Deep learning model for detection of pain intensity from facial expression

Jeffrey Soar, Ghazal Bargshady, Xujuan Zhou, Frank Whittaker

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

10 Citations (Scopus)

Abstract

Many people who are suffering from a chronic pain face periods of acute pain and resulting problems during their illness and adequate reporting of symptoms is necessary for treatment. Some patients have difficulties in adequately alerting caregivers to their pain or describing the intensity which can impact on effective treatment. Pain and its intensity can be noticeable in ones face. Movements in facial muscles can depict ones current emotional state. Machine learning algorithms can detect pain intensity from facial expressions. The algorithm can extract and classify facial expression of pain among patients. In this paper, we propose a new deep learning model for detection of pain intensity from facial expressions. This automatic pain detection system may help clinicians to detect pain and its intensity in patients and by doing this healthcare organizations may have access to more complete and more regular information of patients regarding their pain.

Original languageEnglish
Title of host publicationSmart Homes and Health Telematics, Designing a Better Future
Subtitle of host publicationUrban Assisted Living - 16th International Conference, ICOST 2018, Proceedings
EditorsMounir Mokhtari, Bessam Abdulrazak, Hamdi Aloulou
Place of PublicationSwitzerland
PublisherSpringer
Pages249-254
Number of pages6
ISBN (Electronic)9783319945231
ISBN (Print)9783319945224
DOIs
Publication statusPublished - 2018
Externally publishedYes
Event16th International Conference on Smart homes, Assistive Technologies and Health Telematics, ICOST 2018 - Singapore, Singapore
Duration: 10 Jul 201812 Jul 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10898 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Smart homes, Assistive Technologies and Health Telematics, ICOST 2018
Country/TerritorySingapore
CitySingapore
Period10/07/1812/07/18

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