The application of wavelet packets to the analysis of dynamic electroencephalogram

In this paper we propose a new method for dynamic analysis of EEG signals. Multiresolution decomposition is used to investigate the transition of clinical EEG signals. Wavelet packet transformation is investigated for designing filters with different frequency characteristics in order to detect different kinds of EEG rhythms. Real EEG signals with different brain function states are tested and analyzed. It is shown from the experimental results that the dynamic characteristics of clinical brain electrical activities can be demonstrated by using the wavelet transformation. The method presented in this paper also proposes a new way for the analysis of other biomedical signals.