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 language | English |
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Pages (from-to) | 791-801 |
Number of pages | 11 |
Journal | International Journal of Human-Computer Interaction |
Volume | 32 |
Issue number | 10 |
DOIs | |
Publication status | Published - 8-Jun-2016 |