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Feedback plays an important role when learning to use a Brain-Computer Interface (BCI). Here we compare visual and haptic feedback in a short experiment. By imagining left and right hand movements, six subjects tried to control a BCI with the help of either visual or haptic feedback every 1s. Alpha band EEG signals from C3 and C4 were classified. The classifier was updated after each prediction using correct class information. Thus feedback could be given throughout the experiment. Subjects got better at controlling the BCI during the experiment independent of the feedback modality. Haptic feedback did not present any artifacts to the signals. More research is required on haptic feedback for BCI-applications because it frees visual attention to other tasks.

Brain-Computer Interfaces (BCIs) need an uninterrupted flow of feedback to the user, which is usually delivered through the visual channel. Our aim is to explore the benefits of vibrotactile feedback during users� training and control of EEG-based BCI applications. An experimental setup for delivery of vibrotactile feedback, including specific hardware and software arrangements, was specified. We compared vibrotactile and visual feedback, addressing the performance in presence of a complex visual task on the same (visual) or different (tactile) sensory channel. The preliminary experimental setup included a simulated BCI control. in which all parts reflected the computational and actuation process of an actual BCI, except the souce, which was simulated using a �noisy� PC mouse. Results indicated that the vibrotactile channel can function as a valuable feedback modality with reliability comparable to the classical visual feedback. Advantages of using a vibrotactile feedback emerged when the visual channel was highly loaded by a complex task.

A Brain-Computer Interface (BCI) allow direct expression of its user�s will by interpreting signals which directly reflect the brain�s activity, thus bypassing the natural efferent channels (nerves and muscles). To be correctly mastered, it is needed that this artificial efferent channel is complemented by an artificial feedback, which continuously informs the user about the current state (in the same way as proprioceptors give a feedback about joint angle and muscular tension). This feedback is usually delivered through the visual channel. We explored the benefits of vibrotactile feedback during users� training and control of EEG-based BCI applications. A protocol for delivering vibrotactile feedback, including specific hardware and software arrangements, was specified and implemented. Thirteen subjects participated in an experiment where the feedback of the BCI system was delivered either through a visual display, or through a vibrotactile display, while they performed a virtual navigation task. Attention to the task was probed by presenting visual cues that the subjects had to describe afterwards. When compared with visual feedback, the use of tactile feedback did not decrease BCI control performance; on the other side, it improved the capacity of subjects to concentrate on the requested (visual) task. During experiments, vibrotactile feedback felt (after some training) more natural. This study indicated that the vibrotactile channel can function as a valuable feedback modality in the context of BCI applications. Advantages of using a vibrotactile feedback emerged when the visual channel was highly loaded by a complex task.