内模滤波与小波分解结合用于视觉诱发脑电信号提取──提取视觉诱发脑电信号的新方法之六

为了从强自发脑电ＥＥＧ背景中提取视觉诱发脑电（ＶＥＰ）信号，按内模滤波方法，利用递推最小二乘算法估计叠加后的ＶＥＰ信号的内模参数；然后以在线迭代的方式来设计具有自适应能力的内模滤波器，并将其与小波变换方法恰当结合．临床试用结果表明，此法比单纯采用按典型ＶＥＰ信号的内模参数设计内模滤波器，或单纯采用小波变换法提取ＶＥＰ信号效果更理想．

Combination of Internal Model Filtering and Wavelet Decomposition for Extracting Visual Evoked Potentials

To extract visual evoked potential (VEP) from strong electro-encephalogram (EEG) background activity, the internal model filtering is firstly performed in terms of the internal model parameters of actual VEP (obtained from the superposition of several EEG records) estimated in an on-line manner via the recursive least squares (RLS) method, then the wavelet transform technique is combined with the internal model filter developed previously. The real clinical applications have shown more desirable result by using the combined approach than by the typical VEP-based internal model filtering approach or the pure wavelet transform approach separately.