ArticleFrontiers in human neuroscience2023
An online hybrid BCI combining SSVEP and EOG-based eye movements.
Article in Frontiers in human neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 20 citations in OpenAlex.
- A Cheonjiin Layout Mental Speller: Developing a Simple and Cost-Effective EEG-Based Brain-Computer Interface System.Sensors (Basel, Switzerland) · 2026Article
- Bridging cognition and control through passive eye movement integration in motor imagery brain-computer interfaces.Frontiers in human neuroscience · 2026Review
- Intersession Robust Hybrid Brain-Computer Interface: Safe and User-Friendly Approach with LED Activation Mechanism.Micromachines · 2025Article
- A Safe and Efficient Brain-Computer Interface Using Moving Object Trajectories and LED-Controlled Activation.Micromachines · 2025Article
- Development of a humanoid robot control system based on AR-BCI and SLAM navigation.Cognitive neurodynamics · 2024Article
- The role of eye movement signals in non-invasive brain-computer interface typing system.Medical & biological engineering & computing · 2024Review
- Non-invasive EEG-based BCI spellers from the beginning to today: a mini-review.Frontiers in human neuroscience · 2023Review
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Authors and funding
5 authors at 1 institution in 1 country.
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Abstract
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.
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