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Abstract
A crucial part of clinical care is pain evaluation, but traditional approaches mostly rely on subjective self-reporting, which may be incorrect or impractical for patients who are nonverbal or mentally impaired. This work introduces an AI-powered facial recognition tool for pain assessment that uses facial expression analysis to deliver an objective, non-invasive, and real-time assessment of pain. To detect and measure pain, the system combines cutting-edge technologies including computer vision, deep learning, and facial landmark detection. To capture both spatial and temporal aspects of facial expressions, a hybrid model that combines convolutional neural networks (CNN), long short-term memory (LSTM), and attention mechanisms is used. Image collection, pre-processing, facial feature extraction, and categorization of pain severity into predetermined groups are all part of the methodology.
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