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Using AI to Detect Pain through Facial Expressions: A Review

Pain assessment is a complex task largely dependent on the patient’s self-report. Artificial intelligence (AI) has emerged as a promising tool for automating and objectifying pain assessment through the identification of pain-related facial expressions. However, the capabilities and potential of AI...

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Autores principales: De Sario, Gioacchino D., Haider, Clifton R., Maita, Karla C., Torres-Guzman, Ricardo A., Emam, Omar S., Avila, Francisco R., Garcia, John P., Borna, Sahar, McLeod, Christopher J., Bruce, Charles J., Carter, Rickey E., Forte, Antonio J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10215219/
https://www.ncbi.nlm.nih.gov/pubmed/37237618
http://dx.doi.org/10.3390/bioengineering10050548
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author De Sario, Gioacchino D.
Haider, Clifton R.
Maita, Karla C.
Torres-Guzman, Ricardo A.
Emam, Omar S.
Avila, Francisco R.
Garcia, John P.
Borna, Sahar
McLeod, Christopher J.
Bruce, Charles J.
Carter, Rickey E.
Forte, Antonio J.
author_facet De Sario, Gioacchino D.
Haider, Clifton R.
Maita, Karla C.
Torres-Guzman, Ricardo A.
Emam, Omar S.
Avila, Francisco R.
Garcia, John P.
Borna, Sahar
McLeod, Christopher J.
Bruce, Charles J.
Carter, Rickey E.
Forte, Antonio J.
author_sort De Sario, Gioacchino D.
collection PubMed
description Pain assessment is a complex task largely dependent on the patient’s self-report. Artificial intelligence (AI) has emerged as a promising tool for automating and objectifying pain assessment through the identification of pain-related facial expressions. However, the capabilities and potential of AI in clinical settings are still largely unknown to many medical professionals. In this literature review, we present a conceptual understanding of the application of AI to detect pain through facial expressions. We provide an overview of the current state of the art as well as the technical foundations of AI/ML techniques used in pain detection. We highlight the ethical challenges and the limitations associated with the use of AI in pain detection, such as the scarcity of databases, confounding factors, and medical conditions that affect the shape and mobility of the face. The review also highlights the potential impact of AI on pain assessment in clinical practice and lays the groundwork for further study in this area.
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spelling pubmed-102152192023-05-27 Using AI to Detect Pain through Facial Expressions: A Review De Sario, Gioacchino D. Haider, Clifton R. Maita, Karla C. Torres-Guzman, Ricardo A. Emam, Omar S. Avila, Francisco R. Garcia, John P. Borna, Sahar McLeod, Christopher J. Bruce, Charles J. Carter, Rickey E. Forte, Antonio J. Bioengineering (Basel) Review Pain assessment is a complex task largely dependent on the patient’s self-report. Artificial intelligence (AI) has emerged as a promising tool for automating and objectifying pain assessment through the identification of pain-related facial expressions. However, the capabilities and potential of AI in clinical settings are still largely unknown to many medical professionals. In this literature review, we present a conceptual understanding of the application of AI to detect pain through facial expressions. We provide an overview of the current state of the art as well as the technical foundations of AI/ML techniques used in pain detection. We highlight the ethical challenges and the limitations associated with the use of AI in pain detection, such as the scarcity of databases, confounding factors, and medical conditions that affect the shape and mobility of the face. The review also highlights the potential impact of AI on pain assessment in clinical practice and lays the groundwork for further study in this area. MDPI 2023-05-02 /pmc/articles/PMC10215219/ /pubmed/37237618 http://dx.doi.org/10.3390/bioengineering10050548 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
De Sario, Gioacchino D.
Haider, Clifton R.
Maita, Karla C.
Torres-Guzman, Ricardo A.
Emam, Omar S.
Avila, Francisco R.
Garcia, John P.
Borna, Sahar
McLeod, Christopher J.
Bruce, Charles J.
Carter, Rickey E.
Forte, Antonio J.
Using AI to Detect Pain through Facial Expressions: A Review
title Using AI to Detect Pain through Facial Expressions: A Review
title_full Using AI to Detect Pain through Facial Expressions: A Review
title_fullStr Using AI to Detect Pain through Facial Expressions: A Review
title_full_unstemmed Using AI to Detect Pain through Facial Expressions: A Review
title_short Using AI to Detect Pain through Facial Expressions: A Review
title_sort using ai to detect pain through facial expressions: a review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10215219/
https://www.ncbi.nlm.nih.gov/pubmed/37237618
http://dx.doi.org/10.3390/bioengineering10050548
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