One of today’s most propitious immersive technologies isvirtual reality(VR). This term is colloquially associated with headsets that transport users to a bespoke, built-for-purpose immersive 3D virtual environment. It has given rise to the field of immersive analytics—a new field of research that aims to use immersive technologies for enhancing and empowering data analytics. However, in developing such a new set of tools, one has to ask whether the move from standard hardware setup to a fully immersive 3D environment is justified—both in terms of efficiency and development costs. To this end, in this paper, we presentAeroVR—an immersive aerospace design environment with the objective of aiding the component aerodynamic design process by interactively visualizing performance and geometry. We decompose the design of such an environment into function structures, identify the primary and secondary tasks, present an implementation of the system, and verify the interface in terms of usability and expressiveness. We deploy AeroVR on a prototypical design study of a compressor blade for an engine.

Photogrammetry is a promising set of methods for generating photorealistic 3D models of physical objects and structures. Such methods may rely solely on camera-captured photographs or include additional sensor data. Digital twins are digital replicas of physical objects and structures. Photogrammetry is an opportune approach for generating 3D models for the purpose of preparing digital twins. At a sufficiently high level of quality, digital twins provide effective archival representations of physical objects and structures and become effective substitutes for engineering inspections and surveying. While photogrammetric techniques are well-established, insights about effective methods for interacting with such models in virtual reality remain underexplored. We report the results of a qualitative engineering case study in which we asked six domain experts to carry out engineering measurement tasks in an immersive environment using bimanual gestural input coupled with gaze-tracking. The qualitative case study revealed that gaze-supported bimanual interaction of photogrammetric 3D models is a promising modality for domain experts. It allows the experts to efficiently manipulate and measure elements of the 3D model. To better allow designers to support this modality, we report design implications distilled from the feedback from the domain experts.

Multiple Sclerosis (MS) is a chronic, incurable disease of the central nervous system that is also one of the most common causes of disability among young adults. Despite available pharmacological treatments, the patients often require ongoing, supervised rehabilitation. Thus, therapists are constantly searching for new, effective ways of improving functional performance and quality of life without frequently visiting medical centers. One of the most promising methods is remote telerehabilitation enhanced with an immersive augmented reality (AR) interface. Here, we investigated the effectiveness of using a commercially available AR system in MS patients’ treatment. To evaluate such an approach to rehabilitation, we conducted a medical study with 30 MS patients undergoing immunomodulatory treatment. In this study, we evaluated the influence on the patients’ upper limbs’ hand grip strength and efficiency of the patients’ upper limbs. In addition, we also analyzed the level of neurotrophins to assess the potential impact of the training on the brain plasticity process. Our results show that rehabilitation enhanced with AR significantly improves the strength and efficiency of the patients’ upper limbs. Furthermore, we further infer that AR-enhanced systems are a promising possibility of training without leaving home.

We present a refinement of the Immersive Parallel Coordinates Plots (IPCP) system for Virtual Reality (VR). The evolved system provides data-science analytics built around a well-known method for visualization of multidimensional datasets in VR. The data-science analytics enhancements consist of importance analysis and a number of clustering algorithms including a novel SuMC (Subspace Memory Clustering) solution. These analytical methods were applied to both the main visualizations and supporting cross-dimensional scatter plots. They automate part of the analytical work that in the previous version of IPCP had to be done by an expert. We test the refined system with two sample datasets that represent the optimum solutions of two different multi-objective optimization studies in turbomachinery. The first one describes 54 data items with 29 dimensions (DS1), and the second 166 data items with 39 dimensions (DS2). We include the details of these methods as well as the reasoning behind selecting some methods over others.