Building a taxonomy for evidence-based medical eXtended Reality (MXR) applications: identifying best practices for design innovation and global collaboration
Aims: This article aims to create a taxonomy of evidence-based medical eXtended Reality (MXR) applications, including Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), and 360-degree photo/video technologies, to identify best practices for designing and evaluating user experiences and interfaces (UX/UI). The goal is to assist researchers, developers, and practitioners in comparing and extrapolating the best solutions for high-precision MXR tools in medical and wellness contexts. Methods: To develop the taxonomy, a review of medical and MXR publications was conducted, followed by three systematic mapping studies. Applications were categorized by end-users and purposes. The first mapping cross-referenced digital health technology classifications. The second validated the structure by incorporating over 350 evidence-based MXR apps, with input from twenty XR-HCI researchers. The third, ongoing mapping adds emerging apps, refining the taxonomy further. Results: The taxonomy is presented in a dynamic database and 3D interactive graph, allowing international researchers to visualize and discuss developed evidence-based medical and wellness XR applications. This formalizes prior efforts to distinguish validated MXR solutions from speculative ones. Conclusion: The taxonomy focuses solely on evidence-based applications, highlighting areas where VR, AR, and MR have been successfully implemented. It serves as a tool for stakeholders to analyze and understand best practices in MXR design, promoting the development of safe, effective, and user-friendly medical and wellness applications.
Authors
- Jolanda G. Tromp
- Chung Văn Lê (ORCID: https://orcid.org/0000-0001-9849-3226)
- Pezhman Raeisian Parvari
Publication Details
- Journal
- Empathic Computing
- Published
- 2024-12-06
- DOI
- https://doi.org/10.70401/ec.2025.0002
- Citations
- 1
- Primary Topic
- Augmented Reality Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.25
Funders
- Medical Device Innovation Center