Brain Activity in the Evaluation of the Impression of Robot Bodily Expressions

Abstract

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.

Assessment of the Impressions of Robot Bodily Expressions Using Electroencephalogram Measurement of Brain Activity

“…Research in cognitive neuroscience has shown that the power of low-alpha frequency band is the most reactive band to social cues such as movements (Allison et al, 2000;Cochin et al, 1998). We suppose that this frequency band reacts in a similar way to robot bodily expressions (Khiat et al, 2006). The next step in assessing the impression is to observe the amount of change in the power of low-alpha frequency band compared to the whole spectrum.…”