EEG Analysis Based On Wavelet Transform

With the improvement of daily life, the quality of our life has taken great change in recent years. Meanwhile, the development of EEG has gotten quite great progress; the demand of EEG is more and more high. EEG automatic identify is the key technology. With the development of EEG, many automatic identify methods come forth simultaneously.Something about EEG is introduced in this paper, including the ingredient of EEG and the process of EEG visual analysis. Moreover, the principal of wavelet analysis is introduced in this paper. Especially the deep analysis to continuous wavelet transform(CWT), discrete wavelet transform and multi-resolution analysis are given in this paper.This paper uses wavelet transform to study the EEG automatic identity, trying to enlarge the EEG automatic identify from epilepsy to more disorders. Adapting wavelet basis has been put forward by the author. CWT has been used to analyze EEG in order to choose the most fitness wavelet basis. In the progress of automatic identify, the method deal with the spike wave, sharp wave and slow wave in the first instance, then use the adapting wavelet basis method to identify the element of the EEG signal and give the analysis report and diagnosis. Simulation results show the feasibility and the validity of the method.