Clinical trials
Randomised controlled trials, feasibility studies, and clinical interventions conducted by independent research institutions using the MAGES platform.
Clinical trial examining the combined effect of VR-based physical and cognitive training on inflammation markers and Alzheimer’s biomarkers including amyloid beta and tau proteins in MCI patients.
Randomised controlled trial comparing VR training against video instruction for medical students performing THA. Assessed implantation accuracy and time to competency.
Explores VR simulation as a competency-based assessment tool at Western Governors University, moving beyond form-based measures to problem-solving and clinical reasoning.
Evaluates the VRADA VR system for combined physical and cognitive training in MCI patients, assessing impact on inflammatory markers and Alzheimer’s disease biomarkers.
Development and usability evaluation of a VR simulation for resuscitative endovascular balloon occlusion of the aorta — a rare, high-stakes trauma procedure.
Describes the algorithms, models, and architecture of a medical XR simulation for COVID-19 swab testing and PPE training, based on a world-standard hygiene protocol.
RCT protocol for a digital health VR intervention targeting stress and anxiety management in surgical patients, addressing a key factor in perioperative outcomes.
Mixed-methods feasibility study evaluating a VR app combining physical and cognitive training for older adults with MCI. Assessed usability, engagement, and early clinical indicators.
Prospective randomised pilot trial demonstrating VR simulation effectively trained healthcare personnel in COVID-19 swab testing and PPE protocols during the pandemic.
Blinded RCT demonstrating that VR simulation significantly improved PGY-1 orthopaedic residents’ performance in cadaveric total hip arthroplasty. Preferential benefit on specific surgical technique components.
Case studies
From university hospitals to medical schools to specialist training centres — MAGES is in active use at institutions across three continents.
Advanced approaches for comprehensive analysis and enhancement of cardiac arrest resuscitation training for emergency medicine and nursing teams.
Nasopharyngeal swab training, hand hygiene, and PPE protocols delivered via immersive VR simulation at one of Switzerland’s leading university hospitals.
The first hospital-based Department of Virtual Medicine, using MAGES to develop and run extended reality OSCE simulations for clinical examination training.
Connecting four reputable medical schools in a networked collaborative VR surgical training environment — a first for medical education at this scale.
The largest ever interactive abdominal anatomy and surgery collection of XR simulations — an in-depth first-person exploration of topographical anatomy from the inside out.
Cognitive training and skill-based scoring simulations for soft skills in a collaborative online environment, supporting WGU’s competency-based learning model.
Deployment of MAGES simulations across Sofmedica’s network of medical institutions in Southeast Europe. Full case study available.
Published research
The most recent publications from the ORamaVR team -- spanning robotic simulation, team-based VR training, computational medical XR, and platform research.
Validation pilot study of a fully immersive VR simulator for robotic surgical training. Evaluates skill transfer, usability, and clinical validity of the ERMIS platform for robotic procedure education.
Presents iREACT, a non-linear team-based VR training system for cardiac arrest resuscitation incorporating crew resource management (CRM) tools for emergency teams.
Demonstrates how geometric algebra and large language models can be combined to enable instruction-based 3D transformations in interactive medical simulation scenes.
A course paper introducing the CMXR discipline — the intersection of computational medicine, XR technology, and AI for next-generation healthcare training and clinical applications.
Technical research article published through AIP Publishing, advancing the scientific foundations of the MAGES platform and medical XR simulation methodology.
Presents an edge-computing approach to XR application deployment using a Docker registry architecture, enabling scalable and low-latency delivery of medical XR simulations.
Introduces a digital twin VR environment for robotic surgical training, enabling realistic practice of robotic-assisted procedures with accurate instrument simulation and performance feedback.
Randomised controlled trial comparing VR training effectiveness against video instruction for medical students performing total hip arthroplasty. Assessed implantation accuracy and time to competency.
Showing 8 of 65+ peer-reviewed publications. Full bibliography available on request.
View all publications →In their own words
“We have worked with ORamaVR and our residents absolutely love training with the platform. This has really been good for our training — I am really trying to interest all my colleagues and training centers that this is necessary for them to make their residents better.”
“This was magnificent, it was really like live surgery. It is very easy to use — I would definitely promote it.”
“VR is the future of medical education and we are pushing further the limits with ORamaVR and MAGES SDK.”
“Quite a fascinating teaching tool. It allows us to take residents through the case step by step without a cadaver or a book — a medium that they understand and can appreciate.”
“Very nice experience and it will be very fruitful for young surgeons. It’s a great tool and helpful for the training.”
“MAGES SDK has streamlined our pipeline incredibly. The development and feedback loop has been so tight that in about one month we had a full-blown teaching tool.”
“Thanks to its high-quality toolset and capabilities, the MAGES SDK has allowed us to create and author simulations in a very time and resource efficient manner.”
“MAGES SDK allowed us to create VR content with minimal effort.”
“Train anywhere, any time. Minimal equipment required for simulating the whole robotic experience.”
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