21 citations · 63 across the 8 of their papers we have counts for
9 papers
Towards Artificial Learning Companions for Mental Imagery-based Brain-Computer Interfaces
Léa Pillette, Camille Jeunet, Roger N'Kambou +2
Mental Imagery based Brain-Computer Interfaces (MI-BCI) enable their users to control an interface, e.g., a prosthesis, by performing mental imagery tasks only, such as imagining a…
Would Motor-Imagery based BCI user training benefit from more women experimenters?
Aline Roc, Léa Pillette, B. N'Kaoua +1
Mental Imagery based Brain-Computer Interfaces (MI-BCI) are a mean to control digital technologies by performing MI tasks alone. Throughout MI-BCI use, human supervision (e.g., exp…
AI in the media and creative industries
Giuseppe Amato, Malte Behrmann, Frédéric Bimbot +16
Thanks to the Big Data revolution and increasing computing capacities, Artificial Intelligence (AI) has made an impressive revival over the past few years and is now omnipresent in…
Active Inference for Adaptive BCI: application to the P300 Speller
Jelena Mladenović, Jérémy Frey, Emmanuel Maby +3
Adaptive Brain-Computer interfaces (BCIs) have shown to improve performance, however a general and flexible framework to implement adaptive features is still lacking. We appeal to…
A generic framework for adaptive EEG-based BCI training and operation
Jelena Mladenović, Jérémie Mattout, Fabien Lotte
There are numerous possibilities and motivations for an adaptive BCI, which may not be easy to clarify and organize for a newcomer to the field. To our knowledge, there has not bee…
The Impact of Flow in an EEG-based Brain Computer Interface
Jelena Mladenović, Jérémy Frey, Manon Bonnet-Save +2
Major issues in Brain Computer Interfaces (BCIs) include low usability and poor user performance. This paper tackles them by ensuring the users to be in a state of immersion, contr…