Sofien Gannouni

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Over the last few decades, brain signals have been significantly exploited for brain-computer interface (BCI) applications. In this paper, we study the extraction of features using event-related desynchronization/synchronization techniques to improve the classification accuracy for three-class motor imagery (MI) BCI. The classification approach is based on(More)
Integrating and accessing data stored in autonomous, distributed and heterogeneous data sources have been recognized as of a great importance to small and huge-scale businesses. Enhancing the accessibility and the reusability of these data entail the development of new approaches for data sharing. These approaches should satisfy a minimal set of criteria in(More)
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