研究EEG与叉车司机在不同复杂度的任务场景中的情境意识之间的关系
Yutao Kang1, Yaojie Tao1, Jianjun Wu2
1College of Ocean Science and Engineering, Shanghai Maritime University, China.
概括
脑电图 (EEG) 可以评估叉车司机的情况意识 (SA). 前部,中部,顶部和部区域的特定EEG波模式与SA相关,随着任务复杂性的增加而变得更强.
科学领域:
- 人类因素和人体工程学
- 神经科学是一个神经科学.
- 职业安全 在职业安全.
背景情况:
- 情境意识 (SA) 丧失是叉车操作中人为错误的主要原因.
- 准确评估叉车司机的SA对于防止事故至关重要.
- 电脑电图 (EEG) 信号与SA水平之间的关系尚不清楚.
研究的目的:
- 调查多频段EEG信号与叉车司机SA水平之间的相关性.
- 确定场景复杂性如何影响EEG-SA关系.
- 为了确定特定的EEG模式,表明高与低SA.
主要方法:
- 在模拟操作期间从11个叉车运营商收集了EEG数据.
- 利用换测试来分析不同大脑区域 (F,C,P,O) 和SA水平的EEG波段 (θ,α,β) 之间的相关性.
- 在不同复杂的场景中,在高SA状态和低SA状态的运营商之间比较了EEG模式.
主要成果:
- 截然不同的EEG模式区分高和低SA组.
- 中部和部区域的 θ/β, θ/(α+β) 和部区域的 θ/β, (α+θ) /(α+β) 的特定比率与SA. 一贯相关.
- 这些EEG-SA相关性随着场景复杂性的增加而被放大.
结论:
- 基于EEG的指标可以有效地评估叉车司机的SA.
- 已识别的EEG模式为SA监测提供了客观指标.
- 这些发现支持为工业应用开发实时SA评估工具.
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