This paper presents the design and feasibility evaluation of a low-cost, head-mounted pupil dilation tracking system based on computer vision. The proposed solution employs a standard webcam and active infrared illumination, enabling stable eye image acquisition under controlled lighting conditions. The developed image processing pipeline incorporates adaptive contrast enhancement and geometric pupil detection, allowing for the estimation of relative changes in pupil diameter in real time. System evaluation was conducted in a controlled experiment involving 24 participants performing an N-back task with emotional modulation, a well-established paradigm for eliciting task-evoked pupillary responses under constant working-memory demands. The results revealed statistically significant changes in relative pupil dilation in response to stimuli with varying emotional valence during a working memory task, confirming the system’s ability to capture task-evoked pupillary responses (TEPRs). The proposed system constitutes a low-cost research tool for studies of task engagement and physiological responses in the context of human–computer interaction and psychophysiology, with a focus on the analysis of functional pupilometric changes.
Jasinska et al. (Fri,) studied this question.