Advances in Hybrid Brain-Computer Interfaces: Principles, Design, and Applications

Joint Authors

Li, Zina
Zhang, Shuqing
Pan, Jiahui

Source

Computational Intelligence and Neuroscience

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-10-08

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Biology

Abstract EN

Conventional brain-computer interface (BCI) systems have been facing two fundamental challenges: the lack of high detection performance and the control command problem.

To this end, the researchers have proposed a hybrid brain-computer interface (hBCI) to address these challenges.

This paper mainly discusses the research progress of hBCI and reviews three types of hBCI, namely, hBCI based on multiple brain models, multisensory hBCI, and hBCI based on multimodal signals.

By analyzing the general principles, paradigm designs, experimental results, advantages, and applications of the latest hBCI system, we found that using hBCI technology can improve the detection performance of BCI and achieve multidegree/multifunctional control, which is significantly superior to single-mode BCIs.

American Psychological Association (APA)

Li, Zina& Zhang, Shuqing& Pan, Jiahui. 2019. Advances in Hybrid Brain-Computer Interfaces: Principles, Design, and Applications. Computational Intelligence and Neuroscience،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1129432

Modern Language Association (MLA)

Li, Zina…[et al.]. Advances in Hybrid Brain-Computer Interfaces: Principles, Design, and Applications. Computational Intelligence and Neuroscience No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1129432

American Medical Association (AMA)

Li, Zina& Zhang, Shuqing& Pan, Jiahui. Advances in Hybrid Brain-Computer Interfaces: Principles, Design, and Applications. Computational Intelligence and Neuroscience. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1129432

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1129432