Aricò Pietro, Borghini Gianluca, Graziani Ilenia, Taya Fumihico, Sun Yu, Bezerianos Anastasios, Thakor Nitish V, Cincotti Febo, Babiloni Fabio
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:3001-4. doi: 10.1109/EMBC.2014.6944254.
In this study, a framework able to classify online different levels of mental workload induced during a simulated flight by using the combination of the Electroencephalogram (EEG) and the Heart Rate (HR) biosignals has been proposed. Ten healthy subjects were involved in the experimental protocol, performing the NASA - Multi Attribute Task Battery (MATB) over three different difficulty levels in order to simulate three classic showcases in a flight scene (cruise flight phase, flight level maintaining, and emergencies). The analyses showed that the proposed system is able to estimate online the mental workload of the subjects over the three different conditions reaching a high discriminability (p<.05). In addition, it has been found that the classification parameters remained stable within a week, without recalibrating the system with new parameters.
在本研究中，提出了一种通过结合脑电图（EEG）和心率（HR）生物信号来对模拟飞行期间在线诱导的不同水平的心理负荷进行分类的框架。十名健康受试者参与了实验方案，在三个不同难度级别上执行美国国家航空航天局 - 多属性任务组合（MATB），以模拟飞行场景中的三个经典场景（巡航飞行阶段、飞行高度保持和紧急情况）。分析表明，所提出的系统能够在线估计受试者在三种不同条件下的心理负荷，具有较高的可辨别性（p<.05）。此外，还发现分类参数在一周内保持稳定，无需用新参数重新校准系统。
