Second Multimodal Sensing Grand Challenge for Next-Gen Pain Assessment (AI4Pain 2025)

Second Multimodal Sensing Grand Challenge for Next-Gen Pain Assessment (AI4PAIN 2025)

Building on the success of the first AI4PAIN challenge, the Second Multimodal Sensing Grand Challenge for Next-Gen Pain Assessment (AI4PAIN 2025) continues to push the boundaries of AI-driven pain assessment by focusing on the classification of physiological signals. This year, the challenge aims to advance the development of machine learning models that leverage Electrodermal Activity (EDA), Blood Volume Pulse (BVP), Respiratory (RESP), and Peripheral Oxygen Saturation (SpO₂) signals for automated pain detection.  

Pain assessment remains a critical challenge in healthcare, as it is inherently subjective and difficult to quantify. Traditional self-report methods, while widely used, are limited by patient communication barriers and variability in pain perception. The integration of multimodal physiological sensing and artificial intelligence (AI) offers a promising avenue for developing objective pain assessment tools that can enhance clinical decision-making and improve patient care. 

The AI4PAIN 2025 challenge provides participants with access to a curated dataset, standardised evaluation metrics, and a competitive platform to benchmark AI models. Participants will be encouraged to explore novel deep learning architectures, signal processing techniques, feature engineering approaches, and interpretability methods to enhance model performance and clinical applicability.  

This competition is an opportunity to collaborate, innovate, and contribute to the future of digital health. We invite researchers, data scientists, and AI practitioners to join us in advancing the field of pain assessment and shaping next-generation healthcare solutions. 

We look forward to seeing the creative and impactful contributions from the research community. 

History

First AI4PAIN Grand Challenge was organised at ACII 2024, Glasgow. [AI4Pain 2024]