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The role of eye movement signals in non-invasive brain-computer interface typing system
Liu, Xi1,2,3; Hu, Bingliang1,3; Si, Yang4,5; Wang, Quan1,3
作者部门光谱成像技术研究室
2024
发表期刊Medical and Biological Engineering and Computing
ISSN01400118;17410444
产权排序1
摘要

Brain-Computer Interfaces (BCIs) have shown great potential in providing communication and control for individuals with severe motor disabilities. However, traditional BCIs that rely on electroencephalography (EEG) signals suffer from low information transfer rates and high variability across users. Recently, eye movement signals have emerged as a promising alternative due to their high accuracy and robustness. Eye movement signals are the electrical or mechanical signals generated by the movements and behaviors of the eyes, serving to denote the diverse forms of eye movements, such as fixations, smooth pursuit, and other oculomotor activities like blinking. This article presents a review of recent studies on the development of BCI typing systems that incorporate eye movement signals. We first discuss the basic principles of BCI and the recent advancements in text entry. Then, we provide a comprehensive summary of the latest advancements in BCI typing systems that leverage eye movement signals. This includes an in-depth analysis of hybrid BCIs that are built upon the integration of electrooculography (EOG) and eye tracking technology, aiming to enhance the performance and functionality of the system. Moreover, we highlight the advantages and limitations of different approaches, as well as potential future directions. Overall, eye movement signals hold great potential for enhancing the usability and accessibility of BCI typing systems, and further research in this area could lead to more effective communication and control for individuals with motor disabilities. Graphical Abstract: This article delves into three pivotal components of the BCI typing system: data, algorithms, and interaction. The system leverages eye movement and EEG data as inputs, which are processed through algorithms for data fusion, feature extraction, and classification to yield output results. Furthermore, it facilitates real-time interaction by providing visual feedback via an efficient user interface. (Figure presented.). © International Federation for Medical and Biological Engineering 2024.

关键词Brain-computer interface Speller EEG Eye movement Text input
DOI10.1007/s11517-024-03070-7
收录类别EI
语种英语
EI入藏号20241215789908
引用统计
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/97294
专题光谱成像技术研究室
通讯作者Wang, Quan
作者单位1.Key Laboratory of Spectral Imaging Technology, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an; 710119, China;
2.University of Chinese Academy of Sciences, Beijing; 100049, China;
3.Key Laboratory of Biomedical Spectroscopy of Xi’an, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an; 710119, China;
4.Department of Neurology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, Chengdu; 611731, China;
5.University of Electronic Science and Technology of China, Chengdu; 611731, China
推荐引用方式
GB/T 7714
Liu, Xi,Hu, Bingliang,Si, Yang,et al. The role of eye movement signals in non-invasive brain-computer interface typing system[J]. Medical and Biological Engineering and Computing,2024.
APA Liu, Xi,Hu, Bingliang,Si, Yang,&Wang, Quan.(2024).The role of eye movement signals in non-invasive brain-computer interface typing system.Medical and Biological Engineering and Computing.
MLA Liu, Xi,et al."The role of eye movement signals in non-invasive brain-computer interface typing system".Medical and Biological Engineering and Computing (2024).
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