Pain typically is measured by patient self-report, but self-reported pain is difficult to interpret and may be impaired or in some circumstances not possible to obtain. For instance, in patients with restricted verbal abilities such as neonates, young children, and in patients with certain neurological or psychiatric impairments (e.g., dementia). Additionally, the subjectively experienced pain may be partly or even completely unrelated to the somatic pathology of tissue damage and other disorders. Therefore, the standard self-assessment of pain does not always allow for an objective and reliable assessment of the quality and intensity of pain. Given individual differences among patients, their families, and healthcare providers, pain often is poorly assessed, underestimated, and inadequately treated. To improve assessment of pain, objective, valid, and efficient assessment of the onset, intensity, and pattern of occurrence of pain is necessary. To address these needs, several efforts are being made in machine learning and computer vision community for automatic and objective assessment of pain from video as a powerful alternative to self-reported pain. The workshop aims to bring together interdisciplinary researchers working in field of automatic multimodal assessment of pain (using video, audio, and physiological signals). A key focus of the workshop is the translation of laboratory work into clinical practice.

Aims

The workshop aims to bring together interdisciplinary researchers working in field of automatic multimodal assessment of pain (using video and physiological signals). A key focus of the workshop is the translation of laboratory work into clinical practice. Topics of interest include, but are not limited to:

• • Multimodal assessment of pain intensity from video or wearable motion sensors (e.g., face, head, body,)

  • Multimodal assessment of pain intensity from physiological signals

  • Multimodal assessment of pain intensity from functional near-infrared spectroscopy

  • Movement based detection of pain

  • Clinically relevant chronic and acute pain corpora recording and annotation for infants, adults, and adults with restricted communication

  • New approaches to and consideration on labelling pain-related datasets

  • Applications of technology for pain and related states recognition

  • New conceptual approaches, critique and ethical considerations to the design and use of AI for pain inferences

Important dates

Deadline for workshop paper submission: July 1st, 2026 (extended)

Decisions released to authors:  July 23th, 2026

Deadline for camera-ready submission: August 1st, 2026

Workshop date: October 5, 2026

Prior AAP Workshops:

• Camberra, Australia (2025)

• Glasgow, UK (2024)

• Paris, France (2023)

• Montreal, Canada (2021)

• Buenos Aires, Argentina (2020)