title: A model for dual channel segmentation of the EEG signal.
abstract: Dual channel segmentation of the EEG signal has been developed. The purpose was to divide the signals into segments, according to information common for the two channels. The criterion for segmentation was based on the changes in the cross-spectrum of the two signals. It has been shown theoretically, as well as by simulation studies and by analysis of real EEG data that this method is sensitive to changes common for both channels, whereas segmentation does not occur as a result of changes in each channel separately.
authors.affiliation: Department of Biomedical Engineering, Technion, Haifa, Israel.
authors.forename: I
authors.initials: I
authors.lastname: Gath
authors.forename: A
authors.initials: A
authors.lastname: Michaeli
authors.forename: C
authors.initials: C
authors.lastname: Feuerstein
mesh_terms: D000465:Algorithms; D004569:Electroencephalography; D004827:Epilepsy / Q000503:physiopathology; D006801:Humans; D008433:Mathematics; D008962:Models, Theoretical