Analysis of Pilot’s Training Effect Based on EEG Signal

In order to evaluate the effectiveness of EEG entropy value to reflect the pilot’s brain activity, this study collected the EEG data of pilot in the flight training simulator which can simulate the airfield traffic pattern, and the approximate entropy algorithm was used to process the EEG data. The analysis compares EEG signal activity characteristics of the pilot in different flight stages, different meteorological conditions and different training levels using t test and linear regression method. The results showed that the EEG entropy can be used to evaluate the training effect of pilots, when the entropy reaches a fixed value, the next stage of training can be carried out. Good flight training effect can effectively reduce flight accidents caused by human factors and improve flight safety.