Design Eye-Tracking Augmented Reality Headset to Reduce Cognitive Load in Repetitive Parcel Scanning Task

Abstract

Repetitive tasks widely exist in applied fields of human-computer interaction. One underestimated example is parcel scanning, which has consistent operation difficulty but comprises multiple processes (e.g., label seeking and scanning, result confirming, and parcel relocating), involving respective cognitive requirements. Many devices are developed to facilitate repetitive operations, but few are to reduce fluctuating cognitive load throughout task processes. We present the eye-tracking augmented reality headset that integrates foveated vision detection and smooth pursuit of eye tracking and investigate how it can reduce cognitive load in the repetitive task. In total, 33 participants completed a set of parcel scanning tasks with the headset and their visual and cognitive performance were assessed. The results show that the headset maintained high scanning efficiency and lower cognitive load across the tasks with varying difficulties and it significantly reduced the participants’ cognitive load during the processes of barcode seeking and scanning and result confirmation. The headset demonstrated good usability and ease of use. Implications for how the case study result could be used in generalizing applications are discussed.