Abstract
Brain-computer interface (BCI) technology, including applications based on the steady-state visual evoked potentials (SSVEPs) have proven to provide reliable and accurate control. In this paper, we present and evaluate remote steering of a previously developed and successfully tested mobile robotic car (MRC) utilizing the SSVEP-based BCI system. The visual stimulations were presented inside the head-mounted virtual reality (VR) glasses, here, the Oculus Go. The live video feedback from the MRCs point of view was displayed inside the custom made app of the VR environment. The three visual stimuli were located on both sides and above the video stream of the MRC camera.
The task of this study was to steer the MRC through a 8 m long path (in the real world) with 6 turns. Seven participants took part in the experiment reaching on average an accuracy of 98.1 (standard deviation: 5.04) %, an information transfer rate (ITR) of 10.71 (2.78) bits/min with an average command classification time of 3.95 (2.3) seconds. For classification, the minimum energy combination method (MEC) with 16 EEG electrodes as well as a filter bank decomposing method were utilized. All participants successfully completed the task, almost all subjects stated that the presented VR-based SSVEP-BCI was a highly immersive experience.
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References
Beraldo, G., Antonello, M., Cimolato, A., Menegatti, E., Tonin, L.: Brain-computer interface meets ROS: a robotic approach to mentally drive telepresence robots. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 1–6, May 2018. https://doi.org/10.1109/ICRA.2018.8460578
Chen, X., Wang, Y., Gao, S., Jung, T.P., Gao, X.: Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface. J. Neural Eng. 12(4), 046008 (2015)
Friman, O., Volosyak, I., Graser, A.: Multiple channel detection of steady-state visual evoked potentials for brain-computer interfaces. IEEE Trans. Biomed. Eng. 54(4), 742–750 (2007)
Gergondet, P., Petit, D., Kheddar, A.: Steering a robot with a brain-computer interface: impact of video feedback on BCI performance. In: 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication, pp. 271–276. IEEE (2012)
Kerous, B., Skola, F., Liarokapis, F.: EEG-based BCI and video games: a progress report. Virtual Reality 22, 1–17 (2017)
Koo, B., Lee, H.G., Nam, Y., Choi, S.: Immersive BCI with SSVEP in VR head-mounted display. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1103–1106. IEEE (2015)
Ron-Angevin, R., Velasco-Alvarez, F., Sancha-Ros, S., da Silva-Sauer, L.: A two-class self-paced BCI to control a robot in four directions. In: 2011 IEEE International Conference on Rehabilitation Robotics (ICORR), pp. 1–6. IEEE (2011)
Stawicki, P., et al.: Investigating spatial awareness within an SSVEP-based BCI in virtual reality. In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 615–618. IEEE (2018)
Stawicki, P., et al.: SSVEP-based BCI in virtual reality-control of a vacuum cleaner robot. In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 534–537. IEEE (2018)
Stawicki, P., Gembler, F., Volosyak, I.: Evaluation of suitable frequency differences in SSVEP-based BCIs. In: Blankertz, B., Jacucci, G., Gamberini, L., Spagnolli, A., Freeman, J. (eds.) Symbiotic 2015. LNCS, vol. 9359, pp. 159–165. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24917-9_17
Stawicki, P., Gembler, F., Volosyak, I.: Driving a semiautonomous mobile robotic car controlled by an SSVEP-based BCI. Comput. Intell. Neurosci. 2016, 5 (2016)
Volosyak, I.: SSVEP-based bremen-BCI interface–boosting information transfer rates. J. Neural Eng. 8(3), 036020 (2011)
Wang, F., Zhang, X., Fu, R., Sun, G.: Study of the home-auxiliary robot based on BCI. Sensors 18(6), 1779 (2018)
Wolpaw, J.R., et al.: Independent home use of a brain-computer interface by people with amyotrophic lateral sclerosis. Neurology 91(3), e258–e267 (2018)
Wolpaw, J., Birbaumer, N., McFarland, D., Pfurtscheller, G., Vaughan, T.: Brain-computer interfaces for communication and control. Clin. Neurophysiol. 113, 767–791 (2002)
Wu, C.M., Chen, Y.J., Zaeni, I.A., Chen, S.C.: A new SSVEP based BCI application on the mobile robot in a maze game. In: 2016 International Conference on Advanced Materials for Science and Engineering (ICAMSE), pp. 550–553. IEEE (2016)
Acknowledgment
This research was supported by the European Fund for Regional Development (EFRD or EFRE in German) under Grants GE-1-1-047, and IT-1-2-001. We also thank all the participants of this research study and our student assistants.
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Stawicki, P., Gembler, F., Grichnik, R., Volosyak, I. (2019). Remote Steering of a Mobile Robotic Car by Means of VR-Based SSVEP BCI. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2019. Lecture Notes in Computer Science(), vol 11506. Springer, Cham. https://doi.org/10.1007/978-3-030-20521-8_34
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