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The source localization of the human brain activities is an importantresource for the recognition of cognitive state, medical disorders and a betterunderstanding of the brain in general. In this study, we have compared 51mother wavelets from 7 different wavelet families in a Stationary Wavelettransform (SWT) decomposition of an EEG signal. This process includes Haar,Symlets, Daubechies, Coiflets, Discrete Meyer, Biorthogonal and reverseBiorthogonal wavelet families in extracting five different brainwave sub-bandsfor a source localization. For this process, we used the Independent ComponentAnalysis (ICA) for feature extraction followed by the Boundary Element Model(BEM) and the Equivalent Current Dipole (ECD) for the forward and inverseproblem solutions. The evaluation results in investigating the optimal motherwavelet for source localization eventually identified the sym 20 mother waveletas the best choice followed by bior 6.8 and coif 5.

Source localization of the EEG human brainwaves activities via all the  different mother wavelets families for stationary wavelet transform  decomposition