Use of Multiple EEG Features and Artificial Neural Network to Monitor the Depth of Anesthesia.

Gu, Yue; Liang, Zhenhu; Hagihira, Satoshi

Gu, Yue; Liang, Zhenhu; Hagihira, Satoshi.

Affiliation

Gu Y; Key Laboratory of Computer Vision and System (Ministry of Education), School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China. guyue@email.tjut.edu.cn.
Liang Z; Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China. zhl@ysu.edu.cn.
Hagihira S; Department of Anesthesiology, Graduate School of Medicine, Osaka University, Osaka 565-0871, Japan. hagihira@anes.med.osaka-u.ac.jp.

Sensors (Basel) ; 19(11)2019 May 31.

Article in En | MEDLINE | ID: mdl-31159263

Subject(s)

Anesthesia/methods; Electroencephalography/methods; Monitoring, Physiologic/methods; Neural Networks, Computer; Adolescent; Adult; Algorithms; Consciousness Monitors; Entropy; Female; Humans; Male; Middle Aged; Propofol/therapeutic use; Young Adult

Key words

artificial neural network; bispectral index; depth of anesthesia; electroencephalogram

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neural Networks, Computer / Electroencephalography / Anesthesia / Monitoring, Physiologic Limits: Adolescent / Adult / Female / Humans / Male / Middle aged Language: En Journal: Sensors (Basel) Year: 2019 Document type: Article Affiliation country: China Country of publication: Switzerland

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