An objective study into single vs multiple channel brain signal analysis using realistic ictal EEG

Information on electromagnetic (EM) brain function can be extracted from electroencephalographic (EEG) recordings through various signal processing techniques and it is usually assumed that this requires multiple simultaneous recordings. However, sometimes only a single channel of EEG is available. Here we objectively assess a novel methodology which exploits only a single measurement channel to extract information of interest. The method relies on a combination of a nonlinear dynamical systems framework and constrained Independent Component Analysis (ICA) which incorporates prior information into the process. We use synthetically generated ictal EEG, composed of real multichannel EEG onto which is superimposed known “seizure-like” activity, at different SNR levels, through an equivalent current dipole (ECD) model. We show that the method can extract desired information from single channels with a reasonable accuracy even at very small SNR and from channels distant from the focus of the activity