Controlling devices using physiological signals is an increasingly active research field in human-robot interaction. Using brain signals, or Electroencephalograms (EEG), to control devices is widely known as Brain-Computer Interfacing (BCI). In a BCI system, brain signals are used to directly control devices and not as a communication channel, so target applications are restricted to handicapped and aged people. On the other hand, it is possible for healthy people to simply control devices using voice and body movements. In this paper, quantifying human's state of mind and emotions is investigated by analyzing changes in brain activity. The existence of a relation between robots' bodily expressions and their impressions on the observer is demonstrated. We also show a correlation between the nature of the expression and the power of the low-alpha channel in brain signals. Robots can make use of this quantification as an extra channel of information to achieve smoother and more human-like adaptive interaction.

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During an interaction process, people usually adapt their behavior according to the interpretation of their partner's bodily expressions. It is not known how much similar expressions performed by robots affect a human observer. This paper explores this issue. The study shows a correlation between the nature of the bodily expressions, through the result of questionnaires, and the effect on brain activity. It has been demonstrated that unpleasant bodily expressions of the robot elicit unpleasant impressions and vice versa. This was observed through brain activity in a specific area when the expression is pleasant, and in another area when it is unpleasant.