van Weelden Evy, Alimardani Maryam, Wiltshire Travis J, Louwerse Max M
Department of Cognitive Science & Artificial Intelligence, Tilburg University, the Netherlands.
Department of Cognitive Science & Artificial Intelligence, Tilburg University, the Netherlands.
Appl Ergon. 2022 Nov;105:103838. doi: 10.1016/j.apergo.2022.103838. Epub 2022 Aug 5.
This paper systematically reviews 20 years of publications (N = 54) on aviation and neurophysiology. The main goal is to provide an account of neurophysiological changes associated with flight training with the aim of identifying neurometrics indicative of pilot's flight training level and task relevant mental states, as well as to capture the current state-of-art of (neuro)ergonomic design and practice in flight training. We identified multiple candidate neurometrics of training progress and workload, such as frontal theta power, the EEG Engagement Index and the Cognitive Stability Index. Furthermore, we discovered that several types of classifiers could be used to accurately detect mental states, such as the detection of drowsiness and mental fatigue. The paper advances practical guidelines on terminology usage, simulator fidelity, and multimodality, as well as future research ideas including the potential of Virtual Reality flight simulations for training, and a brain-computer interface for flight training.
本文系统回顾了20年来关于航空与神经生理学的54篇出版物。主要目标是阐述与飞行训练相关的神经生理变化,以识别表明飞行员飞行训练水平和与任务相关心理状态的神经测量指标,并掌握飞行训练中(神经)工效学设计与实践的当前技术水平。我们确定了多个训练进展和工作量的候选神经测量指标,如额叶θ波功率、脑电图参与指数和认知稳定性指数。此外,我们发现几种类型的分类器可用于准确检测心理状态,如困倦和精神疲劳的检测。本文提出了关于术语使用、模拟器逼真度和多模态的实用指南,以及未来的研究思路,包括虚拟现实飞行模拟用于训练的潜力,以及用于飞行训练的脑机接口。