On validating a generic camera-based blink detection system for cognitive load assessment

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Abstract

Detecting the human operator's cognitive state is paramount in settings wherein maintaining optimal workload is necessary for task performance. Blink rate is an established metric of cognitive load, with a higher blink frequency being observed under conditions of greater workload. Measuring blink rate requires the use of eye-trackers which limits the adoption of this metric in the real-world. The authors aim to investigate the effectiveness of using a generic camera-based system as a way to assess the user's cognitive load during a computer task. Participants completed a mental task while sitting in front of a computer. Blink rate was recorded via both the generic camera-based system and a scientific-grade eye-tracker for validation purposes. Cognitive load was also assessed through the performance in a single stimulus detection task. The blink rate recorded via the generic camera-based approach did not differ from the one obtained through the eye-tracker. No meaningful changes in blink rate were however observed with increasing cognitive load. Results show the generic-camera based system may represent a more affordable, ubiquitous means for assessing cognitive workload during computer task. Future work should further investigate ways to increase its accuracy during the completion of more realistic tasks.

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APA

Biondi, F. N., Graf, F., Pillai, P., & Balasingam, B. (2023). On validating a generic camera-based blink detection system for cognitive load assessment. Cognitive Computation and Systems, 5(4), 255–264. https://doi.org/10.1049/ccs2.12088

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