Fast Memory Response Behavior Performance Prediction based on EEG Signals

In fast memory response training, predicting behavioral performance through EEG data can provide a technical basis for people selection and decision-making assistance. Therefore, this article models the relationship between EEG data and behavioral performance, and constructs a correlation model between EEG and behavior. The research results indicate that the human-machine operation performance prediction model based on the mental fatigue index and EEG characteristics has a confidence level of over 80%. Using a logistic regression model, the probability of predicting the correctness of manipulation based on the coupling of mental fatigue index and EEG fatigue evaluation index system can reach 89.85%; Using a transfer learning neural network model based on multi head attention mechanism, the probability of predicting perceptual response time based on the coupling of mental fatigue index and EEG fatigue evaluation index system can reach 83.3%.