Time-Frequency Processing Method for Extracting EEG Signal Features

The article introduces a time-frequency processing method for extracting EEG signal features, referencing HHT (Hilbert-Huang Transform) resources. This technique employs Hilbert-Huang Transform-based signal processing to extract features from EEG signals. HHT is particularly effective for analyzing nonlinear and non-stationary signals, delivering high-resolution time-frequency information through its two-stage implementation: Empirical Mode Decomposition (EMD) for signal decomposition into intrinsic mode functions (IMFs), followed by Hilbert spectral analysis for instantaneous frequency calculation. Widely adopted in EEG signal processing, this method demonstrates high reliability and accuracy through proper implementation of the sifting process and spectral transformation algorithms. Therefore, when extracting EEG features, utilizing the HHT method with appropriate boundary condition handling and stopping criteria can yield more precise and detailed time-frequency characteristic information.