Figure 2.

Block diagram of WICA for automatic EEG artifact removal. Raw data to be removed are appended to the artifact samples first. The next stage is wavelet decomposition via channel by channel, in which data are projected into n-dimensional space where ICA is performed. Subsequently, n-m neural-related WICs are used for n-channel wavelet coefficient reconstruction, whereas m artifactual WICs are automatically recognized by correlation analysis. Finally, the n-channel EEG signal without artifacts is reconstructed by inverse DWT from n-channel wavelet coefficient.