Passive Brain-Computer Interfaces for Enhanced Human-Robot Interaction.
作者： Maryam Alimardani , Kazuo Hiraki
关键词:
摘要: Brain-computer interfaces (BCIs) have long been seen as control that translate changes in brain activity, produced either by means of a volitional modulation or response to an external stimulation. However, recent trends the BCI and neurofeedback research highlight passive monitoring user’s activity order estimate cognitive load, attention level, perceived errors emotions. Extraction such higher information from signals is gateway for facilitation interaction between humans intelligent systems. Particularly field robotics, BCIs provide promising channel prediction affective state development user-adaptive interaction. In this paper, we first illustrate state-of-the art technology then examples employment human-robot (HRI). We finally discuss prospects challenges integration socially demanding HRI settings. This work intends inform community opportunities offered systems enhancement while recognizing potential pitfalls.
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