Proteus: measuring, understanding and tackling variabilities in Brain-Computer Interaction – PROTEUS

Whereas Brain-Computer Interfaces (BCI) are very promising for various applications, e.g., brain-based wheelchair control or plane pilots’ mental state monitoring, they are not reliable. Their reliability degrades even more when used across contexts (e.g., days, users’ states or applications used) due to various sources of variabilities. Unfortunately, such variabilities are 1) often ignored in the literature, as most BCIs are assessed in a single context and 2) barely understood. Thus, for BCIs to fulfill their promises and be used outside laboratories, we need to make them robust to such variabilities. In project PROTEUS we propose to do so by 1) Systematically measuring BCI and brain signal variabilities across various contexts while sharing the collected databases; 2) Characterizing, understanding and modeling the variability and their causes based on these new databases; and 3) Tackling these variabilities by designing new machine learning algorithms optimally invariant to them according to our models, and using the resulting BCIs for two practical applications affected by variabilities: tetraplegic BCI user training and auditory attention monitoring at home or in flight.