基于小波包分解的时变脑电节律提取

研究从时变非平稳脑电信号中提取脑电动态节律的新方法。首先用小波包分解构造不同频率特性的时变滤波器以提取各种时变的脑电节律，研究临床脑电信号瞬时变化。在此基础上测试并分析两种不同功能状态下的脑电信号，并由此构造各种节律的时变脑电地形图。实验结果表明，小波包分解可以有效提取脑电不同节律的动态特性，此方法也适用于分析其他生物医学信号。

Extracting Time-Varying Rhythms of EEG Signal Based on Wavelet Packet Decomposition

A new method for detecting time-varying rhythms of nonstationary electroencephalogram is studied. Firstly, wavelet packet transformation is used to design the filters with different frequency characteristics to extract different kinds of dynamic EEG rhythms, so that it can be used to investigate the instantaneous transition of clinical EEG signals. On this basis, two actual EEG signals with different brain function states are tested and analyzed. The parameters of the wavelet packet transform corresponding to the rhythms are developed to reconstruct the time-varying electrical brain activity mapping (TVEBAM). From the experimental results, the dynamic characteristics of clinical brain electrical activities can be extracted by using wavelet packet decomposition. The method can be used as a new way for analyzing other biomedical signals.