MATLAB and Time-Frequency Analysis Toolbox

In our MATLAB implementation, we have developed specialized programs using the time-frequency analysis toolbox to process EEG spectrograms and raw EEG signals. Time-frequency analysis is a technique that decomposes signals into time and frequency components, which proves particularly valuable for studying both spectral characteristics and temporal properties of brainwave patterns. Our implementation incorporates multiple time-frequency analysis methods including wavelet transform (using functions like cwt for continuous wavelet analysis) and short-time Fourier transform (implemented through spectrogram function with configurable windowing parameters), providing more accurate and comprehensive signal characterization. The codebase features adaptive parameter optimization algorithms that automatically adjust analysis windows based on signal characteristics. Additionally, our programs include graphical user interfaces (built using MATLAB App Designer) for visualizing analytical results, along with modular tools for data preprocessing (such as filtering and artifact removal) and statistical analysis modules capable of performing hypothesis testing and correlation studies. We believe these well-documented programs with commented configuration parameters will significantly assist researchers and medical professionals in the field of EEG signal processing and neurological studies.