不同复杂任务场景下叉车驾驶员脑电与态势感知的关系研究。

IF 1.6 4区 医学 Q3 ERGONOMICS
Yutao Kang, Yaojie Tao, Jianjun Wu, Yu Jiao, Feng Liu, Wei Huang
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引用次数: 0

摘要

叉车作业中的态势感知(SA)丢失是一个主要的人为错误来源。准确评估叉车司机的SA水平至关重要。虽然脑电图(EEG)等生理传感器已被提出用于测量SA,但EEG-SA的关系尚不清楚。本研究分析了11名叉车操作员的脑电图数据,比较了高SA组和低SA组的脑电图状态。通过排列测试,该研究评估了多波段脑电图(F、C、P、O区)与SA的相关性,并研究了场景复杂性如何影响这些关系。结果显示,高、低SA组脑电模式(F、C、P和O区θ、α和β波)明显不同:C和P区θ / β、θ / (α + β)和O区θ / β、(α + θ) / (α + β)与不同情景下SA的相关性一致,且这些指标随着情景复杂性的增加而增强。研究结果促进了基于脑电图的SA评估,有助于在现实环境中准确测量SA。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A study of the relationship between EEG and situation awareness of forklift drivers in task scenarios with different complexities.

Situation awareness (SA) loss in forklift operations is a major human error source. Accurately assessing the SA levels of forklift drivers is essential. While physiological sensors such as electroencephalography (EEG) have been proposed to measure SA, the EEG-SA relationship remains unclear. This study analyzed EEG data from 11 forklift operators, comparing EEG states between high and low SA groups. Using permutation tests, the study assessed multi-band EEG correlations (F, C, P, O regions) with SA and examined how scenario complexity influenced these relationships. Results revealed distinct EEG patterns (θ, α and β waves in F, C, P and O regions) between high and low SA groups: θ / β, θ / (α + β) in the C and P regions, and θ / β, (α + θ) / (α + β) in the O region consistently correlating with SA across scenarios - and these indicators strengthened with scenario complexity. The findings advance EEG-based SA assessment, aiding accurate SA measurement in real-world settings.

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来源期刊
CiteScore
4.80
自引率
8.30%
发文量
152
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