Group study via collaborative BCI

Group decisions are a common phenomenon in modern society. Groups typically have increased sensing and cognition capabilities that allow them to make better decisions than individuals. In the last decade, researchers have started evaluating the possibilities to exploit, by means of collaborative BCI, the neurophysiological signals of a group of observers to improve the decision-making process. Following this stream of research, in this work we build a collaborative BCI and focus on the role of each subject in the group, trying to answer the question whether there are some subjects that would be better to remove or that are fundamental to enhance group performance. Moreover, we focus on identifying the smallest subgroup allowing to achieve 100% of accuracy.