Abstract
Since their early developments a few decades ago, Brain-Computer Interfaces have mainly been used as means to assist disabled users to perform daily interaction. Recently, a new trend emerged for using BCIs as interaction media for the general public, with particularly promising applications from the field of passive BCIs. Passive BCIs aim at sensing the users’ mental states to enable an adaptive interaction. Current Augmented and Virtual Reality systems often provide generic experiences with no adaptation of the content nor the interaction techniques to the users’ mental states, even though this adaptation would help improve the usability of these systems in several application fields (education, entertainment, rehabilitation…).
A major objective of the next generation of Virtual and Augmented Reality systems is to be able to adapt to the user online by integrating neurophysiological insights to improve their usability and user experience (UX) through the use of Brain-Computer Interfaces (BCI)
Even though AR/VR systems may initially be designed with UX in mind through processes that were established for desktop and mobile touch interfaces, their true usability can only be established post-hoc in controlled experiments through qualitative methods and semi-structured interviews. Unlike in desktop and mobile applications, AR/VR users cannot be easily interrupted during use due to the immersiveness AR/VR provide, which limits UX evaluation in AR/VR to subjective questionnaires presented before and after interaction. This approach cannot measure how UX changes throughout use, and it cannot capture the nuances of usability perception during the various stages of an AR/VR application. While presenting UX questionnaires during interruption is an alternative, this process interrupts the user and more severely breaks their sense of presence in the immersive environment, which is the ultimate goal AR/VR applications pursue. A new approach would therefore be to quantitatively and continuously evaluate the user experience in AR/VR scenarios through the continuous neurophysiological measurements that complement AR/VR interaction, which can pave the way to adaptive systems that adjust virtual content and interaction techniques to the users’ mental states and establishing a framework for such adaptive interfaces.