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Published in: Neural Computing and Applications 14/2022

07-01-2021 | S.I. : Healthcare Analytics

Global research on artificial intelligence-enhanced human electroencephalogram analysis

Authors: Xieling Chen, Xiaohui Tao, Fu Lee Wang, Haoran Xie

Published in: Neural Computing and Applications | Issue 14/2022

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Abstract

The application of artificial intelligence (AI) technologies in assisting human electroencephalogram (EEG) analysis has become an active scientific field. This study aims to present a comprehensive review of the research field of AI-enhanced human EEG analysis. Using bibliometrics and topic modeling, research articles concerning AI-enhanced human EEG analysis collected from the Web of Science database during the period 2009–2018 were analyzed. After examining 2053 research articles published around the world, it was found that the annual number of articles had significantly grown from 78 to 468, with the USA and China being the most influential and prolific. The results of the keyword analysis showed that “electroencephalogram,” “brain–computer interface,” “classification,” “support vector machine,” “electroencephalography,” and “signal” were the most frequently used. The results of topic modeling and evolution analyses highlighted several important issues, including epileptic seizure detection, brainmachine interface, EEG classification, mental disorders, emotion, and alcoholism and anesthesia. The findings suggest that such visualization and analysis of the research articles could provide a comprehensive overview of the field for communities of practice and inquiry worldwide.

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Appendix
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Metadata
Title
Global research on artificial intelligence-enhanced human electroencephalogram analysis
Authors
Xieling Chen
Xiaohui Tao
Fu Lee Wang
Haoran Xie
Publication date
07-01-2021
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 14/2022
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-020-05588-x

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