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EEG-based Mental Workload and Stress Recognition of Crew Members in Maritime Virtual Simulator: A Case Study

机译:基于EEG的海上虚拟模拟器中船员的心理工作量和压力识别:一个案例研究

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Many studies have shown that the majority of maritime accidents/incidents are attributed to human errors as the initiating cause. Efforts have been made to study human factors that can result in a safer maritime transportation. Among all techniques, Electroencephalogram (EEG) has the advantages such as high time resolution, possibility to continuously monitor brain states with high accuracy, recognition of human mental workload, emotion, stress, vigilance, etc. In this paper, we designed and carried out an experiment to collect the EEG signals to study stress and sharing of the mental workload among crew members during collaboration tasks performance on the ship's bridge virtual simulator. Four maritime trainees were monitored in the experiment. Each of them had a role such as an officer on watch, captain, pilot, or steersman. The results show that the captain had the highest stress and workload. However, the other three trainees experienced low workload and stress due to shared work and responsibility. The EEG is a promising evaluation tool to be used in the human factors study in the maritime domain.
机译:许多研究表明,大多数海事事故/事故起因是人为错误。已经努力研究可以导致更安全的海上运输的人为因素。在所有技术中,脑电图(EEG)具有以下优点:时间分辨率高,可以以高精度连续监视大脑状态,识别人类的精神工作量,情绪,压力,警惕性等。在本文中,我们设计并实施了一项收集EEG信号的实验,以研究船上桥梁虚拟模拟器在协作任务执行过程中船员之间的压力和精神工作量的分配。实验中监测了四名海上学员。他们每个人都有一个角色,例如值班人员,上尉,飞行员或舵手。结果表明,机长压力和工作量最高。但是,由于共同的工作和责任感,其他三名学员的工作量少,压力大。脑电图是一种有前途的评估工具,可用于海事领域的人为因素研究。

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