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

被引：22

作者：

Katidioti, Ioanna ^{[1
]}

Borst, Jelmer P. ^{[1
]}

de Haan, Douwe J. Bierens ^{[2
]}

Pepping, Tamara ^{[2
]}

van Vugt, Marieke K. ^{[3
]}

Taatgen, Niels A. ^{[3
]}

机构：

[1] Univ Groningen, Dept Artificial Intelligence, NL-9747 AG Groningen, Netherlands

[2] Univ Groningen, Dept Artificial Intelligence, Human Machine Commun, Groningen, Netherlands

[3] Univ Groningen, Dept Artificial Intelligence, Cognit Modeling, Groningen, Netherlands

来源：

INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION | 2016年 / 32卷 / 10期

基金：

欧洲研究理事会;

关键词：

TASK; SIZE; LOAD;

D O I：

10.1080/10447318.2016.1198525

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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-independentit does not require a task analysisit can be broadly applied.

引用

页码：791 / 801

页数：11

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