A Processing Method of EEG Signals Based on Second Generation Wavelet Transform and Blind Signal Separation
Abstract：Objective To study a processing method for EEG signals mixed with EOG and ECG signals disturbance. Methods First, the EEG was denoised by the hard threshold method, the soft threshold method, the compromise threshold method and the μ law threshold method in the second generation wavelet, and then the denoised EEG which still contained EOG and ECG was separated by fast independent component analysis ( FastICA) algorithm. Results The μ law threshold method of the second generation wavelet had better denoising effect and FastICA algorithm had more ideal separate performance. Conclusion It is an effective preprocessing method for EEG in denoising with the μ law threshold method of the second generation wavelet and then in separating disturbance of independent source with FastICA algorithm.
Keywords：EEG signalssecond generation waveletμ law threshold methoddenoisingfastICA algorithm
Publication Date：2010-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)