Mind Meets Robots: A Review of EEG-Based Brain-Robot Interaction Systems
arxiv(2024)
摘要
Brain-robot interaction (BRI) empowers individuals to control
(semi-)automated machines through their brain activity, either passively or
actively. In the past decade, BRI systems have achieved remarkable success,
predominantly harnessing electroencephalogram (EEG) signals as the central
component. This paper offers an up-to-date and exhaustive examination of 87
curated studies published during the last five years (2018-2023), focusing on
identifying the research landscape of EEG-based BRI systems. This review aims
to consolidate and underscore methodologies, interaction modes, application
contexts, system evaluation, existing challenges, and potential avenues for
future investigations in this domain. Based on our analysis, we present a BRI
system model with three entities: Brain, Robot, and Interaction, depicting the
internal relationships of a BRI system. We especially investigate the essence
and principles on interaction modes between human brains and robots, a domain
that has not yet been identified anywhere. We then discuss these entities with
different dimensions encompassed. Within this model, we scrutinize and classify
current research, reveal insights, specify challenges, and provide
recommendations for future research trajectories in this field. Meanwhile, we
envision our findings offer a design space for future human-robot interaction
(HRI) research, informing the creation of efficient BRI frameworks.
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