An automated ICU agitation monitoring system for video streaming using deep learning classification

An automated ICU agitation monitoring system for video streaming using deep learning classification

Abstract Objective To address the challenge of assessing sedation status in critically ill patients in the intensive care unit (ICU), we aimed to develop a non-contact automatic classifier of agitation using artificial intelligence and deep learning. Methods We collected the video recordings of ICU...

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Bibliographic Details
Main Authors: Pei-Yu Dai, Yu-Cheng Wu, Ruey-Kai Sheu, Chieh-Liang Wu, Shu-Fang Liu, Pei-Yi Lin, Wei-Lin Cheng, Guan-Yin Lin, Huang-Chien Chung, Lun-Chi Chen
Format: Article
Language:English
Published: BMC 2024-03-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Motion detection
Deep learning
Video streaming data
ICU
RASS
Online Access:https://doi.org/10.1186/s12911-024-02479-2

Internet

https://doi.org/10.1186/s12911-024-02479-2

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