Suggestions for APA Research and Translational Perspective

This chapter outlines future directions for research and practical applications of automatic pain assessment (APA) in clinical settings. It offers a comprehensive pain glossary which can be useful for non-clinical researchers. For crossing the so-called AI chasm, this chapter emphasizes the need for a multi-modal approach that integrates biosignals, behavioral analysis, and facial expression recognition to address the complexity of pain and variability in patient responses. Collaborative efforts between clinicians, bioengineers, and computer scientists are highlighted as essential for developing more accurate and real-time pain assessment frameworks. A significant focus is placed on improving data quality and integration. Therefore, the principal datasets for pain research are discussed. Additionally, a selection of wearable health monitoring systems and tools for APA are presented. On these bases, this chapter suggests establishing a “gold standard” for data collection to ensure consistency across research settings, which would enhance the clinical applicability of APA methods. Another section proposes a translational framework for integrating APA into clinical practice. This involves creating a comprehensive dashboard that allows clinicians to access multi-dimensional data, helping them make more informed decisions. Since pain is not exclusive to humans, the chapter concludes with a section dedicated to APA in animals and key aspects of translational medicine.