The EEG De-noising Research Based on Wavelet and Hilbert Transform Method

To remove the noises of EEG effectively, this paper makes the EEG De-noising research about Wavelet and Hilbert Transform. In HHT De-noising process, first, according to EEG own frequency characteristics, the EEG signals are made eight scales decomposition by using EMD algorithm, and obtain eight IMF component signals. Second, reconstruct the IMF component signals after filtering. Finally, get the EEG after De-noising. The experimental results show that HHT method can preferably eliminate the noises which mixed in the EEG. The De-noising effects of HHT and Wavelet Transform methods are compared by using the evaluation indexes. It finds that HHT method is superior to the traditional Wavelet Transform in the EEG De-noising, and its efficiency is higher.