Imagine you are facing a mirror, seeing at the same time both your real body and a virtual display of your brain in activity and perfectly superimposed to your real image “inside your real skull”. In this paper, we introduce a novel augmented reality paradigm called “Mind-Mirror” which enables the experience of seeing “through your own head”, visualizing your brain “in action and in situ”. Our approach relies on the use of a semi-transparent mirror positioned in front of a computer screen. A virtual brain is displayed on screen and automatically follows the head movements using an optical face-tracking system. The brain activity is extracted and processed in real-time with the help of an electroencephalography cap (EEG) worn by the user. A rear view is also proposed thanks to an additional webcam recording the rear of the user's head. The use of EEG classification techniques enables to test a Neurofeedback scenario in which the user can train and progressively learn how to control different mental states, such as “concentrated” versus “relaxed”. The results of a user study comparing a standard visualization used in Neurofeedback to our approach showed that the Mind-Mirror could be successfully used and that the participants have particularly appreciated its innovation and originality. We believe that, in addition to applications in Neurofeedback and Brain-Computer Interfaces, the Mind-Mirror could also be used as a novel visualization tool for education, training or entertainment applications.

Brain-Computer Interfaces (BCI) introduce a novel way of interacting with real and virtual environments by directly exploiting cerebral activity. However in most setups using a BCI, the user is explicitly asked to remain as motionless as possible, since muscular activity is commonly admitted to add noise and artifacts in brain electrical signals. Thus, as for today, people have been rarely let using other classical input devices such as mice or joysticks simultaneously to a BCI-based interaction. In this paper, we present an experimental study on the influence of manipulating an input device such as a standard computer mouse on the performance of a BCI system. We have designed a 2-class BCI which relies on Alpha brainwaves to discriminate between focused versus relaxed mental activities. The study uses a simple virtual environment inspired by the well-known Pac-Man videogame and based on BCI and mouse controls. The control of mental activity enables to eat pellets in a simple 2D virtual maze. Different levels of motor activity achieved with the mouse are progressively introduced in the gameplay: 1) no motor activity (control condition), 2) a semi-automatic motor activity, and 3) a highly-demanding motor activity. As expected the BCI performance was found to slightly decrease in presence of motor activity. However, we found that the BCI could still be successfully used in all conditions, and that relaxed versus focused mental activities could still be significantly discriminated even in presence of a highly-demanding mouse manipulation. These promising results pave the way to future experimental studies with more complex mental and motor activities, but also to novel 3D interaction paradigms that could mix BCI and other input devices for virtual reality and videogame applications.