The present study investigated depth perception in virtual environments. Twenty-three participants verbally estimated ten distances between 40 cm and 500 cm in three different virtual environments in two conditions: (1) only one target was presented or (2) ten targets were presented at the same time. Additionally, the presence of a metric aid was varied. A questionnaire assessed subjective ratings about physical complaints (e.g., headache), the experience in the virtual world (e.g., presence), and the experiment itself (self-evaluation of the estimations). Results show that participants underestimate the virtual distances but are able to perceive the distances in the right metric order even when only very simple virtual environments are presented. Furthermore, interindividual differences and intraindividual stabilities can be found among participants, and neither the three different virtual environments nor the metric aid improved depth estimations. Estimation performance is better in peripersonal than in extrapersonal space. In contrast, subjective ratings provide a preferred space: a closed room with visible floor, ceiling, and walls.
While the ecological validity of virtual reality (VR) applications is usually assessed by behavioral data or interrogation, an alternative approach on a neuronal level is offered by brain imaging methods. Because it is yet unclear if 3D space in virtual environments is processed analogically to the real world, we conducted a study investigating virtual spatial processing in the brain using functional magnetic resonance imaging (fMRI). Results show differences in VR spatial brain processing as compared to known brain activations in reality. Identifying differences and commonalities of brain processing in VR reveals limitations and holds important implications for VR therapy and training tools. When VR therapy aims at the rehabilitation of brain function and activity, differences in brain processing have to be taken into account for designing effective VR training tools. Furthermore, for an evaluation of possible restoration effects caused by VR training, it is necessary to integrate information about the brain activation networks elicited by the training. The present study provides an example for demonstrating the benefit of fMRI as an evaluation tool for the mental processes involved in virtual environments.
Ventricular Assist Devices (VADs) support the heart in its vital task of maintaining circulation in the human body when the heart alone is not able to maintain a sufficient flow rate due to illness or degenerative diseases. However, the engineering of these devices is a highly demanding task. Advanced modeling methods and computer simulations allow the investigation of the fluid flow inside such a device and in particular of potential blood damage. In this paper we present a set of visualization methods which have been designed to specifically support the analysis of a tensor-based blood damage prediction model. This model is based on the tracing of particles through the VAD, for each of which the cumulative blood damage can be computed. The model's tensor output approximates a single blood cell's deformation in the flow field. The tensor and derived scalar data are subsequently visualized using techniques based on icons, particle visualization, and function plotting. All these techniques are accessible through a Virtual Reality-based user interface, which features not only stereoscopic rendering but also natural interaction with the complex three-dimensional data. To illustrate the effectiveness of these visualization methods, we present the results of an analysis session that was performed by domain experts for a specific data set for the MicroMed DeBakey VAD.
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