https://orcid.org/0000-0001-5322-601X
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ABSTRACT
Brain–Computer Interfaces (BCIs) are specialized systems that allow users to control computer applications using their brain waves. With the advent of consumer-grade electroencephalography (EEG) devices, brain-controlled systems started to find applications outside of the medical field, opening many research opportunities in the area of Human-Computer Interaction (HCI). One particular area that is gaining more evidence due to the arrival of consumer-grade devices is that of computer games, as it allows more user-friendly applications of BCI technology for the general public. In this paper, the results of a Systematic Literature Review (SLR) of BCI games using consumer-grade devices are presented. Papers published in a time span of 12 years were reviewed and their data collected using a rigid systematic process. Several analyses were made based on the gathered data, and a clear view of the current scenario and challenges for HCI of BCI-based games using consumer-grade devices is provided. The search shows that although many games were created with simplified controls for research purposes, there was an increasing number of more user-friendly BCI games, especially for entertainment. The most predominant control signals were the attention and meditation, followed by motor imagery and emotion recognition, being mainly captured by NeuroSky and Emotiv EEG devices. The results also show that there are still many open issues and research opportunities in the field of HCI for BCI-based games, as most evaluations investigated only quantitative aspects of the BCI systems, while very few studies analyzed usability and qualitative aspects of the users’ interaction with the games.
Acknowledgments
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 National Council of Scientific and Technological Development (CNPq) under grant 130158/2015-1 and by the Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES). We also would like to thank the resources of the PAIRG’s Laboratory of Physical and Physiological Computing (PAIRG L2PC) at UFRN, and the reviewers that participated in the evaluation of our work, providing us with constructive criticism and many important insights and suggestions for discussion and inclusion in the manuscript.
Disclosure of potential conflicts of interest
There are no conflicts of interest to disclose.
Notes
1. The term “Brain-Machine Interface” (BMI) is often used in such cases.
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Notes on contributors
Gabriel Alves Mendes Vasiljevic
Gabriel Alves Mendes Vasiljevic is currently a Ph.D. candidate of Computer Science at the Federal University of Rio Grande do Norte (UFRN) and a member of the Physical Artifacts of Interaction Research Group (PAIRG) at UFRN. He is currently working on researches in the areas of human-computer interaction and physiological computing, focusing on brain-computer interfaces.
Leonardo Cunha de Miranda
Leonardo Cunha de Miranda is an Associate Professor at the Federal University of Rio Grande do Norte (UFRN). He is also the founder/head of the Physical Artifacts of Interaction Research Group (PAIRG) at UFRN and the founder/coordinator of the PAIRG’s Laboratory of Physical and Physiological Computing (PAIRG L2PC) at UFRN. He received a Ph.D. degree in computer science from the University of Campinas (UNICAMP). His areas of interests are human-computer interaction, physical computing, physiological computing, and his current research interests include tangible interface, gestural interface and brain-computer interface.