Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/71895
Title: Pain detection using deep learning with evaluation system
Authors: Kornprom Pikulkaew
Ekkarat Boonchieng
Waraporn Boonchieng
Varin Chouvatut
Keywords: Computer Science
Engineering
Issue Date: 1-Jan-2021
Abstract: © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. Recent evidence has appeared that major enhancements in patient results can be increased by the periodical observing patient pain levels by medical staff in hospitals. Nevertheless, owing to the responsibility and pressure that the staffs have, this kind of observation has been complicated to withstand; thus, a system that works automatically could be the solution. Using an automatic facial expression system to detect pain which pain can be defined via several facial action units (AUs). To simplify pain detection using deep learning, data were collected from the UNBC database, which contains sequences of images that show participants’ faces while they were doing an arrangement of movement-of-motion tests. To improve pain detection using facial expressions, this research proposes a pain detection technique that uses deep learning. Finally, the resulting of the experiment will be compared with the self-reports, and doctors will be asked to evaluate the system.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85091919743&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/71895
ISSN: 21945365
21945357
Appears in Collections:CMUL: Journal Articles

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