An attempt is made to develop a method for automatic artifact selection in
an electroencephalogram. Wavelet transform and artificial neural networks
are combined with the analysis of statistical properties, based on the
fractional dimension dynami
cs. Application of the method to experimental
EEG signals showed that it can increase the reliability of artifacts selection.
