Cognitive Load Estimation Based on Pupillometry in Virtual Reality with Uncontrolled Scene Lighting
Marie Eckert, Emanuël A. P. Habets, Olli Rummukainen
Abstract
Virtual reality (VR) technology enables and requires new ways of user experience testing in immersive environments. For various aspects of user experience, objective assessment of the cognitive load can be a useful parameter. With eye-tracking becoming a more widespread feature of current VR headsets, pupillometry is an appealing option to unobtrusively measure cognitive load during a VR experience. This paper shows that pupil size measured by an off-the-shelf VR headset with an integrated eye tracker positively correlates with the self-reported cognitive load during a standard n-back task adapted to a VR environment. To overcome the need for steady scene-lighting conditions, we present a method to correct for the light-induced pupil size changes, otherwise masking the cognitive load effects. Our results show that a commercially available VR headset with eye tracking can be used to measure the cognitive load in unpredictable lighting conditions without additional hardware.