Project Elements: A computational entity-component-system in a scene-graph pythonic framework, for a neural, geometric computer graphics curriculum

We present the Elements project, a computational science and computer graphics (CG) framework, that offers for the first time the advantages of an Entity-Component-System (ECS) along with the rapid prototyping convenience of a Scenegraph-based pythonic framework. This novelty allows advances in the teaching of CG: from heterogeneous directed acyclic graphs and depth-first traversals, to animation, skinning, geometric algebra and shader-based components rendered via unique systems all the way to their representation as graph neural networks for 3D scientific visualization. Taking advantage of the unique ECS in a a Scenegraph underlying system, this project aims to bridge CG curricula and modern game engines, that are based on the same approach but often present these notions in a black-box approach. It is designed to actively utilize software design patterns, under an extensible open-source approach. Although Elements provides a modern, simple to program pythonic approach with Jupyter notebooks and unit-tests, its CG pipeline is not black-box, exposing for teaching for the first time unique challenging scientific, visual and neural computing concepts.Comment: 8 pages, 8 figures, 2 listings, submitted to EuroGraphics 2023 education trac

A True AR Authoring Tool for Interactive Virtual Museums

In this work, a new and innovative way of spatial computing that appeared recently in the bibliography called True Augmented Reality (AR), is employed in cultural heritage preservation. This innovation could be adapted by the Virtual Museums of the future to enhance the quality of experience. It emphasises, the fact that a visitor will not be able to tell, at a first glance, if the artefact that he/she is looking at is real or not and it is expected to draw the visitors' interest. True AR is not limited to artefacts but extends even to buildings or life-sized character simulations of statues. It provides the best visual quality possible so that the users will not be able to tell the real objects from the augmented ones. Such applications can be beneficial for future museums, as with True AR, 3D models of various exhibits, monuments, statues, characters and buildings can be reconstructed and presented to the visitors in a realistic and innovative way. We also propose our Virtual Reality Sample application, a True AR playground featuring basic components and tools for generating interactive Virtual Museum applications, alongside a 3D reconstructed character (the priest of Asinou church) facilitating the storyteller of the augmented experience.Comment: This is a preprint of a chapter for a planned book that was initiated by "Visual Computing in Cultural Heritage" and that is expected to be published by Springer. The final book chapter will differ from this preprin

MAGES 4.0: Accelerating the world's transition to medical VR training

In this work, we propose MAGES 4.0, a novel Software Development Kit (SDK) to accelerate the creation of collaborative medical training scenarios in VR/AR. Our solution offers a versatile authoring platform for developers to create medical simulations in a future-proof, low-code environment. MAGES breaks the boundaries between realities since students can collaborate using virtual and augmented reality devices at the same medical scene. With MAGES we provide a solution to the 150-year-old training model which is unable to meet the level of healthcare professionals needed. Our platform incorporates, among others, the following novel advancements: a) 5G edge-cloud remote rendering and physics dissection, b) realistic real-time simulation of organic tissues as soft-bodies, c) a highly realistic cutting and tearing algorithm, d) neural network assessment for user profiling and, e) a VR recorder to record and replay or resume the training simulation from any perspective

A Digital Health Intervention for Stress and Anxiety Relief in Perioperative Care: Protocol for a Feasibility Randomized Controlled Trial

BackgroundStress and anxiety are psychophysiological responses commonly experienced by patients during the perioperative process that can increase presurgical and postsurgical complications to a comprehensive and positive recovery. Preventing and intervening in stress and anxiety can help patients achieve positive health and well-being outcomes. Similarly, the provision of education about surgery can be a crucial component and is inversely correlated with preoperative anxiety levels. However, few patients receive stress and anxiety relief support before surgery, and resource constraints make face-to-face education sessions untenable. Digital health interventions can be helpful in empowering patients and enhancing a more positive experience. Digital health interventions have been shown to help patients feel informed about the possible benefits and risks of available treatment options. However, they currently focus only on providing informative content, neglecting the importance of personalization and patient empowerment. ObjectiveThis study aimed to explore the feasibility of a digital health intervention called the Adhera CARINAE Digital Health Program, designed to provide evidence-based, personalized stress- and anxiety-management methods enabled by a comprehensive digital ecosystem that incorporates wearable, mobile, and virtual reality technologies. The intervention program includes the use of advanced data-driven techniques for tailored patient education and lifestyle support. MethodsThe trial will include 5 hospitals across 3 European countries and will use a randomized controlled design including 30 intervention participants and 30 control group participants. The involved surgeries are cardiopulmonary and coronary artery bypass surgeries, cardiac valve replacement, prostate or bladder cancer surgeries, hip and knee replacement, maxillofacial surgery, or scoliosis. The control group will receive standard care, and the intervention group will additionally be exposed to the digital health intervention program. ResultsThe recruitment process started in January 2022 and has been completed. The primary impact analysis is currently ongoing. The expected results will be published in early 2023. ConclusionsThis manuscript details a comprehensive protocol for a study that will provide valuable information about the intervention program, such as the measurement of comparative intervention effects on stress; anxiety and pain management; and usability by patients, caregivers, and health care professionals. This will contribute to the evidence planning process for the future adoption of diverse digital health solutions in the field of surgery. Trial RegistrationClinicalTrials.gov NCT05184725; https://www.clinicaltrials.gov/ct2/show/NCT05184725 International Registered Report Identifier (IRRID)DERR1-10.2196/3853

VRADA training system as a non-pharmacological dual intervention to alleviate symptoms of the pathophysiology of Mild Cognitive Impairment

In this study, a VR system called VRADA (VR Exercise App for Dementia and Alzheimer's Patients) was designed for physical and cognitive training forindividuals with Mild Cognitive Impairment (MCI). The inflammatory factors IL-1β and TNF-α, Alzheimer's disease (AD) hallmarks total tau, p181-tau, Αβ42 and Aβ40, the ratio of Aβ42/40 and p181-tau/Aβ42 were assessed on the blood serum of patients diagnosed with MCI to determine the effect of VRADA training. No significant differences were verified in the levels of inflammatory markers after the end of the study, however IL-1β levels of the VRADA group were significantly lower than those of the control group, at the follow-up of the study. Also, patients following VRADA intervention presented significantly higher Αβ42/Αβ40 ratio, and lower levels of Αβ42, of total tau, p-tau181, and of the crucial ratio p-tau181/Αβ42, in comparison with patients of the Control group. These results are promising for the further employment of the VRADA training during early dementia, and hopefully for halting the progression to AD