Power Spectrum Extraction of EEG Signals During Left/Right Hand Movements in Male and Female Subjects

During my undergraduate graduation project, I conducted research on extracting power spectra from EEG signals during left/right hand movements in male and female subjects. The study employed a frequency-division extraction approach, specifically isolating distinct characteristics during left-hand and right-hand movements. The implementation involved developing a MATLAB program with modular functions including: - Signal preprocessing using bandpass filters (0.5-45 Hz) to remove artifacts - Frequency band separation through digital filtering techniques (alpha, beta, and gamma bands) - Power spectrum calculation utilizing Fast Fourier Transform (FFT) algorithms with Hanning windowing - Feature extraction routines comparing spectral power differences between movement conditions The program architecture was designed for clarity and educational value, with commented code sections explaining each processing step. Complete EEG datasets from movement experiments were included along with comprehensive program documentation covering algorithm parameters and implementation details. The research objective was to investigate correlations between EEG signals and human movement, providing foundational insights for neuroscience studies. By analyzing power spectrum variations across different movement states, we gained understanding of neural mechanisms underlying human motor control. The findings contribute significantly to comprehending human movement behavior and neurological functions, offering valuable references for subsequent research in related fields. The methodology demonstrates practical applications of signal processing techniques in biomedical research, particularly in neural signal analysis and brain-computer interface development.