A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers

Brain signals refer to the biometric information collected from the human brain. The research on brain signals aims to discover the underlying neurological or physical status of the individuals by signal decoding. The emerging deep learning techniques have improved the study of brain signals signifi...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Journal of neural engineering Ročník 18; číslo 3
Hlavní autoři: Zhang, Xiang, Yao, Lina, Wang, Xianzhi, Monaghan, Jessica, McAlpine, David, Zhang, Yu
Médium: Journal Article
Jazyk:angličtina
Vydáno: England 01.06.2021
Témata:
Algorithms
Brain
Brain-Computer Interfaces
Deep Learning
Electroencephalography - methods
Humans
brain signals
brain–computer interface
survey
deep learning algorithms
ISSN:1741-2552, 1741-2552
On-line přístup:Zjistit podrobnosti o přístupu
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Brain signals refer to the biometric information collected from the human brain. The research on brain signals aims to discover the underlying neurological or physical status of the individuals by signal decoding. The emerging deep learning techniques have improved the study of brain signals significantly in recent years. In this work, we first present a taxonomy of non-invasive brain signals and the basics of deep learning algorithms. Then, we provide the frontiers of applying deep learning for non-invasive brain signals analysis, by summarizing a large number of recent publications. Moreover, upon the deep learning-powered brain signal studies, we report the potential real-world applications which benefit not only disabled people but also normal individuals. Finally, we discuss the opening challenges and future directions.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
ObjectType-Review-3
content type line 23
ISSN:1741-2552
1741-2552
DOI:10.1088/1741-2552/abc902