Recent work in HRI found that prefrontal hemodynamic activity correlated with participants’ aversions to certain robots. Using a combination of brain-based objective measures and survey-based subjective measures, it was shown that increasing the presence (co-located vs. remote interaction) and human-likeness of the robot engaged greater neural activity in the prefrontal cortex and severely decreased preferences for future interactions. The results of this study suggest that brain-based measures may be able to capture participants’ affective responses (aversion vs. affinity), and in a variety of interaction settings. However, the brain-based evidence of this work is limited to temporally-brief (6-second) post-interaction samples. Hence, it remains unknown whether such measures can capture affective responses over the course of the interactions (rather than post-hoc). Here we extend the previous analysis to look at changes in brain activity over the time course of more realistic human-robot interactions. In particular, we replicate the previous findings, and moreover find qualitative evidence suggesting the measurability of fluctuations in affect over the course of the full interactions.
@inproceedings{straitscheutz14phycs,
title={Using near infrared spectroscopy to index temporal changes in affect in realistic human-robot interactions},
author={Megan Strait and Matthias Scheutz},
year={2014},
booktitle={Physiological Computing Systems (PhyCS), Special Session on Recognition of Affect Signals from Physiological Data for Social Robots},
url={https://hrilab.tufts.edu/publications/straitscheutz14phycs.pdf}
}