A Hybrid Asynchronous Brain-Computer Interface Combining SSVEP and EOG Signals for Rapid Target Recognition

• Published in: Intelligent Robotics and Applications pp. 760 - 770
• Main Authors: Mai, Ximing, Sheng, Xinjun, Shu, Xiaokang, Ding, Yidan, Meng, Jianjun, Zhu, Xiangyang
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Asynchronous BCI; Hybrid BCI; Saccade eye movement; SSVEP; Target recognition
• ISBN: 9783031138218; 303113821X
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-031-13822-5_68

Brain-Computer interfaces (BCIs) can help the disabled restore their ability of communicating and interacting with the environment. Asynchronous steady-steady visual evoked potential (SSVEP) allows the user to fully control the BCI system, but it also faces the challenge of the long erroneous state when the user switches his/her aimed target. To tackle this problem, a training-free SSVEP and EOG hybrid BCI system was proposed, where the spontaneous saccade eye movement occurred in SSVEP paradigm was hybridized into SSVEP detection by Bayesian approach to recognize the new target rapidly and accurately. The experiment showed that the proposed hybrid BCI had significantly higher asynchronous accuracy and short gaze shifting time compared to the conventional SSVEP-BCI. The results indicated the feasibility and efficacy of introducing the spontaneous eye movement information into SSVEP detection without increasing the user’s task burden.