Pain Classification

Pain classification research aims to develop objective and accurate methods for assessing pain intensity and type, moving beyond subjective self-reporting. Current efforts focus on applying machine learning, particularly deep learning architectures like convolutional neural networks (CNNs), transformers, and various boosting algorithms, to analyze diverse data sources including physiological signals (e.g., Blood Volume Pulse, electromyography), medical images (e.g., X-rays), and video recordings of facial expressions. These advancements hold significant promise for improving pain management, diagnosis of conditions like osteoarthritis, and potentially reducing reliance on potentially unreliable self-reported pain scales.