Exploring Pupil Dilation as an Indicator of Performance in Gaze-Based Robot Navigation for Assistive Technology

Human-robot interaction (HRI) based assistive devices play a crucial role for individuals with severe disability, significantly impacting their quality of life. A pivotal step towards creating a more human-centric HRI involves gaining a thorough understanding of the user's mental load such as cognitive load, stress, and fatigue, which can influence the performance of the system. Previous studies have found pupil dilation as a potential candidate for exploring mental workload. This paper explores the impact of pupil diameter variation on performance during an eye-tracking-based robot navigation task. Nineteen healthy individuals participated in the experiment where they used eye-gaze to activate different navigational buttons on a computer screen to control the movement of a mobile robot on a predefined trajectory for two rounds. The variation of pupil diameter is correlated to various performance parameters such as lap completion time and number of commands. Results show that the difference between the Gaussian means of the pupil diameter distribution during round1 and round2 is significantly correlated (rho =0.5, p-value =0.03) with the lap completion time while the correlation with the number of commands is also found to be strong (r h o=0.45, p-value =0.05). These quantifications of pupil diameter variations with performance measures have the potential to play a vital role in advancing the HRI systems as they can be used to predict the performance variation in real-time so that the HRI can be more responsive to the user's changing mental states, a key requirement for the practical usability and acceptability of such systems as assistive