Using gaze behavior to measure cognitive load

Measuring and influencing cognitive load during information processing can be seen as a promising instrument to mitigate the risk of information overload while increasing processing capabilities. In this study, we demonstrate how to use cross-sectional time-series data generated with an eye tracking device to indicate cognitive load levels. Thereby we combine multiple measures related to fixations, saccades and blinks and calculate one comprehensive and robust measure. Applicability is demonstrated by conducting two separate experiments in a decision-making scenario in the context of information visualization.