Pain Assessment

Pain assessment research focuses on developing objective, reliable methods to measure pain intensity and presence, particularly in populations unable to self-report. Current efforts leverage advanced machine learning, employing deep learning architectures like transformers, convolutional neural networks (CNNs), and Vision-MLPs, often trained on synthetic or augmented datasets to address data scarcity and ethical concerns related to real patient data. These models analyze various data modalities, including facial video, thermal imaging, and physiological signals like blood volume pulse, aiming to improve pain management and reduce reliance on subjective reporting. The ultimate goal is to create accurate, unbiased, and personalized pain assessment tools for improved clinical decision-making.