Multimodal AI Approaches for Pain Assessment

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are transforming pain assessment and prediction by offering objective, data-driven alternatives to traditional self-reported methods. This chapter explores multimodal AI approaches that integrate facial expression recognition, speech pattern analysis, and wearable biosensors to assess and monitor pain in real-time. Natural Language Processing (NLP) is also employed to extract pain descriptors from clinical narratives and unstructured health records. In addition, ML models enable the prediction of pain onset and severity, facilitating personalized treatment planning and proactive intervention. While these technologies offer substantial benefits, challenges such as data bias, privacy concerns, and integration into clinical workflows remain. Future directions include explainable AI, brain imaging integration, and the development of virtual health assistants to enhance the accuracy and equity of AI-driven pain care.

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