A Score based method for P300 Collaborative BCI

Group decision-making is the process where two or more people are engaged in generating a solution for a given problem. In the last decade, researchers started exploiting collaborative Brain-Computer Interfaces to enhance group performance. Various methods have been proposed to integrate EEG data of multiple users showing the improvement in group decisionmaking over single-user BCIs and non-BCI systems. In this study, we investigate four EEG integration strategies: EEG averaging across participants, the standard majority voting rule and two weighted voting system. For each approach, we evaluate three different scenarios varying the number of iterations necessary to perform a single selection. In all cases, it is possible to exceed 90% of accuracy with at least one collaborative BCI.

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