third Multimodal Sensing Grand Challenge for Next-Gen Pain Assessment (AI4Pain 2026)

AI4PAIN 2026 – Third Multimodal Sensing Grand Challenge for Next-Gen Pain Assessment

Building on the success of the previous AI4PAIN challenges, the Third Multimodal Sensing Grand Challenge for Next-Generation Pain Assessment (AI4PAIN 2026) continues to advance the development of artificial intelligence methods for objective pain evaluation using physiological sensing technologies. While earlier editions focused on pain intensity recognition, the 2026 challenge introduces a new problem centred on the detection and localisation of pain from physiological signals.   

In clinical settings, accurate pain evaluation is essential not only to determine whether a patient is experiencing pain, but also to identify where the pain originates. Pain localisation plays a critical role in diagnosis, treatment selection, and monitoring of neurological and musculoskeletal conditions. However, in many situations, including patients with cognitive impairment, neurological disorders, or limited communication ability, reliable self-report is not available. Objective methods capable of detecting and localising pain could therefore provide valuable support for clinical decision-making.  

Physiological sensing offers a promising pathway toward this goal, as nociceptive stimulation produces measurable changes in autonomic and cardiovascular activity. The AI4PAIN 2026 challenge focuses on the analysis of physiological recordings, including Electrodermal Activity (EDA), Blood Volume Pulse (BVP), Respiratory (RESP), and Peripheral Oxygen Saturation (SpO₂), which provide objective information about the body’s physiological response to painful stimulation. 

Participants will be provided with a curated dataset together with predefined training, validation, and test partitions, enabling fair and reproducible comparison of machine learning approaches. The challenge encourages the development of robust and interpretable models capable of extracting meaningful information from physiological signals, with potential applications in digital health, clinical monitoring, and human-centred sensing technologies.   

By providing a common benchmark and evaluation framework, AI4PAIN 2026 aims to stimulate innovation at the intersection of artificial intelligence, biomedical sensing, and healthcare, and to advance the development of objective tools for next-generation pain assessment.  

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

History

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

Second AI4PAIN Grand Challenge, at ICMI 2025, Canberra, Australia. [AI4Pain 2025]