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International Work-Conference on Artificial Neural Networks

IWANN 2019: Advances in Computational Intelligence pp 418–429Cite as

A VR-Based Hybrid BCI Using SSVEP and Gesture Input

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11506))

Abstract

Brain-Computer Interfaces (BCIs) using Steady-State Visual Evoked Potentials have been proven to work with many different display technologies for visual stimulation. The recent advent of consumer grade Virtual Reality (VR) Head-Mounted Devices (VR-HMDs) has made research in the area of VR-based BCIs more accessible than ever - yet the possibilities of such systems still have to be tested. In this paper, we present a BCI using a well-studied 3-step spelling interface converted into a Virtual Environment (VE). The Oculus Rift CV1 VR-HMD used in this study also provides motion tracking capability, which was used to implement a novel hybrid BCI utilizing gesture input. The interface consisted of three flickering boxes on a virtual screen in the VE for typing letters. Head shake gestures were used to intuitively trigger “Delete/Back” commands. A g.tec g.USBamp amplifier was used to record and filter the signal of eight electrodes mounted in an electroencephalography cap. The Minimum Energy Combination (MEC) method was used to classify commands in real time. Eighteen participants successfully performed seven spelling tasks each, reaching an accuracy of 91.11 ± 10.26% (mean ± Standard Deviation, SD) and an Information Transfer Rate of 23.56 ± 7.54 bit/minute (mean ± SD). Questionnaires filled out before and after the experiment show that most participants enjoyed the VR BCI experience and found the gesture input very natural. Future studies could expand the input mechanism by adding more head gestures, e.g. pecking, nodding or circling to control intuitively related software tasks.

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Acknowledgments

This work was supported by the European Fund for Regional Development (EFRD - or EFRE in German) under Grant IT-1-2-001. We thank all the participants of this research study as well as our student assistants.

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Authors and Affiliations

  1. Faculty of Technology and Bionics, Rhine-Waal University of Applied Sciences, 47533, Kleve, Germany

    Roland Grichnik, Mihaly Benda & Ivan Volosyak

Authors
  1. Roland Grichnik
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  2. Mihaly Benda
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  3. Ivan Volosyak
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Corresponding author

Correspondence to Ivan Volosyak .

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Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. University of Malaga, Malaga, Spain

    Gonzalo Joya

  3. Polytechnic University of Catalonia, Barcelona, Spain

    Andreu Catala

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Grichnik, R., Benda, M., Volosyak, I. (2019). A VR-Based Hybrid BCI Using SSVEP and Gesture Input. 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_35

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  • DOI: https://doi.org/10.1007/978-3-030-20521-8_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20520-1

  • Online ISBN: 978-3-030-20521-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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