Real-time adjustments to task difficulty during flight training are crucial for optimizing performance and managing pilot workload. This study evaluated the functionality of a pre-trained brain-computer interface (BCI) that adapts training difficulty based on real-time estimations of workload from brain signals. Specifically, an EEG-based neuro-adaptive training system was developed and tested in Virtual Reality (VR) flight simulations with military student pilots. The neuro-adaptive system was compared to a fixed sequence that progressively increased in difficulty, in terms of self-reported user engagement, workload, and simulator sickness (subjective measures), as well as flight performance (objective metric). Additionally, we explored the relationships between subjective workload and flight performance in the VR simulator for each condition. The experiments concluded with semi-structured interviews to elicit the pilots' experience with the neuro-adaptive prototype. Results revealed no significant differences between the adaptive and fixed sequence conditions in subjective measures or flight performance. In both conditions, flight performance decreased as subjective workload increased. The semi-structured interviews indicated that, upon briefing, the pilots preferred the neuro-adaptive VR training system over the system with a fixed sequence, although individual differences were observed in the perception of difficulty and the order of changes in difficulty. Even though this study shows performance does not change, BCI-based flight training systems hold the potential to provide a more personalized and varied training experience.

翻译：飞行训练中根据任务难度实时调整对优化表现和管理飞行员工作负荷至关重要。本研究评估了一个基于脑信号实时估算工作负荷来调整训练难度的预训练脑机接口（BCI）的功能性。具体而言，我们开发并测试了一个基于EEG的神经自适应训练系统，并将其应用于军事学生飞行员的虚拟现实（VR）飞行模拟训练。通过主观测量（自我报告的用户参与度、工作负荷和模拟器晕动症）与客观指标（飞行表现），将该神经自适应系统与难度渐进增加的固定序列系统进行了比较。此外，我们探讨了VR模拟器中每种条件下主观工作负荷与飞行表现之间的关系。实验结束后通过半结构化访谈收集了飞行员对神经自适应原型的体验反馈。结果显示，自适应系统与固定序列系统在主观测量和飞行表现方面均无显著差异。两种条件下，飞行表现均随主观工作负荷增加而降低。半结构化访谈表明，在简要介绍后，飞行员倾向于选择神经自适应VR训练系统而非固定序列系统，尽管在难度感知和变化顺序方面存在个体差异。尽管本研究显示表现未发生改变，但基于BCI的飞行训练系统仍具有提供更个性化和多样化训练体验的潜力。