AI Based Acute Pain Detection: Insights Through Facial Expression Analysis Using CNN

Facial expressions can provide critical information about an individual's pain experience, expressing pain and detecting it can be challenging at several times. In this study, we employed efficient computer techniques for recognizing facial expressions corresponding to three different pain levels: little pain, severe pain, and no pain at all. A “Convolutional Neural Network” (CNN) is a type of computer program that we trained to identify certain facial emotions. This required training the computer to identify tiny fluctuations in facial expressions that correspond to various pain levels. This not only helps us in understanding of pain in manifestation but also provides a promising avenue for developing automated pain assessment tools. This work has impacts for healthcare applications as well, as it can lead to more accurate and timely pain management procedures based on objective face analysis.

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Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1109/icses63760.2024.10910760
Citations
2
Primary Topic
Medical Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.37
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article

AI Based Acute Pain Detection: Insights Through Facial Expression Analysis Using CNN

D B Vishwas, M Santhosh, Halemirle Deepak, Diya Dharmendra et al.
2 citations
Medical Imaging and Analysis
0.37
article

AI Based Acute Pain Detection: Insights Through Facial Expression Analysis Using CNN

D B Vishwas, M Santhosh, Halemirle Deepak, Diya Dharmendra, S. Benaka Santhosha
article en
2 citations

Abstract

Facial expressions can provide critical information about an individual's pain experience, expressing pain and detecting it can be challenging at several times. In this study, we employed efficient computer techniques for recognizing facial expressions corresponding to three different pain levels: little pain, severe pain, and no pain at all. A “Convolutional Neural Network” (CNN) is a type of computer program that we trained to identify certain facial emotions. This required training the computer to identify tiny fluctuations in facial expressions that correspond to various pain levels. This not only helps us in understanding of pain in manifestation but also provides a promising avenue for developing automated pain assessment tools. This work has impacts for healthcare applications as well, as it can lead to more accurate and timely pain management procedures based on objective face analysis.

Dayananda Sagar University (IN), Dr. Hari Singh Gour University (IN)
Gender equality
Openalex Percentile: Top 41%
Medical Imaging and Analysis
0.37
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