安全与环境学报

基于fNIRS技术的飞行员焦虑情绪测评方法研究

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汪磊 ¹ , 高茗倩 ¹ , 洪瑞媛 ¹

安全与环境学报 | 安全管理 2026,26(6):

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安全与环境学报 |安全管理 2026 , 26 (6) :

基于fNIRS技术的飞行员焦虑情绪测评方法研究

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汪磊¹, 高茗倩¹, 洪瑞媛¹

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^1.中国民航大学安全科学与工程学院

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出版时间: 2026-06-25 doi: 10.13637/j.issn.1009-6094.2025.1233

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为了客观、有效地测量飞行员焦虑情绪状态,克服传统焦虑情绪量表评估方法的滞后性,研究引入功能性近红外光谱成像(Functional Near-Infrared Spectroscopic Imaging,fNIRS)技术,提出一种融合飞行任务的飞行员焦虑情绪测评方法。首先,选取24名飞行员作为被试,通过在全动模拟机内设计实施飞行任务情境试验,以诱发被试的焦虑情绪状态,同时采集被试fNIRS数据并记录反应时间;之后,运用最小绝对收缩和选择算子(Least Absolute Shrinkage and Selection Operator,LASSO)回归和支持向量回归等方法进行数据分析,重点分析前额叶皮层下含氧血红蛋白浓度(HbO)对不同焦虑水平的敏感性。研究结果显示:状态焦虑会在一定程度上影响被试的行为绩效,且左、右内侧额上回(Frontal_Sup_Medial_L、Frontal_Sup_Medial_R)、右侧中扣带回(Cingulum_Mid_R)的HbO指标对焦虑情绪具有较高的敏感性;基于径向基核函数优化的状态焦虑测量算法模型取得了中等拟合表现,其均方根误差(Root Mean Square Error,RMSE)为6.86,决定系数(R~2)为0.55。研究结果表明了基于fNIRS技术在模拟飞行情境中测量飞行员焦虑情绪的可行性,为下一步开发可应用的飞行员焦虑情绪测评工具提供了依据和参考。

关键词

安全卫生工程技术 / 功能性近红外光谱成像 / 状态焦虑 / 飞行安全 / 机器学习

引用本文

汪磊, 高茗倩, 洪瑞媛. 基于fNIRS技术的飞行员焦虑情绪测评方法研究. 安全与环境学报, 2026 , 26 (6) . DOI: 10.13637/j.issn.1009-6094.2025.1233

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国家自然科学基金项目

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2026年第26卷第6期

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doi: 10.13637/j.issn.1009-6094.2025.1233

首发时间：2026-07-17
出版时间：2026-06-25

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^1.中国民航大学安全科学与工程学院

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科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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