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

Ioanna Katidioti, Jelmer P. Borst, Douwe J. Bierens de Haan, Tamara Pepping, Marieke K. van Vugt, Niels A. Taatgen

Research output: Contribution to journalArticleAcademicpeer-review

27 Citations (Scopus)
288 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)791-801
Number of pages11
JournalInternational Journal of Human-Computer Interaction
Volume32
Issue number10
DOIs
Publication statusPublished - 8-Jun-2016

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