考虑个体眼动数据差异的认知负荷评估方法

Jun Chen, Qilin Zhang, Long Cheng, Xudong Gao, Lin Ding
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引用次数: 6

摘要

在飞行员执行飞行任务的过程中,高认知负荷会导致飞行员态势感知能力下降。严重的可能会导致航空事故。本文基于k-means和支持向量机算法,提出了一种考虑个体差异的基于眼动数据的认知负荷评估方法。与传统的基于支持向量机的方法相比,该方法可以根据个体差异对数据进行聚类,然后利用支持向量机对数据进行分类。最后,实验结果表明本文提出的方法具有较高的分类精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Cognitive Load Assessment Method Considering Individual Differences in Eye Movement Data
In the process of the pilot executing the flight task, the high cognitive load will cause a decrease in the pilot's situation awareness. Seriously, it may cause an aviation accident. In the paper, based on k-means and SVM (support vector machines) algorithms, a cognitive load assessment method based on eye movement data that considers individual differences has been proposed. Compared to traditional SVM-based methods, this method can cluster data based on individual differences, and then classify them by SVM. Finally, the experimental results show that the method proposed in the paper has a higher classification accuracy.
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