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飞机驾驶舱显示界面脑力负荷判别预测生理模型
引用本文:陆崑,卫宗敏,庄达民,完颜笑如.飞机驾驶舱显示界面脑力负荷判别预测生理模型[J].北京航空航天大学学报,2016,42(4):685-693.
作者姓名:陆崑  卫宗敏  庄达民  完颜笑如
作者单位:中国民航管理干部学院航空器适航审定系,北京,100102;北京航空航天大学航空科学与工程学院,北京,100083
基金项目:国家“973”计划(2010CB734104);民航安全能力建设资金(MHRD20141010)~~
摘    要:针对飞机驾驶舱显示界面脑力负荷的客观判别预测问题,综合采用事件相关电位(ERP)、心电图(ECG)和眼电图(EOG)3类生理测量技术,结合主观测评法和绩效测评法,在同一飞行实验任务中开展脑力负荷的实验测量与数学建模研究。实验结果表明:随着脑力负荷的增加,ERP测量技术中的失匹配负波(MMN)成分的峰值幅度(在Fz电极处)显著增加,P3a成分的峰值(在Fz电极处)显著降低;ECG测量技术中的心率变异性指标全部窦性心搏RR间期(简称RR间期)的标准差(SDNN)的数值显著降低;EOG测量技术中的眨眼次数显著降低。在此基础上,基于Bayes判别方法构建了脑力负荷判别预测生理综合评估模型,并将生理综合评估模型判别结果与NASA任务负荷指数(NASA_TLX)量表判别结果进行了比较,生理综合评估模型判别结果略高于NASA_TLX判别结果。该模型为飞机驾驶舱显示界面脑力负荷状态的客观、实时判定和预测提供了一种新的方法,同时也为中国正在研发的新型战斗机和大型客机驾驶舱显示界面中的人为因素适航审定工作提供了新的符合性验证工具。

关 键 词:驾驶舱  显示界面  脑力负荷  生理测量  预测模型  适航审定
收稿时间:2015-04-24

Integrated physiological model for mental workload assessment and prediction of aircraft flight deck display interface
LU Kun,WEI Zongmin,ZHUANG Damin,WANYAN Xiaoru.Integrated physiological model for mental workload assessment and prediction of aircraft flight deck display interface[J].Journal of Beijing University of Aeronautics and Astronautics,2016,42(4):685-693.
Authors:LU Kun  WEI Zongmin  ZHUANG Damin  WANYAN Xiaoru
Institution:LU Kun;WEI Zongmin;ZHUANG Damin;WANYAN Xiaoru;Development of Aircraft Airworthiness Certification,Civil Aviation Management Institute of China;School of Aeronautic Science and Engineering,Beijing University of Aeronautics and Astronautics;
Abstract:This paper focuses on the objective discrimination and prediction of mental workload of the aircraft flight deck display interface. By three physiological measurement methods of event-related potentials (ERP), electrocardiograph (ECG) and electro-oculogram (EOG), as well as subjective evaluation and performance evaluation, both experimental measurement and mathematical modeling of mental workload were carried out under the same flight simulation task conditions. The experimental results indicate that as the mental workload increased, the peak amplitude of the mismatch negativity (MMN) at Fz significantly increased, while the peak amplitude of P3a at Fz, the standard deviation of normal-to-normal RR intervals (SDNN) value, and the eye blink numbers significantly decreased. Based on the results of experimental measurement, the Bayesian discrimination analysis method was employed to construct the mental workload discrimination model of the aircraft flight deck display interface. The integrated physiological model showed a higher accuracy in the discrimination and prediction of mental workload compared with NASA_TLX. Thus, this model provides not only a new approach for the objective and real-time discrimination and prediction of mental workload of the aircraft cockpit display interface, but also a new compliance verification tool for the human factor airworthiness certification of flight deck display interface of the new generation fighter aircraft and large passenger aircraft.
Keywords:flight deck  display interface  mental workload  physiological measurement  prediction model  airworthiness certification
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