Method for analyzing dynamic characteristic of EEG Functional connectivity related to driving fatigue

Disclosed is a method for analyzing dynamic characteristics of EEG functional connectivity related to driving fatigue including: using independent component analysis and wavelet packet transformation to preprocess EEG data; constructing the preprocessed EEG data into a temporal brain network with dynamic characteristics based on a sliding window method; measuring a spatiotemporal topology of the temporal brain network based on a temporal efficiency analysis framework; and performing statistical analysis on the spatiotemporal topology of the temporal brain network to obtain a correlation between behaviors related to driving fatigue and dynamic characteristics of the temporal brain network, wherein the temporal brain network with dynamic characteristics is constructed by introducing the temporal characteristic into the static network of the driving fatigue, a spatiotemporal recombination rule of the temporal brain network during the driving fatigue can be obtained through statistical analysis, thus having a more accurate analysis result, and being beneficial for disclosing a more critical dynamic characteristic of information transmission function reorganization among brain regions related to the driving fatigue on a fine temporal scale.