A new method: to determine the applicability of linear ICA to a given problem. (High lighted by an EEG case study applied to epilepsy)

A new method, in the form of a hypothesis test, is presented that compares the eigenvalues of a multichannel data set to eigenvalues of a synthetic mixture. The synthetic mixture is created from a set of independent components (IC´s) that have been demixed from the original data. The IC´s are then repropagated from a fictitious source space to a set of Fictitious sensors under ICA rules. The hypothesis is: if the real data has been formed in compliance to the ICA rules then its eigenvalues should be the same as the synthetic mixture formed from the repropagated IC´s. The hypothesis test is a general method and can be applied to any ICA problem. Here four common cases of epileptic seizure from electroencephalogram (EEG) records are used to highlight the method for a real case study.