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Review Article | Open Access

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

Wenchang Zhang1,2( ), Chuanqi Tan2, Fuchun Sun2, Hang Wu1, Bo Zhang2
Institute of Medical Support Technology, Academy of Military Sciences, Tianjin 300161, China
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, Beijing 100084, China
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Abstract

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.

Keywords

BCIEEGMISSVEPP300

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Brain Science Advances
Volume 4 Issue 2,
December 2018
Pages 156-167
DOI: 10.26599/BSA.2018.9050010

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Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

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Cite this article:
Zhang W, Tan C, Sun F, et al. A review of EEG-based brain-computer interface systems design. Brain Science Advances, 2018, 4(2): 156-167. https://doi.org/10.26599/BSA.2018.9050010

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Received: 18 November 2018
Revised: 20 December 2018
Accepted: 31 December 2018
Published: 02 April 2019
© The authors 2018

This article is published with open access at journals.sagepub.com/home/BSA

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/ en-us/nam/open-access-at-sage).