Dynamic changes of pupil dilation represent an established indicator of cognitive load in cognitive sciences Exploitation of these insights regarding pupil dilation as an indicator of cognitive load for attention-aware Information and Communication (ICT) systems has been impeded due to restrictions of pupil analysis to a posteriori processing and exclusion of disturbing environmental factors. To overcome these issues, this paper proposes an algorithm based on Hoeks's pupil response model, enabling online analysis of pupil dilation for the dynamic interpretation of cognitive load as an input for interactive, attention-aware systems, which outperforms state-of-the-art approaches regarding complexity, accuracy, flexibility and computation time. Beyond mathematical pupil modeling, this paper identifies Environment Illumination compensation (IC), Blink Compensation (BC), Reference Baseline computation (RB) and Onset/Offset detection (OO) as crucial fields of research for the transfer of pupillometry from the laboratory into real-life application scenarios.
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