A physical learning companion for Mental-Imagery BCI User Training. Issue 136 (April 2020) - Pillette, Léa; Jeunet, Camille; Mansencal, Boris; N'Kambou, Roger; N'Kaoua, Bernard; Lotte, Fabien
Highlights: Learning companions could improve Brain-Computer Interface (BCI) user experience. Non-autonomous users can benefit from learning companions (increased performances). Companions' interventions should be adapted to users performance and progression. Abstract: Mental-Imagery based Brain-Computer Interfaces (MI-BCI) present new opportunities to interact with digital technologies, such as wheelchairs or neuroprostheses, only by performing mental imagery tasks (e.g., imagining an object rotating or imagining hand movements). MI-BCIs can also be used for several applications such as communication or post-stroke rehabilitation. Though, their lack of reliability remains a barrier to a larger scale development of the technology. For example, one task between two is recognized on average 75% of the time. It has been shown that users are more likely to struggle using MI-BCIs if they are non-autonomous or tensed. This might, at least in part, result from a lack of social presence and emotional support, which have yet very little been tested in MI-BCI, despite recommendations from the educational literature. One way to provide such social and emotional context is by using a learning companion. Therefore, we designed, implemented and evaluated the first learning companion dedicated to the improvement of MI-BCI user training. We called this companion PEANUT for Personalized Emotional Agent for Neurotechnology User Training. PEANUT provided social presence and emotional support, depending on the performance and progress of the user, through interventions combining both pronounced sentences and facial expressions. It was designed based on the literature, data analyses and user-studies. We notably conducted various online user surveys to identify the desired characteristics of our learning companion in terms of appearance and supporting speech content. From the results of these surveys we notably deduced which should be the characteristics (personal/non-personal, exclamatory/declarative) of the sentences to be used depending on the performance and progression of a learner. We also found that eyebrows could increase expressiveness of cartoon-like faces. Then, once this companion was implemented, we evaluated it during real online MI-BCI use. We found that non-autonomous people, i.e., who are more inclined to work in a group, that are usually disadvantaged when using MI-BCI were advantaged compared to autonomous people when PEANUT was present with an increase of 3.9% of peak performances. Furthermore, in terms of user experience, PEANUT seems to have improved how people felt about their ability to learn and memorize how to use an MI-BCI by 7.4%, which is a dimension of the user experience we assessed.