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One of the objectives of the control using the human thought is to make useful robotic systems for persons with high dependency (quadriplegics, paraplegics, etc.). When the human subject is not able to move his limbs, upper or lower, he is no longer able to perform basic and necessary tasks in his daily life. Recently, robotic systems have reached a very advanced level. For example, humanoid robots...
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...
The Steady State Visual Evoked Potentials (SSVEP), present in ElectroEncephaloGram (EEG) signal, are currently used as a convenient approach to a Brain-Computer Interface (BCI). However, the stimulus frequencies are bellow the Flicker Fusion Frequency (FFF). In this work, the possibility of producing SSVEP for stimulus frequency beyond the FFF is investigated. From our experimental SSVEP results,...
Brain-Computer Interface (BCI) systems allow user to operate devices without muscular activation and experimental results indicate that they can induce activity-dependent plasticity. A BCI system has two key features: exploitation of brain signal changes induced by the cognitive task assigned to the user and mutual learning. With respect to the first feature, BCI users can learn to control and hence...
A brain-computer interface (BCI) provides the possibility to translate brain neural activity patterns into control commands without user's movement. The brain activity is most commonly measured non-invasively via standard electroencephalography (EEG), i.e., with electrodes placed on the surface of the scalp. In this article, we evaluate a BCI system based on steady-state visual evoked potentials (SSVEPs)...
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