An online hybrid BCI combining SSVEP and EOG-based eye movements

Hybrid brain-computer interface (hBCI) refers to a system composed of a single-modality BCI and another system. In this paper, we propose an online hybrid BCI combining steady-state visual evoked potential (SSVEP) and eye movements to improve the performance of BCI systems. Twenty buttons correspond...

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Bibliographic Details
Published in:Frontiers in human neuroscience 2023-02, Vol.17, p.1103935-1103935
Main Authors: Zhang, Jun, Gao, Shouwei, Zhou, Kang, Cheng, Yi, Mao, Shujun
Format: Article
Language:English
Subjects:
Accuracy
Brain
Buttons
Computer applications
Decision making
Electrodes
Electroencephalography
Electromyography
electrooculography (EOG)
Experiments
Eye
Eye movements
Human Neuroscience
hybrid brain-computer interface (hBCI)
Implants
Information processing
information transmission rate
Interfaces
steady-state visual evoked potential (SSVEP)
Systems stability
Visual evoked potentials
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Summary:Hybrid brain-computer interface (hBCI) refers to a system composed of a single-modality BCI and another system. In this paper, we propose an online hybrid BCI combining steady-state visual evoked potential (SSVEP) and eye movements to improve the performance of BCI systems. Twenty buttons corresponding to 20 characters are evenly distributed in the five regions of the GUI and flash at the same time to arouse SSVEP. At the end of the flash, the buttons in the four regions move in different directions, and the subject continues to stare at the target with eyes to generate the corresponding eye movements. The CCA method and FBCCA method were used to detect SSVEP, and the electrooculography (EOG) waveform was used to detect eye movements. Based on the EOG features, this paper proposes a decision-making method based on SSVEP and EOG, which can further improve the performance of the hybrid BCI system. Ten healthy students took part in our experiment, and the average accuracy and information transfer rate of the system were 94.75% and 108.63 bits/min, respectively.
ISSN:1662-5161
1662-5161
DOI:10.3389/fnhum.2023.1103935