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OpenViBE2 : Designing and Testing Brain-Computer Interfaces in Videogames
Summary
OpenViBE2 project is testing the use of Brain-Computer Interfaces technology in videogames and virtual worlds.
OpenViBE2 is a collaborative project funded by ANR (French National Research Agency). It aims at studying the automatic adaptation of the content and interaction with virtual environments (VE) based on the user’s mental states, as measured from scalp-EEG signals, with a special focus on videogame applications. Being “consumer world” oriented, the project faces several difficult challenges: robustness, preserving user’s comfort, and adaptability to a large number of users with their own EEG signature, etc.
As compared to previous BCI approaches (e.g., previous OpenViBE1 project), our goal is to use EEG signals not only as a direct input for mental command, but also as complementary means to adapt the interaction protocol and the content of the virtual world. Thus, a main challenging objective is to combine brain-computer interaction with usual mouse or gamepad motor interaction within the same set-up. To sum up, OpenViBE2 covers 3 major innovative aspects: (1) the complex and challenging videogame context; (2) the possibility for the user to keep using other interaction devices such as joysticks, gamepads, etc; and (3) the development of real-time techniques adapting VE interaction and content from mental state measures.
Project Description
Brain-Computer Interaction (BCI) corresponds to the use of brain signals to send “mental commands” to an automated system such as a robot or a simulation. In the previous OpenViBE1 project (2005-2009), we have developed an open-source software called OpenViBE to easily design, test and use BCI. In addition, we have opened new research areas in the field of BCI, EEG signal-processing and in Virtual Reality (VR) technologies supporting BCI applications. BCI is a rapidly growing area of research and several impressive prototypes are already available. However, nowadays, BCI control capabilities are still not comparable to other Human-Computer Interaction (HCI) peripherals such as joysticks or the classical computer mouse. Thus, BCI technologies remain focused on disabled people, who do not have access to the other traditional interfaces.
The objective of OpenViBE2 is to propose a radical shift of perspective about the use of BCI. First, in OpenViBE2 we consider the possibility to merge a BCI with traditional peripherals such as joysticks, mice and other devices, all being possibly used simultaneously in a virtual environment. Therefore, BCI is not seen as a replacement but as a complement of classical HCI. Second, we aim at monitoring brain cognitive functions and mental states of the user in order to adapt, in real-time and in an automated fashion, the interaction protocol itself as well as the content of the remote/virtual environment (VE).
Our project focuses on videogames and “serious games”, which are relatively new fields of application for BCI and span a potentially massive market. The goal of OpenViBE2 is thus: “exploiting EEG information to measure, identify and use the mental states and brain responses of the user to adapt both the way the user can interact with the videogame and the content of the game”.
The OpenViBE2 project raises several technical challenges and scientific questions that can be unfolded along three main research axes: (1) at a neurophysiological/electrophysiological level, the experimental validation of EEG markers usable in a videogame context, (2) at a technological level concerning the on-line processing of EEG data, the design of efficient and adapted signal-processing techniques, and (3) at a technological level concerning the human-computer interaction, the design of novel and efficient adaptive techniques for virtual environments based on on-line brain features extraction.
The successful achievement of this research is expected to produce novel knowledge, methods, tools and techniques for the adaptation of content and interaction with videogames and virtual environments using user’s mental states and brain responses. Throughout the project, we offer to deliver an open-source platform that will integrate our advances in the field of real-time EEG signal-processing.
