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...

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Vydané v:Journal of neural engineering Ročník 18; číslo 3
Hlavní autori: Zhang, Xiang, Yao, Lina, Wang, Xianzhi, Monaghan, Jessica, McAlpine, David, Zhang, Yu
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: England 01.06.2021
Predmet:
Algorithms
Brain
Brain-Computer Interfaces
Deep Learning
Electroencephalography - methods
Humans
brain signals
brain–computer interface
survey
deep learning algorithms
ISSN:1741-2552, 1741-2552
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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.
Bibliografia:ObjectType-Article-1
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ObjectType-Review-3
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ISSN:1741-2552
1741-2552
DOI:10.1088/1741-2552/abc902