Survey of deep learning based EEG data analysis technology

被引：0
作者：
Zhong B. [1 ]
Wang P. [1 ]
Wang Y. [1 ]
Wang X. [1 ]
机构：
[1] School of Computer Science and Technology, East China Normal University, Shanghai
来源：
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2024年 / 58卷 / 05期
关键词：
closed-loop process; deep learning; electroencephalography (EEG); feature extraction; model generalization; preprocessing;
D O I：
10.3785/j.issn.1008-973X.2024.05.001
中图分类号：
学科分类号：
摘要：
A thorough analysis and cross-comparison of recent relevant works was provided, outlining a closed-loop process for EEG data analysis based on deep learning. EEG data were introduced, and the application of deep learning in three key stages: preprocessing, feature extraction, and model generalization was unfolded. The research ideas and solutions provided by deep learning algorithms in the respective stages were delineated, including the challenges and issues encountered at each stage. The main contributions and limitations of different algorithms were comprehensively summarized. The challenges faced and future directions of deep learning technology in handling EEG data at each stage were discussed. © 2024 Zhejiang University. All rights reserved.
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页码：879 / 890
页数：11
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