Detecting the Effect of Stress on Performance in Augmented Reality Using Eye-Tracking

Abstract:

The ability of a user to control their attention level in an Augmented Reality (AR) setting is an unreliable quality for the design of an AR system. An alternative design approach addresses adaptive user interfaces (UI) in which the AR UI adapts to user needs. One use case of such a design is an adaptive interface that detects user stress and controls the system information flow after detection to avoid a decrease in task performance. To acquire measurements of user stress, data are collected from having participants play a custom developed AR Tetris game on a Microsoft Hololens while a Pupil Labs eye tracker tracks their eye movement. Controllable factors include speed of the Tetris blocks, time difference between blocks, and differing amounts of practice time.