Machine learning methods on BioVid heat pain database for pain intensity estimation.

ABSTRACT: Pain assessment is a critical aspect of medical practice, directly influencing patient treatment and quality of life. Traditional pain evaluation methods, such as the Numerical Rating Scale (NRS), Visual Analog Scale (VAS), and Verbal Rating Scale (VRS), are subjective and often unreliable, especially for non-verbal, unconscious, or cognitively impaired patients. This study introduces an objective pain measurement model using advanced machine learning techniques, specifically, Convolutional Neural Networks (CNNs), and Vision Transformers (ViTs), to analyze facial expressions. We compared the performance of CNNs, VGG16, Convolutional Vision Transformer (CvT), and MobileViT, in classifying pain intensity based on facial images captured during peak pain and no-pain moments. The models were tr

SUBMITTER: Pittara M 

PROVIDER: S-EPMC12578783 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature