Review of brain-computer interface based on steady-state visual evoked potential

被引：0
|
作者：
Siyu Liu [1 ]
Deyu Zhang [2 ]
Ziyu Liu [1 ]
Mengzhen Liu [2 ]
Zhiyuan Ming [2 ]
Tiantian Liu [1 ]
Dingjie Suo [1 ]
Shintaro Funahashi [3 ,4 ]
Tianyi Yan [1 ]
机构：
[1] School of Life Science, Beijing Institute of Technology
[2] School of Mechanical and Electrical Engineering, Beijing Institute of Technology
[3] Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology
[4] Kyoto University
来源：
Brain Science Advances | 2022年 / 8卷 / 04期
基金：
中国国家自然科学基金; 中国博士后科学基金; 中央高校基本科研业务费专项资金资助;
关键词：
D O I：
暂无
中图分类号：
TN911.7 [信号处理]; R318 [生物医学工程];
学科分类号：
0711 ; 080401 ; 080402 ; 0831 ;
摘要：
The brain–computer interface(BCI) technology has received lots of attention in the field of scientific research because it can help disabled people improve their quality of life. Steady-state visual evoked potential(SSVEP) is the most researched BCI experimental paradigm, which offers the advantages of high signal-to-noise ratio and short training-time requirement by users. In a complete BCI system, the two most critical components are the experimental paradigm and decoding algorithm. However, a systematic combination of the SSVEP experimental paradigm and decoding algorithms is missing in existing studies. In the present study, the transient visual evoked potential, SSVEP, and various improved SSVEP paradigms are compared and analyzed, and the problems and development bottlenecks in the experimental paradigm are finally pointed out. Subsequently, the canonical correlation analysis and various improved decoding algorithms are introduced, and the opportunities and challenges of the SSVEP decoding algorithm are discussed.
引用
收藏
页码：258 / 275
页数：18
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