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结合稳态视觉诱发电位的多模态脑机接口研究进展
引用本文:迟新一,崔红岩,陈小刚. 结合稳态视觉诱发电位的多模态脑机接口研究进展[J]. 中国生物医学工程学报, 2022, 41(2): 204-213. DOI: 10.3969/j.issn.0258-8021.2022.02.009
作者姓名:迟新一  崔红岩  陈小刚
作者单位:(中国医学科学院 北京协和医学院 生物医学工程研究所,天津 300192)
基金项目:国家自然科学基金(62171473);;天津市自然科学基金(18JCYBJC29600);;中央高校基本科研业务费(3332019015);
摘    要:脑机接口(BCI)能够在大脑与外部环境之间建立一种不依赖于外周神经或肌肉的交流与控制通道,有助于恢复运动障碍者的生活自理能力,是当前神经工程领域最活跃的研究方向之一。其中,稳态视觉诱发电位(SSVEP)脑机接口因信息传输率(ITR)高、所需训练少而备受关注。现有的无创高通讯速率脑机接口系统主要是来自于或基于SSVEP。近年来,为进一步提高脑机接口性能,整合SSVEP与其他类型输入信号的多模态脑机接口逐渐成为脑机接口研究的新趋势。从输入信号类型、实验范式和信号融合等方面,综述结合SSVEP 的多模态脑机接口研究进展,帮助相关研究者理解该领域研究动态,以启发高通讯速率脑机接口系统的设计与实现。同时探讨目前结合SSVEP的多模态脑机接口存在的问题和未来可能的发展趋势,以期推动结合SSVEP的多模态脑机接口技术的发展。

关 键 词:脑机接口  稳态视觉诱发电位  多模态脑机接口  脑电  
收稿时间:2021-04-15

Advances in Multi-Modal Brain-Computer Interface Combined with Steady-State Visual Evoked Potential
Chi Xinyi,Cui Hongyan,Chen Xiaogang. Advances in Multi-Modal Brain-Computer Interface Combined with Steady-State Visual Evoked Potential[J]. Chinese Journal of Biomedical Engineering, 2022, 41(2): 204-213. DOI: 10.3969/j.issn.0258-8021.2022.02.009
Authors:Chi Xinyi  Cui Hongyan  Chen Xiaogang
Affiliation:(Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical Collage, Tianjin 300192, China)
Abstract:Brain-computer interface (BCI) is one of the most active research directions in the field of neural engineering, which can establish a communication and control pathway between the brain and the external environment independent of peripheral nerves or muscles and is helpful to restore the self-care ability of people with movement disorders. Steady-state visual evoked potential BCI attracts great attention for the high information transfer rate and less requirements of training. The existing non-invasive high speed BCI is mainly from or based on SSVEP. In recent years, multi-modal BCI integrateing SSVEP and other input signals has become a new trend in BCI research for further improvement of BCI performance. This paper reviewed advances of multi-modal BCI combined with SSVEP from several aspects, including the type of input signals, fusion of experimental paradigm and signal, aiming to help readers understand the research trends in this field and inspire the design and implementation of high communication rate BCI system. Meanwhile, existing problems and possible development trends in the future were discussed to promote the development of multi-modal BCI combined with SSVEP.
Keywords:brain-computer interface  steady-state visual evoked potential  multi-modal brain-computer interface  EEG  
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