Brain-Computer Interface: Usability Evaluation of Different P300 Speller Configurations: A Preliminary Study

  • Liliana GarciaEmail author
  • Véronique Lespinet-Najib
  • Sarah Saioud
  • Victor Meistermann
  • Samuel Renaud
  • Jaime Diaz-Pineda
  • Jean Marc André
  • Ricardo Ron-Angevin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9094)


Brain–Computer Interface (BCI) is particularly relevant as a new way to interact with the outside world for disabled people. Based on P300 event-related potentials (ERPs) BCIs have been frequently used for communication purposes, being the first P300-based BCI paradigm developed by Farwell and Donchin for visual speller. P300-BCI speller studies require a significant attentional demand during sustained long times which could represent fatigue and feeling of increasing workload. The evaluation of workload while using P300-BCI speller requires taking into account the cognitive, emotional and physical state of participant during task. This would help to improve usability of the system. The objective of the study is to evaluate, through objective and subjective measures, three different size of speller in order to analyze effectiveness, cognitive load and user comfort. Three healthy subjects took part in the experiment. The preliminary results suggest that speller size can have different effects on user performance and represent important workload for subjects.


Brain-Computer Interface (BCI) Usability Speller P300 Matrix Size 


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  1. 1.
    Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-computer interfaces for communication and control. Clinical Neurophysiology 113(6), 767–791 (2002)CrossRefGoogle Scholar
  2. 2.
    Birbaumer, N.: Breaking the silence: Brain-computer interfaces (BCI) for communication and motor control. Psychophysiology 43(6), 517–532 (2006)CrossRefGoogle Scholar
  3. 3.
    Mak, J., Wolpaw, J.: Clinical applications of brain-computer interfaces: Current state and future prospects. IEEE Reviews in Biomedical Engineering 2, 187–199 (2009)CrossRefGoogle Scholar
  4. 4.
    Farwell, L., Donchin, E.: Talking off the top of your head: toward a mental prosthesis utilizing event related brain potentials. Electroencephalography and Clinical Neurophysiology 70(6), 510–523 (1988)CrossRefGoogle Scholar
  5. 5.
    Bianchi, L., Sami, S., Hillebrand, A., Fawcett, I., Quitadamo, L., Seri, S.: Which physiological components are more suitable for visual ERP based brain-computer interface? A preliminary MEG/EEG study. Brain Topography 23(2), 180–185 (2010)CrossRefGoogle Scholar
  6. 6.
    Kleih, S., Nijboer, F., Halder, S., Kübler, A.: Motivation modulates the P300 amplitude during brain- computer interface use. Clinical Neurophysiology 121(7), 1023–1031 (2010)CrossRefGoogle Scholar
  7. 7.
    Krusienski, D., Sellers, E., McFarland, D., Vaughan, T., Wolpaw, J.: Toward enhanced P300 speller performance. Journal of Neuroscience Methods 167(1), 15–21 (2008)CrossRefGoogle Scholar
  8. 8.
    Sellers, E.W., Krusienski, D.J., McFarland, D.J., Vaughan, T.M., Wolpaw, J.R.: A P300 event-related potential brain–computer interface (BCI): The effects of matrix size and inter stimulus interval on performance. Biological Psychology 73(3), 242–252 (2006)CrossRefGoogle Scholar
  9. 9.
    Donchin, E., Spencer, K., Wijesinghe, R.: The mental prosthesis: Assessing the speed of a P300-based brain-computer interface. IEEE Transactions on Rehabilitation Engineering 8(2), 174–179 (2000)CrossRefGoogle Scholar
  10. 10.
    Wang, C., Guan, C., Zhang, H.: P300 brain-computer interface design for communication and control applications. In: 27th Annual International Conference of the Engineering in Medicine and Biology Society IEEE-EMBS 2005, pp. 5400–5403 (2005)Google Scholar
  11. 11.
    Sellers, E.W., Donchin, E.: A P300-based brain–computer interface: Initial tests by ALS patients. Clinical Neurophysiology 117(3), 538–548 (2006)CrossRefGoogle Scholar
  12. 12.
    ISO 9241-11. Ergonomic requirements for office work with visual display terminals (VDTs) – Part 11: Guidance on usability (1998)Google Scholar
  13. 13.
    Nielsen, J.: What is usability? In: Usability Engineering, pp. 23–48. Academic Press, Cambridge (1993)Google Scholar
  14. 14.
    Nielsen, J.: Heuristic evaluation. In: Nielsen, J., Mark, R.L. (eds.) Usability Inspection Methods. John Wiley & Sons, New York (1994)CrossRefGoogle Scholar
  15. 15.
    Frojkaer, E., Hertzum, M., Hornbaek, K.: Measuring usability: are effectiveness, efficiency, and satisfaction really correlated. In: CHI 2000, pp. 345-352. ACM Press, New York (2000)Google Scholar
