng 2013;60(11):3156–66. Lin ZL, Zhang CS, Wu W, Gao XR. Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs. IEEE Trans Biomed Eng 2006;53(12):2610–4. LuJ,McFarland DJ,Wolpaw JR.Adaptive Laplacianfiltering for sensorimotor rhythmbased brain–computer interfaces. J Neural Eng 2013;10(1):016002. Martinez P, Bakardjian H, Cichocki A. Fully online multicommand brain–computer interface with visual neurofeedback using SSVEP paradigm. Comput Intell Neurosci 2007:13. Müller-Putz GR, Scherer R, Brauneis C, Pfurtscheller G. Steady-state visual evoked potential (SSVEP)-based communication: impact of harmonic frequency components. J Neural Eng 2005;2(4):123–30. Müller-Putz GR, Breitwieser C, Cincotti F, Leeb R, Schreuder M, Leotta F, et al. Tools for brain–computer interaction: a general concept for a hybrid BCI. Front Neuroinform 2011;5(30):1–10. Müller-Putz GR, Pfurtscheller G. Control of an electrical prosthesis with an SSVEPbased BCI. IEEE Trans Neural Syst Rehabil Eng 2008;55(1):361–4. Ortner R, Allison BZ, Korisek G, Gaggl H, Pfurtscheller G. An SSVEP BCI to control a hand orthosis for persons with tetraplegia. IEEE Trans Neural Syst Rehabil Eng 2011;19(1):1–5. Panicker RC, Puthusserypady S, Sun Y. An asynchronous P300 BCI with SSVEP-based control state detection. IEEE Trans Biomed Eng 2011;58(6):1781–8. Pfurtscheller G, Neuper C. Motor imagery and direct brain–computer communication. Proc IEEE 2001;89(7):1123–34. Pfurtscheller G, Allison BZ, Brunner C, Bauernfeind G, Solis-Escalante T, Scherer R, et al. The hybrid BCI. Front Neurosci 2010;4(42):1–11. Pritach WS. Psychophysiology of P300. Psychol Bull 1981;89(3):506–40. Regan D. Human brain electrophysiology. NY, USA: Elsevier; 1989. Sellers EW, Donchin E. A P300-based brain–computer interface: initial tests by ALS patients. Clin Neurophysiol 2006;117(3):538–48. Trejo LJ, Rosipal R, Matthews B. Brain–computer interfaces for 1-D and 2-D cursor control: designs using volitional control of the EEG spectrum or steady-state visual evoked potentials. IEEE Trans Neural Syst Rehabil Eng 2006;14(2): 225–9. Vidal JJ. Toward direct brain–computer communication. Annu Rev Biophys Bioeng 1973;2:157–80. Vidaurre C, Blankertz B. Towards a cure for BCI illiteracy. Brain Topogr 2010;23(2):194–8. Wang Y, Wang R, Gao X, Hong B, Gao S. A practical VEP-based brain–computer interface. IEEE Trans Neural Syst Rehabil Eng 2006;14(2):234–9. Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan T. Brain–computer interfaces for communication and control. Clin Neurophysiol 2002;113(6):767–91. Xu MP, Qi HZ,Wan BK, Yin T, Liu ZP, Ming D.Ahybrid BCI speller paradigm combining P300 potential and the SSVEP blocking feature. J Neural Eng 2013;10(2):026001. Yin E, Zhou ZT, Jiang J, Chen FL, Liu YD, Hu DW. A novel hybrid BCI speller based on the incorporation of SSVEP into the P300 paradigm. J Neural Eng 2013;10(2): 026012. Zhang Y, Zhao Q, Jin J,Wang X, Cichocki A. A novel BCI based on ERP components sensitive to configural processing of human faces. J Neural Eng 2012;9(2):026018.

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A new hybrid BCI paradigm based on P300 and SSVEP

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