We present a Virtual Reality (VR) game, PlayMeBack, to investigate cognitive load measurement in interactive VR environments using pupil dilation, Galvanic Skin Response (GSR), Electroencephalogram (EEG) and Heart Rate (HR). The user is shown different patterns of tiles lighting up and is asked to replay the pattern back pressing the tiles in the same sequence they lit up. The task difficulty depends on the length of the observed pattern (3-6 keys). This task is designed to explore the effect of cognitive load on physiological cues, and if pupil dilation, EEG, GSR and HR can be used as measures of cognitive load.

Virtual Reality (VR) is effective in various training scenarios across multiple domains, such as education, health and defense. However, most of those applications are not adaptive to the real-time cognitive or subjectively experienced load placed on the trainee. In this paper, we explore a cognitively adaptive training system based on real-time measurement of task related alpha activity in the brain. This measurement was made by a 32-channel mobile Electroencephalography (EEG) system, and was used to adapt the task difficulty to an ideal level which challenged our participants, and thus theoretically induces the best level of performance gains as a result of training. Our system required participants to select target objects in VR and the complexity of the task adapted to the alpha activity in the brain. A total of 14 participants undertook our training and completed 20 levels of increasing complexity. Our study identified significant differences in brain activity in response to increasing levels of task complexity, but response time did not alter as a function of task difficulty. Collectively, we interpret this to indicate the brain's ability to compensate for higher task load without affecting behaviourally measured visuomotor performance.

Sleep deprivation is known to have serious deleterious effects on executive functioning and job performance. Augmented reality has an ability to place pertinent information at the fore, guiding visual focus and reducing instructional complexity. This paper presents a study to explore how spatial augmented reality instructions impact procedural task performance on sleep deprived users. The user study was conducted to examine performance on a procedural task at six time points over the course of a night of total sleep deprivation. Tasks were provided either by spatial augmented reality-based projections or on an adjacent monitor. The results indicate that participant errors significantly increased with the monitor condition when sleep deprived. The augmented reality condition exhibited a positive influence with participant errors and completion time having no significant increase when sleep deprived. The results of our study show that spatial augmented reality is an effective sleep deprivation countermeasure under laboratory conditions.