空军军医大学学报2024,Vol.45Issue(2) :230-234,240.DOI:10.13276/j.issn.2097-1656.2024.02.020

实际任务背景下脑力负荷的实时监测与评估研究现状

Research status of real-time monitoring and evaluation of mental workload under the background of real tasks

程珊 杨菁华 丛林 滕超淋 张太辉 熊凯文 党维涛 胡文东 马进
空军军医大学学报2024,Vol.45Issue(2) :230-234,240.DOI:10.13276/j.issn.2097-1656.2024.02.020

实际任务背景下脑力负荷的实时监测与评估研究现状

Research status of real-time monitoring and evaluation of mental workload under the background of real tasks

程珊 1杨菁华 2丛林 1滕超淋 1张太辉 1熊凯文 1党维涛 1胡文东 1马进1
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作者信息

  • 1. 空军军医大学航空航天医学系航空航天医学装备教研室,陕西西安 710032
  • 2. 空军工程大学基础部,陕西西安 710051
  • 折叠

摘要

脑力负荷是影响飞行员等关键岗位职业安全的重要风险因素之一,而任务中实时监测作业者的脑力负荷,对于及时识别疲劳状态及预防人因失误具有重大意义.从脑力工作负荷实时评估技术、任务中生物学信号获取方法、脑力任务设置方法与脑力状态识别模型构建等四个方面,本文分别介绍了实际工作场景脑力负荷监测的关键环节的研究现状、存在问题及对策;在此基础上,总结了实际工作场景中脑力负荷研究的重点:便携式生物信号采集技术的研发、考虑任务中不同生理模式与认知交互作用影响、多层次不同模态数据融合的脑力负荷评价模型.本文可以为实际动态脑力工作场景下任务负荷实时监测提供新思路,为疲劳状态的精准识别与事故预防提供充实的理论基础.

Abstract

Mental workload is one of the important risk factors affecting the occupational safety of key positions such as pilots.Real-time monitoring of mental workload during tasks is of great significance for identifying fatigue status in time and preventing human errors.This paper introduces the research status,existing problems and countermeasures of the key links of mental workload monitoring in actual workplace scenarios from four aspects:real-time assessment technology of mental workload,acquisition methods of biological signals in tasks,mental task setting methods,and construction of mental state recognition models.On this basis,the emphases of research on mental workload in actual workplace scenarios are summarized as follows:the research and development of portable biological signal acquisition technology,the effect of different physiological modes and cognitive interactions in tasks,and mental workload evaluation model based on multi-level and multi-modal data fusion.This paper can provide a new idea for the real-time monitoring of task load in actual dynamic mental workplace scenarios,and provide a solid theoretical basis for the accurate identification of fatigue state and accident prevention.

关键词

脑力负荷/实时监测/实际任务背景/疲劳识别/人因失误

Key words

mental workload/real-time monitoring/practical task background/fatigue recognition/human errors

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基金项目

国家自然科学基金(U1933201)

陕西省重点研发计划一般项目(2022SF-114)

出版年

2024
空军军医大学学报
第四军医大学

空军军医大学学报

CHSSCD
影响因子:0.372
ISSN:2097-1656
参考文献量41
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