Research on Biomedical Engineering
Research on Biomedical Engineering
Original Article

Statistical evaluation of a novel SSVEP-BCI stimulation setup based on depth-of-field

Cotrina, Anibal; Benevides, Alessandro Botti; Castillo-Garcia, Javier; Ferreira, Andre; Bastos Filho, Teodiano Freire

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Introduction: The main drawback of a Brain-computer Interface based on Steady-State Visual Evoked Potential (SSVEP-BCI) that detects the emergence of visual evoked potentials (VEP) in reaction to flickering stimuli is its muscular dependence due to users must redirect their gaze to put the target stimulus in their field of view. In this work, a novel setup is evaluated in which two stimuli are placed together in the center of users’ field of view, but with dissimilar distances from them, so that the target selection is performed by focus shifting instead of head, neck and/or eyeball movements. Methods: A model of VEP generation for the novel setup was developed. The Spectral F-test based on Bartett periodogram was used to evaluate the null hypothesis of absence of effects of the non-focused stimulus (NFS) within the VEP elicited by the focused stimulus (FS). To reinforce that there is not statistical evidence to support the presence of NFS effects, the PSDA detection method was employed to find the frequency of FS. Electroencephalographic signals of nine subjects were recorded. Results: Approximately in 80% of the tests, the null hypothesis with 5% level of significance was non-rejected at the fundamental frequency of NFS. The average of the accuracy rate attained with PSDA detection method was 79.4%. Conclusion: Results of this work become further evident to state that if the focused stimulus (FS) will be able to elicit distinguishable VEP pattern regardless the non-focused stimulus (NFS) is also present.


Brain-computer interface, Steady-state visual evoked potential, Depth-of-field, Objective response detection, Statistical F-test.


Allison B, 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 Transactions on Neural Systems and Rehabilitation Engineering. 2010; 18(2):107-16. PMid:20083463.

Allison BZ, McFarland D, Schalk G, Zheng S, Jackson M, Wolpaw J. Towards an independent brain-computer interface using steady state visual evoked potentials. Clinical Neurophysiology. 2008; 119(2):399-408. PMid:18077208.

Bastos TF Fo, Cheein FA, Müller SM, Celeste WC, de la Cruz C, Cavalieri DC, Sarcinelli M Fo, Amaral PF, Perez E, Soria CM, Carelli R. Towards a new modality-independent interface for a robotic wheelchair. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2014; 22(3):567-84. PMid:23744700.

Benevides AB, Cotrina A, Castillo J, Bastos TF Fo, Benevides AB. An ethernet sniffer for on-line acquisition of EEG with the BrainNet36 device applied to a BCI. In: Proceedings of Biosignals and Biorobotics Conference; 2014 May 26-28; Salvador. USA: IEEE; 2014. p. 1-6.

Cheng M, Gao X, Gao S, Xu D. Design and implementation of a brain-computer interface with high transfer rates. IEEE Transactions on Biomedical Engineering. 2002; 49(10):1181-6. PMid:12374343.

Cotrina A, Bastos T, Ferreira A, Benevides A, Castillo J, Rojas D, Benevides A. Towards a SSVEP-BCI based on depth of field. In: Proceedings of the 6th International BCI Conference; 2014 Sept 16-19; Graz. Graz: Graz University of Technology Publishing House; 2014. p. 1-4.

Di Summa A, Fusine S, Bertolasi L, Vicentini S, Perlini S, Bongiovanni LG, Polo A. Mechanism of binocular interaction in refraction errors: study using pattern-reversal visual evoked potentials. Documenta Ophthalmologica. 1999; 98(2):139-51.

Ebenholtz SM. Oculomotor systems and perception. Cambridge: Cambridge University Press; 2001.

Fawcett T. An introduction to ROC analysis. Pattern Recognition Letters. 2005; 27(8):861-74.

Felix LB, Ranaudo FS, Netto AD, Sá AMFLM. A spatial approach of magnitude-squared coherence applied to selective attention detection. Journal of Neuroscience Methods. 2014; 229(30):28-32. PMid:24704394.

Ferreira A, Muller S, Celeste W, Cavalieri D, Benevides A, Filgueira P, Amaral P, Sarcinelli M Fo. Bastos TF Fo, Perez E, Soria C. Smart wheelchairs. In: Bastos T, Kumar D, Arjunan SP, editors. Devices for mobility and manipulation for people with reduced abilities. Boca Raton: CRC Press; 2014. p. 15-40.

Gregory RL. Eye and brain: the psychology of seeing. 5th ed. Princeton: Princeton University Press; 1997.

