Detecting stable phase structures in EEG signals to classify brain activity amplitude patterns

Obtaining an electrocorticograms (ECoG) signal requires an invasive procedure in which brain activity is recorded from the cortical surface. In contrast, obtaining electroencephalograms (EEG) recordings requires the non-invasive procedure of recording the brain activity from the scalp surface, which allows EEG recordings to be performed more easily on healthy humans. In this work, a technique previously used to study spatial-temporal patterns of brain activity on animal ECoG was adapted for use on EEG. The main issues are centered on solving the problems introduced by the increment on the interelectrode distance and the procedure to detect stable frames. The results showed that spatial patterns of beta and gamma activity can also be extracted from the EEG signal by using stable frames as time markers for feature extraction. This adapted technique makes it possible to take advantage of the cognitive and phenomenological awareness of a normal healthy subject.