Face-based automatic pain assessment: challenges and perspectives in neonatal intensive care units

Heiderich, Tatiany Marcondes; Carlini, Lucas Pereira; Buzuti, Lucas F.; Balda, Rita de Cássia Xavier; Barros, Marina Carvalho de Moraes; Guinsburg, Ruth; Thomaz, Carlos Eduardo

doi:10.1016/j.jped.2023.05.005

Cited by 4 publications

(1 citation statement)

References 47 publications

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“…Automated pain recognition and monitoring have been widely explored in neonatal populations. Several reviews report on CV developed over the past two decades aimed at the recognition of pain, monitoring, and the measurement of intensity [159,163,171,179]. These feasibility studies and developed models have cumulated into a point-of-care mobile health application for procedural pain named PainChek Infant [172].…”

Section: Detection and Quantification Of Pain Agitation And Level Of ...mentioning

confidence: 99%

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings

Lindroth,

Nalaie,

Raghu

et al. 2024

J. Imaging

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Computer vision (CV), a type of artificial intelligence (AI) that uses digital videos or a sequence of images to recognize content, has been used extensively across industries in recent years. However, in the healthcare industry, its applications are limited by factors like privacy, safety, and ethical concerns. Despite this, CV has the potential to improve patient monitoring, and system efficiencies, while reducing workload. In contrast to previous reviews, we focus on the end-user applications of CV. First, we briefly review and categorize CV applications in other industries (job enhancement, surveillance and monitoring, automation, and augmented reality). We then review the developments of CV in the hospital setting, outpatient, and community settings. The recent advances in monitoring delirium, pain and sedation, patient deterioration, mechanical ventilation, mobility, patient safety, surgical applications, quantification of workload in the hospital, and monitoring for patient events outside the hospital are highlighted. To identify opportunities for future applications, we also completed journey mapping at different system levels. Lastly, we discuss the privacy, safety, and ethical considerations associated with CV and outline processes in algorithm development and testing that limit CV expansion in healthcare. This comprehensive review highlights CV applications and ideas for its expanded use in healthcare.

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Section: Detection and Quantification Of Pain Agitation And Level Of ...mentioning

confidence: 99%

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings

Lindroth,

Nalaie,

Raghu

et al. 2024

J. Imaging

View full text Add to dashboard Cite

show abstract

Pain Assessment in Neonatal Clinical Practice via Facial Expression Analysis and Deep Learning

Bergamasco,

Lattanzi,

Gavelli

et al. 2024

Lecture Notes in Computer Science

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Human vs machine towards neonatal pain assessment: A comprehensive analysis of the facial features extracted by health professionals, parents, and convolutional neural networks

Carlini,

Coutrin,

Ferreira

et al. 2024

Artificial Intelligence in Medicine

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Face-based automatic pain assessment: challenges and perspectives in neonatal intensive care units

Cited by 4 publications

References 47 publications

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings

Pain Assessment in Neonatal Clinical Practice via Facial Expression Analysis and Deep Learning

Human vs machine towards neonatal pain assessment: A comprehensive analysis of the facial features extracted by health professionals, parents, and convolutional neural networks

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