Document Type
Article
Publication Date
2023
Publication Title
Cognitive Computation and Systems
Volume
2023
Issue
1
First Page
1
Keywords
active vision, cognition, human-robot interaction
Last Page
10
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.
DOI
10.1049/ccs2.12088
ISSN
2517-7567
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Biondi, Francesco; Grad, Frida; Pillai, Prarthana; and Balasingam, Balakumar Dr.. (2023). On validating a generic camera-based blink detection system for cognitive load assessment. Cognitive Computation and Systems, 2023 (1), 1-10.
https://scholar.uwindsor.ca/humankineticspub/47