Exploring Multistable Perception to Modulate Steady-State Visual Evoked Potentials using a Computer Graphics Software for a Brain-Computer Interface
Resumo
This study investigated the use of multistable perception to modulate steady-state visual evoked potentials (SSVEPs) using a computer graphics program and an LCD monitor. The Rubin’s vase ambiguous image was employed for this purpose. A visual stimulator was developed in C++ using the Open Graphics Library (OpenGL). EEG was measured on the occipital area (Oz) of the subject, and a Brain-Computer Interface (BCI) was developed to control a robot in a virtual reality environment. Commands were recognized using the Multivariate Synchronization Index (MSI) method. The results demonstrate the feasibility of eliciting and modulating SSVEP response. During online evaluation, the subject were able to command a virtual telepresence robot with over 80% accuracy and an Information Transfer Rate (ITR) of 7 bits/min.
Referências
Cotrina, A., Benevides, A. B., Castillo-Garcia, J., Benevides, A. B., Rojas-Vigo, D., Ferreira, A., and Bastos-Filho, T. F. (2017). A ssvep-bci setup based on depth-of-field. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(7):1047–1057.
Floriano, A., Carmona, V. L., Diez, P. F., and Bastos-Filho, T. F. (2019). A study of ssvep from below-the-hairline areas in low-, medium-, and high-frequency ranges. Research on Biomedical Engineering, 35(1):71–76.
Mora-Cortes, A., Ridderinkhof, K. R., and Cohen, M. X. (2018). Evaluating the feasibility of the steady-state visual evoked potential (ssvep) to study temporal attention. Psychophysiology, 55(5):e13029.
Morgan, S., Hansen, J., and Hillyard, S. (1996). Selective attention to stimulus location modulates the steady-state visual evoked potential. Proceedings of the National Academy of Sciences of the United States of America, 93(10):4770–4774.
Tello, R. M., Müller, S. M., Hasan, M. A., Ferreira, A., Krishnan, S., and Bastos, T. F. (2016). An independent-bci based on ssvep using figure-ground perception (fgp). Biomedical Signal Processing and Control, 26:69–79.
Vialatte, F.-B., Maurice, M., Dauwels, J., and Cichocki, A. (2010). Steady-state visually evoked potentials: focus on essential paradigms and future perspectives. Progress in neurobiology, 90(4):418–438.
Wang, Y., Wang, Y.-T., and Jung, T.-P. (2010). Visual stimulus design for high-rate ssvep bci. Electronics letters, 46(15):1057–1058.
Xie, S., Liu, C., Obermayer, K., Zhu, F., Wang, L., Xie, X., and Wang, W. (2016). Stimulator selection in ssvep-based spatial selective attention study. Computational intelligence and neuroscience, 2016:6410718.
Yadav, H. and Maini, S. (2023). Electroencephalogram based brain-computer interface: Applications, challenges, and opportunities. Multimedia Tools and Applications, 82(30):47003–47047.
Zhang, Y., Xu, P., Cheng, K., and Yao, D. (2014). Multivariate synchronization index for frequency recognition of ssvep-based brain–computer interface. Journal of neuroscience methods, 221:32–40.
Zhu, D., Bieger, J., Molina, G. G., and Aarts, R. M. (2010). A survey of stimulation methods used in ssvep-based bcis. Computational intelligence and neuroscience, 2010:1.
