Abstract
Visual Brain-Computer Interfaces (BCIs) often use LCDs or LEDs to present flickering stimuli, which limits its application scenarios. Mixed reality head-mounted displays (MRHMDs) have the potential of improving the practical applications for BCIs. However, it’s unclear whether the visual stimulus color designed for traditional BCIs still works in mixed reality. Therefore, this study developed a 10-command SSVEP-BCI system in mixed reality using Hololens2, and explored the system’s performance with two stimulus colors (white and red) against four monochrome backgrounds (green, blue, white, and black). Eight subjects participated in the experiment. Cross-correlation task-related component analysis (xTRCA) was used to recognize the target command. Results showed that both stimulus and background colors affect BCI performance. Specifically, the white stimulus color significantly outperformed the red one on the blue and black backgrounds, while the red stimulus outperformed the white one on the green and white backgrounds. The color contrast ratio (CCR) between the background and stimulus colors correlated positively with SSVEP recognition accuracy. In mixed reality, SSVEP-based BCIs must optimize visual stimulus color, and the CCR is an important criterion for optimization.
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Wolpaw, J.R., Birbaumer, N., McFarland, D.J., Pfurtscheller, G., Vaughan, T.M.: Brain-computer interfaces for communication and control. Clin. Neurophysiol. 113(6), 767–791 (2016)
Xiao, X., et al.: Enhancement for P300-speller classification using multi-window discriminative canonical pattern matching. J. Neural Eng. 18(4), 046–079 (2021)
Wolpaw, J.R.: Brain-computer interfaces as new brain output pathways. J. Physiol. 579(3), 613–619 (2007)
Ramadan, R., Vasilakos, A.: Brain computer interface: control signals review. Neurocomputing 27(5), 26–44 (2017)
Wang, Y., Gao, X., Hong, B., Jia, C., Gao, S.: Brain-Computer Interfaces Based on Visual Evoked Potentials. IEEE Eng. Med. Biol. Mag. 223(5), 64–71 (2008)
Wu, Z., Lai, Y., Xia, Y., Wu, D., Yao, D.: Stimulator selection in SSVEP-based BCI. Med. Eng. Phys. 30(8), 1079–1088 (2008)
Kouji, T., Naoki, H., Kenji, K.: Towards intelligent environments: an augmented reality–brain–machine interface operated with a see-through head-mount display. Front. Neurosci. 5, 60 (2011)
Choi, J., Jo, S.: Application of hybrid brain-computer interface with augmented reality on quadcopter control. In: 8th International Winter Conference on Brain-Computer Interface (BCI), pp. 1–5. IEEE, Gangwon, Korea (South) (2020)
Angrisani, L., Arpaia, P., Moccaldi, N., Esposito, N.: Wearable augmented reality and brain computer interface to improve human-robot interactions in smart industry: a feasibility study for SSVEP signals. In: 4th IEEE International Forum on Research and Technology for Society and Industry, pp. 1–5. IEEE, Palermo, Italy (2018)
Horii, S., Nakauchi, S., Kitazaki, M.: AR-SSVEP for brain-machine interface: estimating user’s gaze in head-mounted display with USB camera. In: 2015 IEEE Virtual Reality, pp. 193–194. IEEE, Arles, France (2015)
Meng, W., Li, R., Zhang, R., Li, G., Zhang, D.: A wearable SSVEP-based BCI system for quadcopter control using head-mounted device. IEEE Access 6, 26789–26798 (2018)
Tello, R.J.M.G., Müller, S.M.T., Ferreira, A., Bastos, T.F.: Comparison of the influence of stimuli color on steady-state visual evoked potentials. Res. Biomed. Eng. 1(3), 1041–1047 (2015)
Cao, T., Wan, F., Mak, P.U., Mak, P.I., Vai, M.I., Hu, Y.: Flashing color on the performance of SSVEP-based brain-computer interfaces. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1819–1822. IEEE, San Diego, CA, USA (2012)
Ke, Y., Liu, P., An, X., Song, X., Ming, D.: An online SSVEP-BCI system in an optical see-through augmented reality environment. J. Neural Eng. 17(1), 016066 (2020)
Wang, Y.T., Jung, T.P.: Visual stimulus design for high-rate SSVEP BCI. Electron. Lett. 46(15), 1057–1058 (2010)
Nakanishi, M., Wang, Y., Chen, X., Wang, Y.T., Gao, X., Jung, T.P.: Enhancing detection of SSVEPs for a high-speed brain speller using task-related component analysis. IEEE Trans. Biomed. Eng. 65(1), 104–112 (2017)
Tanaka, H., Miyakoshi, M.: Cross-correlation task-related component analysis (xTRCA) for enhancing evoked and induced responses of event-related potentials. Neuroimage 197, 177–190 (2019)
Consortium, W.: Web content accessibility guidelines (WCAG) 2.0 (2015)
Conway, B.R., Hubel, D.H., Livingstone, M.S.: Color contrast in macaque V1. Cereb. Cortex 12(9), 915–925 (2002)
Acknowledgments
Research supported by National Natural Science Foundation of China (No. 62106170, 62122059, 81925020, 61976152), Introduce Innovative Teams of 2021 “New High School 20 Items” Project (2021GXRC071), and Tianjin Key Technology R&D Program (No. 17ZXRGGX00020).
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He, F. et al. (2023). Optimization of Stimulus Color for SSVEP-Based Brain-Computer Interfaces in Mixed Reality. In: Ying, X. (eds) Human Brain and Artificial Intelligence. HBAI 2022. Communications in Computer and Information Science, vol 1692. Springer, Singapore. https://doi.org/10.1007/978-981-19-8222-4_16
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DOI: https://doi.org/10.1007/978-981-19-8222-4_16
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