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[脑机接口:从实验室到真实场景]

[Brain-computer interface: from lab to real scene].

作者信息

Yao Dezhong

机构信息

School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, P.R.China.

Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu 611731, P.R.China.

出版信息

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Jun 25;38(3):405-408. doi: 10.7507/1001-5515.202105091.

DOI:10.7507/1001-5515.202105091
PMID:34180184
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9927763/
Abstract

Brain-computer interface (BCI) can be summarized as a system that uses online brain information to realize communication between brain and computer. BCI has experienced nearly half a century of development, although it now has a high degree of awareness in the public, but the application of BCI in the actual scene is still very limited. This collection invited some BCI teams in China to report their efforts to promote BCI from laboratory to real scene. This paper summarizes the main contents of the invited papers, and looks forward to the future of BCI.

摘要

脑机接口(BCI)可以概括为一种利用在线脑信息来实现脑与计算机之间通信的系统。脑机接口已经经历了近半个世纪的发展,尽管它现在在公众中具有较高的认知度,但脑机接口在实际场景中的应用仍然非常有限。本论文集邀请了中国的一些脑机接口团队来汇报他们为推动脑机接口从实验室走向实际场景所做的努力。本文总结了受邀论文的主要内容,并展望了脑机接口的未来。

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1
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本文引用的文献

1
[Bacomics--a new discipline integrating brain and the outside].[脑外整合学——一门融合大脑与外界的新学科]
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Jun 25;38(3):507-511. doi: 10.7507/1001-5515.202101039.
2
[An electroencephalogram-based study of resting-state spectrogram and attention in tinnitus patients].[基于脑电图的耳鸣患者静息态频谱图与注意力研究]
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Jun 25;38(3):492-497. doi: 10.7507/1001-5515.202012015.
3
[Robotic arm control system based on augmented reality brain-computer interface and computer vision].基于增强现实脑机接口和计算机视觉的机器人手臂控制系统
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Jun 25;38(3):483-491. doi: 10.7507/1001-5515.202011039.
4
[Using electroencephalogram for emotion recognition based on filter-bank long short-term memory networks].基于滤波器组长短期记忆网络的脑电图情感识别方法
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Jun 25;38(3):447-454. doi: 10.7507/1001-5515.202012054.
5
[Execution, assessment and improvement methods of motor imagery for brain-computer interface].[脑机接口运动想象的执行、评估与改进方法]
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Jun 25;38(3):434-446. doi: 10.7507/1001-5515.202101037.
6
[Research on feature classification of lower limb motion imagination based on electrical stimulation to enhance rehabilitation].基于电刺激增强康复的下肢运动想象特征分类研究
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Jun 25;38(3):425-433. doi: 10.7507/1001-5515.202007004.
7
[Research on performance of motor-imagery-based brain-computer interface in different complexity of Chinese character patterns].基于运动想象的脑机接口在中国汉字图案不同复杂度下的性能研究
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Jun 25;38(3):417-424. doi: 10.7507/1001-5515.202010031.
8
[Research progress and prospect of collaborative brain-computer interface for group brain collaboration].用于群体脑协作的协同脑机接口研究进展与展望
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Jun 25;38(3):409-416. doi: 10.7507/1001-5515.202007059.
9
High-performance brain-to-text communication via handwriting.通过手写实现高性能的脑-文本通信。
Nature. 2021 May;593(7858):249-254. doi: 10.1038/s41586-021-03506-2. Epub 2021 May 12.
10
Enhancement of Event-Related Desynchronization in Motor Imagery Based on Transcranial Electrical Stimulation.基于经颅电刺激增强运动想象中事件相关去同步化
Front Hum Neurosci. 2021 Mar 18;15:635351. doi: 10.3389/fnhum.2021.635351. eCollection 2021.