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A General Model for Electroencephalography-Controlled Brain-Computer Interface Games

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12250))

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Abstract

The rapid expansion of Brain-Computer Interface (BCI) technology allowed for the recent development of applications outside of clinical environments, such as education, arts and games. Games controlled by electroencephalography (EEG), a specific case of BCI technology, benefit from both areas, since they can be played by virtually any person regardless of physical condition, can be applied in numerous serious and entertainment contexts, and are ludic by nature. However, they also share the same challenges of design and development from both fields, especially since they demand numerous specific and specialized knowledge for their development. In this sense, this work presents a model for games using EEG-based BCI controls. The proposed model is intended to help researchers describe, compare and develop new EEG-controlled games by instantiating its abstract and functional components using concepts from the fields of BCI and games. A group of EEG-controlled games from the literature was selected to demonstrate the usefulness and representativeness of the model. The demonstration showed that an overview classification and the details of the selected games were able to be described using the model and its components.

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Notes

  1. 1.

    This is also the reason that the game component is referred as “EEG-controlled” rather than “EEG-based” in this work, as the first term is a generalization of the latter, i.e., it can represent any game that is controlled by EEG, including those that are based solely on this kind of control.

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Acknowledgements

This work was supported by the Physical Artifacts of Interaction Research Group (PAIRG) at the Federal University of Rio Grande do Norte (UFRN), and partially funded by the Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES). We also thank the resources of the PAIRG’s Laboratory of Physical and Physiological Computing (PAIRG L2PC) at UFRN.

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Authors and Affiliations

  1. Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil

    Gabriel Alves Mendes Vasiljevic & Leonardo Cunha de Miranda

Authors
  1. Gabriel Alves Mendes Vasiljevic
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  2. Leonardo Cunha de Miranda
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Correspondence to Gabriel Alves Mendes Vasiljevic .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

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Vasiljevic, G.A.M., de Miranda, L.C. (2020). A General Model for Electroencephalography-Controlled Brain-Computer Interface Games. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12250. Springer, Cham. https://doi.org/10.1007/978-3-030-58802-1_13

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  • DOI: https://doi.org/10.1007/978-3-030-58802-1_13

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