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We describe a mixed reality environment that has been designed as an aid for training driving skills for a powered wheelchair. Our motivation is to provide an improvement on a previous virtual reality wheelchair driving simulator, with a particular aim to remove any cybersickness effects. The results of a validation test are presented that involved 35 able bodied volunteers divided into three groups: mixed reality trained, virtual reality trained, and a control group. No significant differences in improvement was found between the groups but there is a notable trend that both the mixed reality and virtual reality groups improved more than the control group. Whereas the virtual reality group experienced discomfort (as measured using a simulator sickness questionnaire), the mixed reality group experienced no side effects.

We present ongoing work to develop a virtual reality environment for the cognitive rehabilitation of patients as a part of their recovery from a stroke. A stroke causes damage to the brain and problem solving, memory and task sequencing are commonly affected. The brain can recover to some extent, however, and stroke patients have to relearn to carry out activities of daily learning. We have created an application called VIRTUE to enable such activities to be practiced using immersive virtual reality. Gamification techniques enhance the motivation of patients such as by making the level of difficulty of a task increase over time. The design and implementation of VIRTUE is presented together with the results of a small acceptability study.

We developed an application that makes indoor modelling accessible by utilizing consumer grade technology in the form of Apple's ARKit and a smartphone to assist with serious games level design. We compared our system to that of a tape measure and a system based on an infra-red depth sensor and application. We evaluated the accuracy and efficiency of each system over four different measuring tasks of increasing complexity. Our results suggest that our application is more accurate than the depth sensor system and as accurate and more time efficient as the tape measure over several tasks. Participants also showed a preference to our LevelEd AR application over the depth sensor system regarding usability.