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针对脑电信号和其他医学信号的非平稳性，引入小波变换处理临床脑电信号的动态特性。根据脑电信号的不同节律特性，提出应用小波包变换构造不同频率特性的滤波器，提取脑电信号的４种节律，并由各种节律对应的小波系数构造动态脑电地形图。为了研究不同脑功能状态下脑电信号４种节律的动态特性，文中对两组不同临床脑电数据进行分析与比较，给出了有关的实际分析结果。实验结果表明，利用小波包分析的滤波特性，能够有效地反映临床脑电不同节律的动态特性，也为分析其他生物医学信号提供了一条新的途径。
Aiming at the nonstationarity of EEG and other medical signals, wavelet transform is introduced to deal with the dynamic characteristics of clinical EEG signals. According to the different rhythm characteristics of EEG signals, a wavelet packet transform is proposed to construct filters with different frequency characteristics, four rhythms of EEG signals are extracted, and dynamic EEG maps are constructed by wavelet coefficients corresponding to various rhythms. In order to study the dynamic characteristics of four rhythms of EEG under different brain functional states, two sets of different clinical EEG data were analyzed and compared in this paper, and the relevant actual analysis results were given. The experimental results show that the filter characteristics of wavelet packet analysis can effectively reflect the dynamic characteristics of different rhythms of clinical EEG and provide a new way to analyze other biomedical signals.