验证用于认知负荷评估的通用照相机眨眼检测系统

IF 1.2 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Francesco N. Biondi, Frida Graf, Prarthana Pillai, Balakumar Balasingam
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引用次数: 0

摘要

检测人类操作员的认知状态是最重要的设置,其中保持最佳的工作量是必要的任务执行。眨眼频率是衡量认知负荷的一项指标,在工作负荷较大的情况下,眨眼频率越高。测量眨眼频率需要使用眼动仪,这限制了该指标在现实世界中的采用。作者的目的是研究使用一个通用的基于摄像头的系统来评估用户在计算机任务中的认知负荷的有效性。参与者坐在电脑前完成一项脑力任务。眨眼频率是通过普通的基于摄像头的系统和科学级眼动仪记录的,以进行验证。认知负荷也通过在单一刺激检测任务中的表现来评估。通过普通的基于摄像头的方法记录的眨眼频率与通过眼动仪获得的没有区别。然而,随着认知负荷的增加,眨眼率没有显著变化。结果表明,基于通用相机的系统可能是一种更经济、更普遍的评估计算机任务中认知工作量的方法。今后的工作应进一步研究如何在完成更现实的任务时提高其准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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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来源期刊
Cognitive Computation and Systems
Cognitive Computation and Systems Computer Science-Computer Science Applications
CiteScore
2.50
自引率
0.00%
发文量
39
审稿时长
10 weeks
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