A review of EEG-based brain-computer interface systems design

被引：6

作者：

Wenchang Zhang ^{[1
,2
]}

Chuanqi Tan ^{[2
]}

Fuchun Sun ^{[2
]}

Hang Wu ^{[1
]}

Bo Zhang ^{[2
]}

机构：

[1] Institute of Medical Support Technology, Academy of Military Sciences

[2] State Key Lab.of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, the Department of Computer Science and Technology, Tsinghua University

来源：

Brain Science Advances | 2018年 / 4卷 / 02期

关键词：

BCI; EEG; MI; SSVEP; P300;

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：

A brain-computer interface(BCI) system can recognize the mental activities pattern by computer algorithms to control the external devices. Electroencephalogram(EEG) is one of the most common used approach for BCI due to the convenience and non-invasive implement. Therefore, more and more BCIs have been designed for the disabled people that suffer from stroke or spinal cord injury to help them for rehabilitation and life. We introduce the common BCI paradigms, the signal processing, and feature extraction methods. Then, we survey the different combined modes of hybrids BCIs and review the design of the synchronous/asynchronous BCIs.Finally, the shared control methods are discussed.

引用

页码：156 / 167

页数：12

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