In this paper we review classification algorithms used to design brain-computer interface (BCI) systems based on electroencephalography (EEG). We briefly present the commonly employed algorithms and describe their critical properties. Based on the literature, we compare them in terms of performance and provide guidelines to choose the suitable classification algorithm(s) for a specific BCI.

1 This paper describes the OpenViBE software platform which enables to design, test and use Brain-Computer Interfaces. Brain-Computer Interfaces (BCI) are communication systems that enable users to send commands to computers only by means of brain activity. BCI are gaining interest among the Virtual Reality (VR) community since they have appeared as promising interaction devices for Virtual Environments (VE). The key features of the platform are 1) a high modularity, 2) embedded tools for visualization and feedback based on VR and 3D displays, 3) BCI design made available to non-programmers thanks to visual programming and 4) various tools offered to the different types of users. The platform features are illustrated in this paper with two entertaining VR applications based on a BCI. In the first one, users can move a virtual ball by imagining hand movements, while in the second one, they can control a virtual spaceship using real or imagined foot movements. Online experiments with these applications together with the evaluation of the platform computational performances showed its suitability for the design of VR applications controlled with a BCI. OpenViBE is a free software distributed under an open-source license.

8Major challenges must be tackled for brain-computer interfaces to mature into an established communications medium for VR applications, which will range from basic neuroscience studies to developing optimal peripherals and mental gamepads and more efficient brain-signal processing techniques.

International audienceHow do people appropriate their virtual hand representation when interacting in virtual environments? In order to answer this question , we conducted an experiment studying the sense of embodiment when interacting with three different virtual hand representations , each one providing a different degree of visual realism but keeping the same control mechanism. The main experimental task was a Pick-and-Place task in which participants had to grasp a virtual cube and place it to an indicated position while avoiding an obstacle (brick, barbed wire or fire). An additional task was considered in which participants had to perform a potentially dangerous operation towards their virtual hand: place their virtual hand close to a virtual spinning saw. Both qualitative measures and questionnaire data were gathered in order to assess the sense of agency and ownership towards each virtual hand. Results show that the sense of agency is stronger for less realistic virtual hands which also provide less mismatch between the participant's actions and the animation of the virtual hand. In contrast, the sense of ownership is increased for the human virtual hand which provides a direct mapping between the degrees of freedom of the real and virtual hand

This paper considers whether a passive isometric input device, such as a ¢ ¤ £ ¦ ¥ § © ¥ TM , used together with visual feedback, could provide the operator with a pseudo-haptic feedback. For this aim, two psychophysical experiments have been conducted. The first experiment consisted of a compliance discrimination, between two virtual springs hand-operated by means of the ¢ ¤ £ ¥ § © ¥ TM. In this experiment, the stiffness (or compliance) JND turned out to be 6%. The second experiment assessed stiffness discrimination between a virtual spring and the equivalent spring in reality. In this case, the stiffness (or compliance) JND was found to be 13.4%. These results are consistent with previous outcomes on manual discrimination of compliance. Consequently, this consistency reveals that the passive apparatus that was used can, to some extent, simulate haptic information. In addition, a final test indicated that the proprioceptive sense of the subjects was blurred by visual feedback. This gave them the illusion of using a non isometric device.

How can we connect two brains to a video game by means of a BCI, and what will happen when we do so? How will the two users behave, and how will they perceive this novel common experience? In this paper we are concerned with the design and evaluation of multiuser BCI applications. We created a multiuser videogame called "BrainArena" in which two users can play a simple football game by means of two BCIs. They can score goals on the left or right side of the screen by simply imagining left or right hand movements. To add another interesting element, the gamers can play in a collaborative manner (their two mental activities are combined to score in the same goal), or in a competitive manner (the gamers must push the ball in opposite directions). Two experiments were conducted to evaluate the performance and subjective experience of users in the different conditions. In the first experiment we compared single-user situation with one multiuser situation: the collaborative task. Experiment 1 showed that multiuser conditions are significantly preferred in terms of fun and motivation compared to the single-user condition. The performance of some users was even significantly improved in the multiuser condition. A subset of well-performing subjects was involved in the second experiment, where we added the competitive task. Experiment 2 suggested that competitive and collaborative conditions may lead to similar performances and motivations. However the corresponding gaming experiences can be perceived differently among the participants. Taken together our results suggest that multiuser BCI applications can be operational, effective, and more engaging for participants.

This paper presents a survey of the main results obtained in the field of “pseudo-haptic feedback”: a technique meant to simulate haptic sensations in virtual environments using visual feedback and properties of human visuo-haptic perception. Pseudo-haptic feedback uses vision to distort haptic perception and verges on haptic illusions. Pseudo-haptic feedback has been used to simulate various haptic properties such as the stiffness of a virtual spring, the texture of an image, or the mass of a virtual object. This paper describes the several experiments in which these haptic properties were simulated. It assesses the definition and the properties of pseudo-haptic feedback. It also describes several virtual reality applications in which pseudo-haptic feedback has been successfully implemented, such as a virtual environment for vocational training of milling machine operations, or a medical simulator for training in regional anesthesia procedures.

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