Restoring Engagement in Human-Robot Interaction: A Brain-Computer Interface for Adaptive Learning with Robots

This paper investigates the efficacy of a passive Brain-Computer Interface (BCI) in enabling a robot tutor to adaptively respond to a user's engagement level in real-time. The BCI system extracted EEG Engagement Index from the user's electroencephalography (EEG) signals as an indicator of engagement during Human-Robot Interaction (HRI). A within-subjects study was conducted in which the robot performed attention-recapturing behavior during a learning task under two conditions; either in an adaptive manner whenever a lapse in the user's engagement level was detected by the BCI system (Adaptive condition) or at random intervals regardless of the user's mental states (Random condition). In both conditions, users completed an information retention test following the interaction. The study found no significant difference in the postinteraction test results or mean EEG Engagement Index values between the Adaptive and Random conditions. However, analysis of 10-sec time windows following robot interventions showed that adaptively timed gestures were significantly more effective in restoring user engagement to optimal level compared to randomly timed gestures. This finding provides evidence for the potential of passive BCIs in improving user experience in pedagogical HRI settings.

I. Introduction

The field of brain-computer interfaces (BCIs) has experienced rapid growth in recent years with an increasing number of non-medical applications being developed for everyday use [1]. Specifically, passive BCIs monitor users' mental state to adjust systems' behavior according to users' needs or preferences [2]. These adaptive systems can operate in the background without training or effort from users and can create more human-centric interactions with technology. This branch of BCIs primarily targets healthy users completing cognitively demanding tasks such as driving, pilot training, or learning new information [3]–[8].