Laboratoire d'Informatique de Grenoble Équipe Ingénierie de l'Interaction Humain-Machine

Équipe Ingénierie de l'Interaction

Bidirectional Feedback in Motor Imagery BCIs: Learn to Control a Drone within 5 Minutes

In CHI'14 Extended Abstracts on Human Factors in Computing Systems. 2014. pages 479-482. 2014.

Nataliya Kos'myna, Franck Tarpin-Bernard, Bertrand Rivet


Brain Computer Interface systems rely on lengthy training phases that can last up to months due to the inherent variability in brainwave activity between users. We propose a BCI architecture based on the co-learning between the user and the system through different feedback strategies. Thus, we achieve an operational BCI within minutes. We apply our system to the piloting of an AR.Drone 2.0 quadricopter. We show that our architecture provides better task performance than traditional BCI paradigms within a shorter time frame. We further demonstrate the enthusiasm of users towards our BCI-based interaction modality and how they find it much more enjoyable than traditional interaction modalities.