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J-GLOBAL ID：202102210595019471   Reference number：21A2572651

Deep Learning in Physiological Signal Data: A Survey

生理学的信号データにおける深層学習:調査【JST・京大機械翻訳】

Author (4)： Rim Beanbonyka (Department of Computer Science, Soonchunhyang University, Asan 31538, Korea) ,  Sung Nak-Jun (Department of Computer Science, Soonchunhyang University, Asan 31538, Korea) ,  Min Sedong (Department of Medical IT Engineering, Soonchunhyang University, Asan 31538, Korea) ,  Hong Min (Department of Computer Software Engineering, Soonchunhyang University, Asan 31538, Korea)
Material： Sensors (Web)
Volume： 20  Issue： 4  Page： 969  Publication year： 2020 
JST Material Number： U7015A  ISSN： 1424-8220  CODEN： SENSC9  Document type： Article
Article type： 文献レビュー  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： Deep Learning (DL), a successf...

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Thesaurus term： *learning ,  electroencephalogram ,  electrocardiogram ,  electromyogram ,  two dimension ,  one dimension ,  computer architecture ,  machine learning
Semi thesaurus term： モダリティ ,  システム性能 ,  医用画像解析 ,  生理信号 ,  *深層学習 , 【Automatic Indexing@JST】

Author keywords (4)： deep-learning ,  machine learning ,  physiological signals ,  1D signal data analysis

JST classification (2)： Biometry  (EL03020C) ,  Artificial intelligence  (JE08000Z)

Reference (154)：

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• Ganapathy, N.; Swaminathan, R.; Deserno, T.M. Deep learning on 1-D biosignals: A taxonomy-based survey. Yearbook Med. Inf. 2018, 27, 98-109.
• Zhang, D.; Yao, L.; Chen, K.; Wang, S.; Chang, X.; Liu, Y. Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition. IEEE Trans. Cybern. 2019, 1-12.
• PubMed. Available online: https://www.ncbi.nlm.nih.gov/pubmed/ (accessed on 31 October 2019).

Terms in the title (3)： 生理学的信号 ,  深層学習 ,  調査