Model, Taxonomy and Methodology for Research Employing EEG-based Brain-Computer Interface Games


The rapid expansion of Brain-Computer Interface technology, aligned with the advancements on the fields of Human-Computer Interaction, Physiological Computing and Machine Learning, 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 the fields of BCI and games, since they can be played by virtually any person regardless of physical condition, can be applied in numerous contexts, and are ludic by nature. Despite these recent advancements, there is still no solid theoretical foundation to aggregate the terminology and methods of these fields, since current models and classification schemes can represent characteristics of either BCI systems or games, but not both. In this sense, the thesis summarized in this work presents a model for representing EEG-based BCI games, a taxonomy for classifying and comparing studies of the field, and a methodology for conducting scientific studies using those games. The model is intended to describe and develop new EEG games by instantiating its components. The CoDIS taxonomy considers four aspects of such games: concept, design, implementation and study, each with different dimensions to represent various of their characteristics. Based on the model and the taxonomy, the PIERSE methodology was developed for the planning, implementation, execution and reporting of scientific experiments using those games. The contributions of the thesis are detailed in various dimensions in this manuscript.
Palavras-chave: HCI, BCI, EEG, Games


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VASILJEVIC, Gabriel Alves Mendes; CUNHA DE MIRANDA, Leonardo. Model, Taxonomy and Methodology for Research Employing EEG-based Brain-Computer Interface Games. In: SIMPÓSIO BRASILEIRO SOBRE FATORES HUMANOS EM SISTEMAS COMPUTACIONAIS (IHC), 22. , 2023, Maceió/AL. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 .