Using dynamical embedding to isolate seizure components in the ictal EEG

Presents a system for isolating seizure components in segments of ictal EEG. Through the implementation of independent component analysis (ICA), we first separate multi-channel EEG segments into their underlying components. We then employ the method of dynamical embedding to extract a dynamic complexity measure for each independent component. By observing the change in complexity, coupled with the topographical distribution of each component, we can identify those seizure-related components extracted by the ICA process. We have applied the method to four seizure EEG segments and are able to identify probable seizure components in each case. As a proof of principle study, the method indicates that ICA coupled with dynamical embedding may be useful as a tool in pre-processing seizure EEG segments.