International audienceIn this paper, we are studying hybrid Brain-Computer Interfaces (BCI) coupling joystick data, electroencephalogram (EEG – electrical activity of the brain) and electromyogram (EMG – electrical activity of muscles) activities for severe motor disabilities. We are focusing our study on muscular activity as a control modality to interact with an application. We present our data processing and classification technique to detect right and left hand movements. EMG modality is well adapted for DMD patients, because less strength is needed to detect movements in contrast to conventional interfaces like joysticks. Across virtual reality tools, we believe that users will be more able to understand how to interact with such kind of interactive systems. This first part of our study report some very good results concerning the detection of hand movements, according to muscular channel, on healthy subjects

Le développement de nouveaux systèmes d'aide à la personne est l'une des applications interface cerveau ordinateur (BCI) les plus probables à court et moyen terme. Contrairement à de nombreuses technologies d'assistance récentes, les systèmes BCI actuels ne résultent pas d'une approche de conception universelle. De nombreux auteurs ont montré l'importance de prendre en compte des critères comme l'adaptabilité, la flexibilité, et autres critères relatifs à l'ergonomie lors de la conception d'une interface BCI. Dans cet article, nous proposons un cadre de travail visant à accélérer le transfert des expérimentations BCIs des laboratoires de recherche vers les services cliniques puis aux domiciles des patients. Plus précisément, nous montrons l'intérêt de concevoir une salle d'expérimentation dédiée (RBCIE) où les interfaces BCI peuvent être testées et validées efficacement. ABSTRACT. The development of new enabling devices is one of the most credible short and medium-term applications of brain-computer interfaces (BCI). Unlike many other recent assistive technologies (AT), present BCI systems usually do not result from a "design for all" approach, since they are mainly effective for people suffering from severe motor disabilities. However, many authors have shown that it is crucial to take into account adaptability, flexibility, customisability and other ergonomics related criteria while designing a BCI-based AT. In this paper, we specify a framework that could expedite the transferability of BCI experiments from labs to clinical departments and later to patients' homes. We highlight the interest of designing dedicated experimentation facilities (RBCIE) in which the developed BCI systems can be efficiently tested and validated. More generally, we highlight the interest of a multidisciplinary design approach introducing human factors at the core of concerns.

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