Detection of Dynamic Rhythms of Electroencephalography by Using Wavelet Packets Decomposition.

摘要

Wavelet packet decomposition is used to investigate the time-varying characteristics of clinical EEG signals. On the basis of the nonstationary nature of clinical EEG rhythms, wavelet packet analysis is employed for designing filters with different frequency characteristics to detect 4 kinds of EEG rhythms. The coefficients of wavelet transformation corresponding to the rhythms are used to form the dynamic brain electrical activity mapping (DBEAM). In order to understand the dynamic rhythms of the EEG, some clinical EEG are analyzed and compared. It is indicated from the experimental results that the dynamic characteristics of clinical brain electrical activities can be provided in terms of wavelet packet decomposition.