Quantifying Human Mental State in Interactive pHRI: Maintaining Balancing

Abstract

As robots increasingly enter domestic environments, investigating the impact of their physical behaviors and the potential to leverage human mental states during interaction becomes crucial. This study examines how a robot's active behavior (unanticipated physical actions) versus passive behavior (actions aligned with user expectation) affects users' mental states during a physical balance task. Our findings show that passive interaction is generally more cognitively ergonomic, while active behavior, though it reduces imbalance, adds cognitive strain. Users' perceptions of the robot are not affected by its behavior type. We conclude that combining peripheral skin temperature with age and personality traits holds significant potential for enhancing robots' ability to infer users' cognitive ergonomics and belief levels. This study explores the relatively under-researched area of active behavior in physical assistive applications with minimal sensor requirements and identifies easily obtainable online data as indicators of human mental state.