Cognitive load estimation in VR flight simulator

This paper discusses the design and development of a low-cost virtual reality (VR) based flight simulator with cognitive load estimation feature using ocular EEG signals. Focus is on exploring methods to evaluate pilot’s interactions aircraft by means quantifying perceived under different task scenarios. Realistic target tracking context battlefield designed in VR. Head mounted eye gaze tracker headset are used for acquiring pupil diameter, fixation, direction theta, alpha, beta band power data real time. We developed an AI agent model VR created scenarios piloted aircraft. To estimate load, we low-frequency diameter variations, fixation rate, distribution pattern, signal-based index engagement index. compared physiological measures workload standard user’s inceptor control-based metrics. Results simulation study indicate that metrics discussed have strong association difficulty.