A new method: to determine the applicability of linear ica to a given problem. (high lighted by an EEG case study applied to epilepsy)
Charles Peter Unsworth, J.J. Spowart, Gillian Lawson, J. Keith Brown, B. Mulgrew, Robert A. Minns, M. Clark · 2005
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.