Tangible and Collaborative Augmented Reality for Supporting Understanding of Axial Spondyloarthritis

: (Alternative Format Thesis)

Abstract

The effective management of axial spondyloarthritis (axSpA) is underpinned by patients and clinicians building a shared and complete understanding of the patient's health. Particularly in recent years, building this understanding has been supported by advancements in digital health technologies, such as self-management tools and online educational content. Despite this, many challenges still remain for patients and clinicians in presenting and understanding data relating to their health, contributing to the two-way knowledge gap that exists between patients and clinician.

Part of this knowledge gap lies in patients understanding the anatomical structures and disease processes associated with axSpA. This understanding is important for patients in making more informed decisions about the treatment and management of their conditions, and in understanding symptoms. Typically, patients rely on paper-based or online learning material to engage with these concepts, however these are often limited in their interactivity and representation of 3D anatomy. Immersive technologies, such as augmented reality (AR), have been shown to provide significant benefits for anatomical education by enabling users to visualise and interact with 3D anatomical models in highly engaging and immersive experiences. While previous work has shown the benefits of AR for anatomical education, most systems do not utilise the tactile and interactive benefits of physical anatomical model, and it is unclear whether these offer significant learning benefits.

Our research explores the potential of tangible and collaborative AR for supporting patients in understanding the anatomy and disease processes relating to axSpA. We first conducted interviews with patients and clinicians to understand current challenges and opportunities within the axSpA care pathway, and to explore the role of data visualisations in supporting patient education. Based on these interviews, we chose to explore how the use of AR, combined with physical models, could support the delivery of anatomical education. We then conducted an observational study, exploring how pairs of users utilise physical models to collaboratively explore data visualisations in AR. We then developed a tangible AR system for learning spinal anatomy and axSpA progression, and conducted a comparative study to evaluate the learning benefits of physical models. Finally, we conducted an expert qualitative analysis with clinicians to explore the use of tangible AR systems in clinical practice. Our work contributes patient and clinician perspectives on current axSpA care processes, insights into collaborative behaviours in tangible AR, an evaluation of tangible AR for anatomical education, and insights into opportunities and challenges for the use of tangible AR for anatomical education in clinical practice.

Date of Award	20 May 2026
Original language	English
Awarding Institution	University of Bath
Supervisor	Jason Alexander (Supervisor), Dario Cazzola (Supervisor) & Simon Jones (Supervisor)