Guger C, Allison BZ, Großwindhager B, Prückl R, Hintermüller C, Kapeller C, Bruckner M, Krausz G, Edlinger G. How many people could use an SSVEP BCI? Frontiers in Neuroscience. 2012; 6(169):169. PMid:23181009.

He B, Gao S, Yuan H, Wolpaw JR. Brain computer interfaces. In: He B, editor. Neural engineering. New York: Springer; 2013. p. 87-151.

Howard I. Perceiving in depth: basic mechanisms. Oxford: Oxford University Press; 2012. v. 1.

Infantosi A, Lazarev V, De Campos D. Detecting responses to intermittent photic stimulation in the electroencephalogram using the Spectral F Test. Revista Brasileira de Engenharia Biomédica. 2005; 21(1):25-36.

Jiang J. Large sample techniques for statistics. New York: Springer; 2010.

Kelly SP, Lalor E, Finucane C, McDarby G, Reilly R. Visual spatial attention control in an independent brain-computer interface. IEEE Transactions on Biomedical Engineering. 2005; 52(9):1588-96. PMid:16189972.

Lesenfants D, Habbal D, Lugo Z, Lebeau M, Horki P, Amico E, Pokorny C, Gomez F, Soddu A, Muller-Putz G, Laureys S, Noirhomme Q. An independent SSVEP-based brain-computer interface in locked-in syndrome. Journal of Neural Engineering. 2014; 11(3):035002. PMid:24838215.

Melges D, Sa A, Infantosi A. Frequency-domain objective response detection techniques applied to evoked potentials: a review. In: Naik GR, editor. Applied biological engineering: principles and practice. Rijeka: Intech; 2012. p. 47-84.

Middendorf M, McMillan G, Calhoun G, Jones KS. Brain-computer interfaces based on the steady-state visual-evoked response. IEEE Transactions on Rehabilitation Engineering. 2000; 8(2):211-4. PMid:10896190.

Muller S, Celeste W, Bastos T, Sarcinelli M. Brain-computer interface based on visual evoked potentials to command autonomous robotic wheelchair. Journal of Medical and Biological Engineering. 2010; 30(6):407-15.

Müller-Putz GR, Eder E, Wriessnegger SC, Pfurtscheller G. Comparison of DFT and lock-in amplifier features and search for optimal electrode positions in SSVEP-based BCI. Journal of Neuroscience Methods. 2008; 168(1):174-81. PMid:17980917.

Sá AM, Cagy M, Lazarev VV, Infantosi AF. Spectral F-test power evaluation in the EEG during intermittent photic stimulation. Arquivos de Neuro-Psiquiatria. 2006; 64(2-A):228-32. PMid:16791361.

Simpson DM, Tierra-Criollo CJ, Leite RT, Zayen EJ, Infantosi AF. Objective response detection in an electroencephalogram during somatosensory stimulation. Annals of Biomedical Engineering. 2000; 28(6):691-8. PMid:10983714.

Sokol S, Moskowitz A. Effect of retinal blur on the peak latency of the pattern evoked potential. Vision Research. 1981; 21(8):1279-86. PMid:7314511.

Spanos A. Probability theory and statistical inference: econometric modelling with observational data. Cambridge: Cambridge University Press; 1999.

Sutter EE. The brain response interface: Communication through visually-induced, electrical brain responses. Journal of Microcomputer Applications. 1992; 15(1):31-5.

Tierra-Criollo CJ, Infantosi AF. Low-frequency oscillations in human tibial somatosensory evoked potentials. Arquivos de Neuro-Psiquiatria. 2006; 64(2B):402-6. PMid:16917609.

Vishwanath D, Blaser E. Retinal blur and the perception of egocentric distance. Journal of Vision. 2010; 10(10):26. PMid:20884491.

Wang B, Ciuffreda KJ. Depth-of-focus of the human eye: theory and clinical implications. Survey of Ophthalmology. 2006; 51(1):75-85. PMid:16414364.

Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. Brain-computer interfaces for communication and control. Clinical Neurophysiology. 2002; 113(6):767-91. PMid:12048038.

Yin E, Zhou Z, Jiang J, Yu Y, Hu D. A dynamically optimized SSVEP brain-computer interface (BCI) speller. IEEE Transactions on Biomedical Engineering. 2015; 62(6):1447-56. PMid:24801483.

Zhang D, Maye A, Gao X, Hong B, Engel AK, Gao S. An independent brain-computer interface using covert non-spatial visual selective attention. Journal of Neural Engineering. 2010; 7(1):16010. PMid:20083864.
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