Using AI to Detect Pain through Facial Expressions: A Review

Gioacchino D. De Sario, Clifton R. Haider, Karla C. Maita, Ricardo A. Torres-Guzman, Omar S. Emam, Francisco R. Avila, John P. Garcia, Sahar Borna, Christopher J. McLeod, Charles J. Bruce, Rickey E. Carter, Antonio J. Forte

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish (US)
Article number548
JournalBioengineering
Volume10
Issue number5
DOIs
StatePublished - May 2023

Keywords

  • AI
  • artificial intelligence
  • facial expression
  • machine learning
  • pain

ASJC Scopus subject areas

  • Bioengineering

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