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首页> 外文会议>International conference on human-computer interaction;International conference on augmented cognition >A Composite Cognitive Workload Assessment System in Pilots Under Various Task Demands Using Ensemble Learning
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A Composite Cognitive Workload Assessment System in Pilots Under Various Task Demands Using Ensemble Learning

机译：集成学习的飞行员在不同任务需求下的复合认知工作量评估系统

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The preservation of attentional resources under mental stress holds particular importance for the execution of effective performance. Specifically, the failure to conserve attentional resources could result in an overload of attentional capacity, the failure to execute critical brain processes, and subop-timal decision-making for effective motor performance. Therefore, assessment of attentional resources is particularly important for individuals such as pilots who must retain adequate attentional reserve to respond to unexpected events when executing their primary task. This study aims to devise an expert model to assess an operator's dynamic cognitive workload in a flight simulator under various levels of challenge. The results indicate that the operator's cognitive workload can be effectively predicted with combined classifiers of neuro-physiological biomarkers, subjective assessments of perceived cognitive workload, and task performance. This work provides conceptual feasibility to develop a real-time cognitive state monitoring tool that facilitates adaptive human-computer interaction in operational environments.
机译：在精神压力下保持注意力资源对于执行有效表现尤为重要。具体而言，未能保存注意力资源可能导致注意力能力超负荷，无法执行关键的大脑过程以及为有效运动表现而进行的次眼下决策。因此，对注意力资源的评估对于诸如飞行员这样的个人尤其重要，这些飞行员​​在执行其主要任务时必须保留足够的注意力储备以应对意外事件。这项研究旨在设计一种专家模型，以评估操作员在各种挑战级别下的飞行模拟器中的动态认知工作量。结果表明，可以使用神经生理学生物标志物的分类器，感知到的认知工作量的主观评估以及任务绩效来有效地预测操作员的认知工作量。这项工作为开发实时认知状态监视工具提供了概念上的可行性，该工具有助于在操作环境中进行自适应人机交互。

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