A Visual Stimulus Module for P300 Based Brain Computer Interfaces

Abstract

Brain Computer Interfaces (BCIs) are the systems that provide a direct communication channel between human brain and environment. P300 potentials are involuntary brain responses which are used to control BCI systems. In order to elicit P300 responses, stimulus presentation must be provided to the users. However, there are not common paradigms or optimal parameters for all BCI users, or all BCI applications. Using the most convenient method and parameters for each user individually will improve system performance. This study proposes a visual stimulus module for P300 based BCIs. The module offers to design stimulus interfaces based on three different stimulus interfaces, including row/column, single character and region based paradigms. The module also provides customization of the stimulus interface by setting optimal parameters for individuals practically. Furthermore, in this study, we also explained synchronization between stimulus interface and data acquisition module in detailed. In order to test the stimulus module, stimulus interfaces based on three visual stimulus paradigms were designed. All the paradigms were tested by three subjects. P300 responses yielded with three paradigms were compared by using one-way statistical analysis of variance (ANOVA) method. Preliminary results revealed that average amplitude and latency of P300 potentials that were elicited by the different paradigms may differ.

Keywords

• Brain Computer Interface (BCI),P300 Potentials,Region Based Paradigm,Row/Column Paradigm,Single Character Paradigm,Visual Stimulus Module

References

1. Wolpaw J.R., et al., Brain–computer interfaces for communication and control, Clinical Neurophysiology, Vol. 113, 2002, pp. 767–791.
2. Guger C., BCI and Virtual Reality, Workshop Materials on 8th BCI Workshop, May, 2011, Netherlands, Utrecht.
3. Mak J.N., Wolpaw J.R., Clinical Applications of brain–computer interfaces: current state and future prospects, IEEE Reviews in Biomedical Engineering, Vol. 2, 2009, pp. 187-199.
4. Farwell L.A., Donchin E., Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials, Electroencephalography and Clinical Neurophysiology, Vol.70, 1988, pp. 510-523.
5. Furdea A., Halder S., Krusienski D.J., Bross D., Nijboer F.,Birbaumer N.,Kubler A., An auditory oddball (P300) spelling system for brain-computer interfaces, Psychophysiology, Vol. 46, 2009, pp. 617–625.
6. Brouwer A.M., Erp J.B.F., A tactile P300 brain-computer interface, Frontiers in Neuroscience, Vol. 4, 2010, pp.19:1-11.
7. Dinçer E.D., et.al., Tek uyarıcı paradigması ile elde edilen EEG bileşenlerinin yapısal MR görüntülerindeki kaynak lokalizasyonu, Proceedings on the 29. Ulusal Radyoloji Kongresi, 1-5 November, 2008, Turkey, Antalya.
8. Guan C., Thulasidas M., Wu J., High Performance P300 Speller for Brain-Computer Interface, Proceedings on the 2004 IEEE International Workshop on Biomedical Circuits & Systems, 1-3 December 2004, Singapore.

9. Rezai R.F., Abhari K., A region-based P300 speller for brain-computer interface, Canadian Journal of Electrical and Computer Engineering, Vol. 34, Iss. 3, 2009, pp. 81-85.
10. Aydın, E.A., Bay, Ö.F., Güler, İ., Implementation of an embedded web server application for wireless control of brain computer interface based home environments, Journal of Medical Systems, Vol. 40, Iss.1, 2016, pp. 27.
11. Guger C. et.al., How many people are able to control a P300-based brain–computer interface (BCI)?, Neuroscience Letters, Vol. 462, 2009, pp. 94–98.
12. Ikegami S., Takano K, Saeki N., Kansaku K., Operation of a P300-based brain–computer interface by individuals with cervical spinal cord injury, Clinical Neurophysiology, Vol. 122, 2011, pp. 991–996.
13. Takano K., Komatsu T., Hata N., Nakajima Y., Kansaku K., Visual stimuli for the P300 brain–computer interface: A comparison of white/gray and green/blue flicker matrices, Clinical Neurophysiology, Vol. 120, 2009, pp. 1562–1566.
14. Liu Y, Zhou Z., Hu D., Comparison of stimulus types in visual p300 speller of brain-computer interfaces, Proceedings on the IEEE International Conference on Cognitive Informatics (ICCI’10), 07-09 July 2010, Beijing, China.
15. Salvaris M., Sepulveda F., Visual modifications on the P300 speller BCI paradigm, Journal of Neural Engineering, Vol. 6, 2009, pp. 046011 (8pages).
16. Krusienski D.J., A comparison of classification techniques for the P300 speller, Journal of Neural Engineering, Vol. 3, 2006, pp. 299-305.
17. Meinicke P., Kaper M., Hoppe F., Heumann M., Ritter H., Improving transfer rates in brain computer interfacing: a case study, Proceedings on the Neural Information Processing Systems (NIPS), 2002.
18. Sellers E.W., et.al. A P300 event-related potential brain–computer interface (BCI): The effects of matrix size and inter stimulus interval on performance, Biological Psychology, Vol. 73, 2006, pp.242–252.
19. Hirayasu Y., Samura M., Ohta H., Ogura C., Sex effects on rate of change of P300 latency with age, Clinical Neurophysiology, Vol. 111, 2000, pp. 187-194.
20. Juckel G., Age effects on the P300 potential and the corresponding fMRI BOLD-signal, NeuroImage, Vol. 60, 2012, pp. 2027–2034.
21. Brunner C., Andreoni G., Bianchi L., Blankertz B., Breitweiser C., Kanoh S., Kothe C., Lecuyer A., Makeig S., Mellinger J., Perego P., Renard Y., Schalk G., Susila I.P., Ven‐thur B., Müller-putz G., BCI Software Platforms. In: Towards Practical BCIs: Bridging the Gap from Research to Real-World Applications, Allison, B.Z., Dunne, S., Leeb, R., Millan, J., and Nijholt, A. Springer-Verlag Berlin, 303-331, 2013.
22. Edlinger G., Krausz G., Groenegress C., Holzner C., Guger C., Slater M., Brain-Computer Interfaces for Virtual Environment Control, Proceedings on the 13th International Conference on Biomedical Engineering (ICBME) 2008, Proceedings 23, 3-6 December 2008,Singapore.
23. Gavett S., Wygant Z., Amiri S., Rezai R.F., Reducing Human Error in P300 Speller Paradigm for Brain-Computer Interface, Proceedings on the 34th Annual International Conference of the IEEE EMBS, 28 August - 1 September, 2012, California USA.
24. Fazel-Rezai R., Recent Advances in Brain-Computer Interface Systems, Hırvatistan: InTech, 2011.