Gateau Thibault, Durantin Gautier, Lancelot Francois, Scannella Sebastien, Dehais Frederic
ISAE (Institut supérieur de l'aéronautique et de l'espace), Toulouse, France.
PLoS One. 2015 Mar 27;10(3):e0121279. doi: 10.1371/journal.pone.0121279. eCollection 2015.
Working memory is a key executive function for flying an aircraft. This function is particularly critical when pilots have to recall series of air traffic control instructions. However, working memory limitations may jeopardize flight safety. Since the functional near-infrared spectroscopy (fNIRS) method seems promising for assessing working memory load, our objective is to implement an on-line fNIRS-based inference system that integrates two complementary estimators. The first estimator is a real-time state estimation MACD-based algorithm dedicated to identifying the pilot's instantaneous mental state (not-on-task vs. on-task). It does not require a calibration process to perform its estimation. The second estimator is an on-line SVM-based classifier that is able to discriminate task difficulty (low working memory load vs. high working memory load). These two estimators were tested with 19 pilots who were placed in a realistic flight simulator and were asked to recall air traffic control instructions. We found that the estimated pilot's mental state matched significantly better than chance with the pilot's real state (62% global accuracy, 58% specificity, and 72% sensitivity). The second estimator, dedicated to assessing single trial working memory loads, led to 80% classification accuracy, 72% specificity, and 89% sensitivity. These two estimators establish reusable blocks for further fNIRS-based passive brain computer interface development.
工作记忆是驾驶飞机的一项关键执行功能。当飞行员必须回忆一系列空中交通管制指令时，这项功能尤为重要。然而，工作记忆的局限性可能会危及飞行安全。由于功能近红外光谱（fNIRS）方法在评估工作记忆负荷方面似乎很有前景，我们的目标是实现一个基于fNIRS的在线推理系统，该系统集成了两个互补的估计器。第一个估计器是一种基于MACD的实时状态估计算法，用于识别飞行员的瞬时心理状态（未执行任务与执行任务）。它不需要校准过程来进行估计。第二个估计器是一个基于在线支持向量机的分类器，能够区分任务难度（低工作记忆负荷与高工作记忆负荷）。这两个估计器对19名被安置在逼真飞行模拟器中并被要求回忆空中交通管制指令的飞行员进行了测试。我们发现，估计的飞行员心理状态与飞行员的实际状态匹配度显著高于随机水平（总体准确率为62%，特异性为58%，敏感性为72%）。致力于评估单次试验工作记忆负荷的第二个估计器，分类准确率达到80%，特异性为72%，敏感性为89%。这两个估计器为基于fNIRS的进一步被动脑机接口开发建立了可重复使用的模块。
