In this project the popular video game "Portal2" (by Valve Corporation) is controlled with a hybrid brain-computer interface (BCI). Steady state visually evoked potentials (SSVEP) and forearm Electromyography (EMG) are used as signal sources to play a complete level of the popular first-person puzzle game.
The movement commands 'walk forward', 'walk backward', 'turn left', 'turn right', 'look up', 'look down' and 'jump' are controlled by the forearm EMG. The actions 'shoot portal orange', 'shoot portal blue' and 'pick up cube' are performed by focusing on the SSVEP stimuli.
Brain-computer interface (BCI) systems are not often used as input devices for modern games, due largely to their low bandwidth. However, BCIs can become a useful input modality when adapting the dynamics of the brain-game interaction, as well as combining them with devices based on other physiological signal to make BCIs more powerful and flexible.
Context dependence, dwell timers and other intelligent software tools were implemented in a new system to control the Massive Multiplayer Online Role Playing Game World of Warcraft (by Blizzard, Inc.) with the Graz-BCI.
Topographical disorientation (TD) is a severe and persistent impairment of spatial orientation and navigation in familiar as well as new environments and a common consequence of brain damage. Virtual reality (VR) provides a new tool for the assessment and rehabilitation of TD.
In this study a VR-based verbally-guided passive navigation training program was used to improve general spatial abilities in neurologic patients with spatial disorientation. Read full paper.
In this project the creation of a real-world based VR environment was key for implementing this research. Xcessity provided the 3D models of the campus of the university of technology Graz, Austria. In only 4 weeks of time the area was modeled and textured with photos taken from the real environment.
In 3D graphics surface models of objects are mostly represented by polygonal meshes. The ability to switch between several levels of details is essential to provide an appropriately sized input for all kinds of further processing steps. The simplification of those polygonal meshes can be carried out by already existing applications, which, however, were not created for medical imaging purposes. Most of them cannot be used for reducing meshes of medical 3D models. In this project we are pointing out the features necessary for dealing with meshes in the context of medical imaging.
Our main goal is to find a combination of simplification components and control mechanisms, which ensure that the topology, as well as the geometry, is preserved in a reduced version of a 3D model. The combination of error quadrics with a directed edge data structure defines the basis for our simplification tool. In order to keep the triangle meshes manifold, we have applied some completely new techniques for half edge meshes, vertex sets, border stitching and a solution for merging borders.
