Interrupted by Your Pupil: An Interruption Management System Based on Pupil Dilation

Abstract

Interruptions are prevalent in everyday life and can be very disruptive. An important factor that affects the level of disruptiveness is the timing of the interruption: Interruptions at low-workload moments are known to be less disruptive than interruptions at high-workload moments. In this study, we developed a task-independent interruption management system (IMS) that interrupts users at low-workload moments in order to minimize the disruptiveness of interruptions. The IMS identifies low-workload moments in real time by measuring users’ pupil dilation, which is a well-known indicator of workload. Using an experimental setup we showed that the IMS succeeded in finding the optimal moments for interruptions and marginally improved performance. Because our IMS is task-independent—it does not require a task analysis—it can be broadly applied.