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Measuring the older adults’ emotion with commensality robots of different social presence: comparison of EEG and SAM approaches
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DOI：10.1007/s12369-026-01425-8.png)
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Abstract
En 中文
Commensality, the social act of dining collectively, serves as a fundamental mechanism for fostering social bonds and intimacy. However, a significant number of older adults experience diminished commensality due to a scarcity of companionship in aging populations. Past studies have suggested that robotic companionship may be one solution, especially since commensality robots that can track their interlocutors’ emotions can provide higher-quality companionship. However, there has been a lack of research on how to accurately measure users’ genuine emotional state during interaction with a robot to justify the robot’s design. This study employed two techniques, electroencephalography (EEG) and a self-assessment manikin (SAM), to measure reflective emotions during co-eating interactions between older adults and either robots or stuffed animals, including high- and low-social-presence robot groups, as well as within-group comparisons of robot and stuffed-animal interactions. Results showed that the SAM arousal effect was significant only between the robot and stuffed animal groups. The values of other SAM and EEG measures were consistent between and within groups, with no significant differences in SAM valence or EEG. The measures demonstrated convergent validity for valence, consistent across and within conditions, despite a weak individual-level correlation. Divergent validity was observed for arousal, aligning with expectations since frontal alpha asymmetry indexes valence rather than arousal. EEG and SAM thus show convergent validity for valence and appropriate divergence for arousal, though further studies with greater statistical power are needed to confirm the strength of valence convergence. The findings of this study support the feasibility of testing users’ emotions in real-world human-robot interactions, underscoring the significance of this research.
Keywords:
Electroencephalography (EEG)
Emotion in human-robotic interaction
Self-assessment manikin (SAM)
Social agents/robotics
Older adults
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