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Le neurofeedback consiste à mesurer une activité électrophysiologique corticale, à traiter le signal au moyen d’une interface technique afin d’en extraire un paramètre d’intérêt, puis à le présenter en temps réel au sujet sous la forme d’une information compréhensible [1]. L’objectif est d’apprendre au sujet à moduler son activité corticale, en temps réel, afin d’obtenir une amélioration sur une performance...
Although Mental Imagery based Brain-Computer Interfaces (MI-BCIs) seem to be very promising for many applications, they are still rarely used outside laboratories. This is partly due to suboptimal training protocols, which provide little help to users learning how to control the system. Indeed, they do not take into account recommendations from instructional design. However, it has been shown that...
Despite their potential for many applications, Brain -- Computer Interfaces (BCI) are still rarely used due to their low reliability and long training. These limitations are partly due to inappropriate training protocols, which includes the feedback provided to the user. While feedback should theoretically be explanatory, motivating and meaningful, current BCI feedback is usually boring, corrective...
Although EEG-based BCI are very promising for numerous applications, they mostly remain prototypes not used outside laboratories, due to their low reliability. Poor BCI performances are partly due to imperfect EEG signal processing algorithms but also to the user, who may not be able to produce reliable EEG patterns. This paper presents some of our current work that aims at addressing the latter,...
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