EEG filtering based on machine learning simulation design analysis

Abstract

The pretreatment of collected electroencephalogram (EEG) signals is quite important in processing EEG signals. By adopting the knowledge of signal analysis and processing based on Matlab platform, the impact of different wavelet basis functions on the decomposition and reconstruction of EEG signals is simulated. Then EEG signals are decomposed and reconstructed in a five-layer multi-scale way by using db5 wavelet basis function, and the vibration of the signals is simulated. By comparing the simulation results of denoising under different thresholds with that under low-pass filters, the results of specific frequency bands are analyzed. The research shows that in the process of denoising EEG signals, wavelet analysis can extract EEG micro signals effectively, and thus it has important value in the practical use of EEG in broader fields. © 2014 Springer Science+Business Media New York.