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基于稳态视觉诱发电位的脑机接口拼写器：聚焦刺激范式与性能的综述

Brain-Computer Interface Speller Based on Steady-State Visual Evoked Potential: A Review Focusing on the Stimulus Paradigm and Performance.

作者信息

Li Minglun, He Dianning, Li Chen, Qi Shouliang

机构信息

College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China.

Engineering Research Center of Medical Imaging and Intelligent Analysis, Ministry of Education, Northeastern University, Shenyang 110169, China.

出版信息

Brain Sci. 2021 Apr 1;11(4):450. doi: 10.3390/brainsci11040450.

DOI:10.3390/brainsci11040450
PMID:33916189
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8065759/
Abstract

The steady-state visual evoked potential (SSVEP), measured by the electroencephalograph (EEG), has high rates of information transfer and signal-to-noise ratio, and has been used to construct brain-computer interface (BCI) spellers. In BCI spellers, the targets of alphanumeric characters are assigned different visual stimuli and the fixation of each target generates a unique SSVEP. Matching the SSVEP to the stimulus allows users to select target letters and numbers. Many BCI spellers that harness the SSVEP have been proposed over the past two decades. Various paradigms of visual stimuli, including the procedure of target selection, layout of targets, stimulus encoding, and the combination with other triggering methods are used and considered to influence on the BCI speller performance significantly. This paper reviews these stimulus paradigms and analyzes factors influencing their performance. The fundamentals of BCI spellers are first briefly described. SSVEP-based BCI spellers, where only the SSVEP is used, are classified by stimulus paradigms and described in chronological order. Furthermore, hybrid spellers that involve the use of the SSVEP are presented in parallel. Factors influencing the performance and visual fatigue of BCI spellers are provided. Finally, prevailing challenges and prospective research directions are discussed to promote the development of BCI spellers.

摘要

通过脑电图（EEG）测量的稳态视觉诱发电位（SSVEP）具有较高的信息传输速率和信噪比，已被用于构建脑机接口（BCI）拼写器。在BCI拼写器中，字母数字字符的目标被分配不同的视觉刺激，每个目标的注视会产生独特的SSVEP。将SSVEP与刺激进行匹配可让用户选择目标字母和数字。在过去二十年中，已经提出了许多利用SSVEP的BCI拼写器。使用了各种视觉刺激范式，包括目标选择过程、目标布局、刺激编码以及与其他触发方法的组合，并且认为这些会对BCI拼写器性能产生显著影响。本文回顾了这些刺激范式并分析了影响其性能的因素。首先简要描述BCI拼写器的基本原理。仅使用SSVEP的基于SSVEP的BCI拼写器按刺激范式分类并按时间顺序进行描述。此外，还并行介绍了涉及使用SSVEP的混合拼写器。提供了影响BCI拼写器性能和视觉疲劳的因素。最后，讨论了当前面临的挑战和未来的研究方向，以促进BCI拼写器的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/aec857ab05ab/brainsci-11-00450-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/b9deeae02593/brainsci-11-00450-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/d076ea659723/brainsci-11-00450-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/7befacb07944/brainsci-11-00450-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/c0102a556b3d/brainsci-11-00450-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/3a91772136d1/brainsci-11-00450-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/627cb34a336f/brainsci-11-00450-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/8f363357e885/brainsci-11-00450-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/81ef51d4ab1f/brainsci-11-00450-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/9d22b9a5d1ef/brainsci-11-00450-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/aec857ab05ab/brainsci-11-00450-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/b9deeae02593/brainsci-11-00450-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/c24afca2fbaf/brainsci-11-00450-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/0f1ffd30d5fe/brainsci-11-00450-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/d076ea659723/brainsci-11-00450-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/7befacb07944/brainsci-11-00450-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/c0102a556b3d/brainsci-11-00450-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/3a91772136d1/brainsci-11-00450-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/627cb34a336f/brainsci-11-00450-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/8f363357e885/brainsci-11-00450-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/81ef51d4ab1f/brainsci-11-00450-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/9d22b9a5d1ef/brainsci-11-00450-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99d3/8065759/aec857ab05ab/brainsci-11-00450-g012.jpg

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