Towards a Hybrid BCI Gaming Paradigm Based on Motor Imagery and SSVEP

Brain-computer interfaces (BCIs) not only can allow individuals to voluntarily control external devices, helping to restore lost motor functions of the disabled, but can also be used by healthy users for entertainment and gaming applications. In this study, we proposed a hybrid BCI paradigm to explo...

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Bibliographic Details
Published in:International journal of human-computer interaction Vol. 35; no. 3; pp. 197 - 205
Main Authors: Wang, Zhihua, Yu, Yang, Xu, Ming, Liu, Yadong, Yin, Erwei, Zhou, Zongtan
Format: Journal Article
Language:English
Published: Norwood Taylor & Francis 07.02.2019
Lawrence Erlbaum Associates, Inc
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ISSN:1044-7318, 1532-7590, 1044-7318
Online Access:Get full text
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Summary:Brain-computer interfaces (BCIs) not only can allow individuals to voluntarily control external devices, helping to restore lost motor functions of the disabled, but can also be used by healthy users for entertainment and gaming applications. In this study, we proposed a hybrid BCI paradigm to explore a feasible and natural way to play games by using electroencephalogram (EEG) signals in a practical environment. In this paradigm, we combined motor imagery (MI) and steady-state visually evoked potentials (SSVEPs) to generate multiple commands. A classic game, Tetris, was chosen as the control object. The novelty of this study includes the effective usage of a "dwell time" approach and fusion rules to design BCI games. To demonstrate the feasibility of the proposed hybrid paradigm, ten subjects were chosen to participate in online control experiments. The experimental results showed that all subjects successfully completed the predefined tasks with high accuracy. This proposed hybrid BCI paradigm could potentially provide those who suffer disability or paralysis with additional entertainment options, such as brain-actuated games, that could improve their happiness and quality of life. Abbreviations: BCI: brain-computer interface; EEG: electroencephalogram; MI: motor imagery; SSVEP: steady-state visually evoked potential; ERP: event-related potential; SMR: sensorimotor rhythm; VEP: visual evoked potential; TCP/IP: transmission control protocol/internet protocol; GUI: graphical user interface; ERD/ERS: event-related desynchronization/synchronization; CIC: control intention classifier; LRC: left/right classifier; CSP: common spatial pattern; LDA: linear discriminant analysis; ROC: receiver operating characteristic; TPR: true positive rate; FPR: false positive rate; CCA: canonical correlation analysis.
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ISSN:1044-7318
1532-7590
1044-7318
DOI:10.1080/10447318.2018.1445068