  16. 16.
    Chanquoy, L., Tricot, A. Sweller J.: La charge cognitive. Edition Armand Colin (2007)Google Scholar
  17. 17.
    Jeng, J.: Usability assessment of academic digital libraries: Effectiveness, efficiency, satisfaction, and learnability. Libri 55(2–3), 96–121 (2005)Google Scholar
  18. 18.
    Hertzum, M.: Images of usability. International journal of Human-Computer Interaction. 26, 567–600 (2010)CrossRefGoogle Scholar
  19. 19.
    Kececi, H., Degirmenci, Y., Atakay, S.: Habituation and dishabituation of P300. Cognitive and Behavioral Neurology 19(3), 130–134 (2006)CrossRefGoogle Scholar
  20. 20.
    Murata, A., Uetake, A.: Evaluation of mental fatigue in human-computer interaction - analysis using feature parameters extracted from event-related potential. In: 10th IEEE International Workshop on Robot and Human Interactive Communication, pp. 630–635 (2001)Google Scholar
  21. 21.
    Mangun, G.R., Buck, L.A.: Sustained visual spatial attention produces costs and benefits in response time and evoked neural activity. Neuropsychologia 36(3), 189–200 (1998)CrossRefGoogle Scholar
  22. 22.
    Polich, J., Kok, A.: Cognitive and biological determinants of P300: An integrative review. Biological Psychology 41(2), 103–146 (1995)CrossRefGoogle Scholar
  23. 23.
    Schalk, G., McFarland, D., Hinterberger, T., Birbaumer, N., Wolpaw, J.: Bci 2000: A general-purpose brain-computer interface (BCI) system. IEEE Transactions on Biomedical Engineering 51(6), 1034–1043 (2004)CrossRefGoogle Scholar
  24. 24.
    Lu, J., Speier, W., Hu, X., Pouratian, N.: The effects of stimulus timing features on P300 speller performance. Clinical Neurophysiology 124(2), 306–314 (2013)CrossRefGoogle Scholar
  25. 25.
    McFarland, D.J., Sarnacki, W.A., Townsend, G., Vaughan, T., Wolpaw, J.R.: The P300-based brain-computer interface (BCI): Effects of stimulus rate. Clinical Neurophysiology 122(4), 731–737 (2011)CrossRefGoogle Scholar
  26. 26.
    Shih, J.J., Townsend, G., Krusienski, D.J., Shih, K.D., Shih, R.M., Heggeli, K., Paris, T., Meschia, J.F.: Comparison of checkerboard P300 speller vs. row-column speller in normal elderly and aphasic stroke population. Paper Presented at the Fifth International Brain-Computer Interface Meeting, Asilomar Conference Grounds, Pacific Grove, CA (2013). (retrieved)
  27. 27.
    Allison, B.Z., Pineda, J.A.: ERPs evoked by different matrix sizes: implications for a brain computer interface (BCI) system. IEEE Trans. Neural Syst. Rehabil. Eng. 11, 110–113 (2003)CrossRefGoogle Scholar
  28. 28.
    Li, Y., Nam, C.S., Shadden, B., Johnson, S.: A P300-based brain–computer interface (BCI): effects of interface type and screen size. International Journal of Human-Computer Interaction 27(1), 52–68 (2011)CrossRefGoogle Scholar
  29. 29.
    Hart, S.G., Staveland, L.E.: Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. Advances in Psychology 52, 139–183 (1988)Google Scholar
  30. 30.
    Cegarra, J., Morgado, N.: Étude des propriétés de la version francophone du NASATLX. In: Communication Présentée à La Cinquième édition Du Colloque De Psychologie Ergonomique (Epique) (2009)Google Scholar
  31. 31.
    Treder, M.S.: Blankertz, B,: Covert attentionand visual speller design in an ERP-based brain-commputer interface. Behav. Brain Funct. 6, 28 (2010)CrossRefGoogle Scholar
  32. 32.
    Brunner, P., Joshi, S., Briskin, S., Wolpaw, J.R., Bischof, H., Schalk, G.: Does the “P300” Speller Depend on Eye Gaze? J Neural Eng 7, 056013 (2010)CrossRefGoogle Scholar
  33. 33.
    Salvaris, M., Sepulveda, F.: Visual modifications on the P300 speller BCI paradigm. J Neural Eng 6(4), 046011 (2009)CrossRefGoogle Scholar
  34. 34.
    Kim, E., Lovera, J., Schaben, L., Melara, J., Bourdette, D., Whitman, R.: Novel method for measurement of fatigue in multiple sclerosis: Real-Time Digital Fatigue Score. J Rehabil Res Dev. 47(5), 477–484 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Liliana Garcia
    • 1
    Email author
  • Véronique Lespinet-Najib
    • 1
  • Sarah Saioud
    • 2
  • Victor Meistermann
    • 2
  • Samuel Renaud
    • 2
  • Jaime Diaz-Pineda
    • 3
  • Jean Marc André
    • 1
  • Ricardo Ron-Angevin
    • 4
  1. 1.Team CIH - Laboratory IMS CNRS UMR 5218BordeauxFrance
  2. 2.ENSC - Bordeaux INPBordeauxFrance
  3. 3.CATIE - Information and Electronic Technology Center of AquitaineAquitaineFrance
  4. 4.Dpto. Tecnología ElectrónicaUniversidad de MálagaMálagaSpain

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