Automated seizure detection from within an electroencephalogram (EEG) by instrumental means employs novel algorithms within software, using specific measurements of individual waves in trains, rather than any “bulk” process. The acquired signal is filtered, the wave shapes are individually described within a number of parallel runs using a variety of parameters, then criteria (including regularity criteria) are calculated and applied in order to create raw detection results. Finally the raw results are “integrated” for display. As a result, reported seizures closely follow the incidence and duration of seizures detected by trained clinicians. The invention is useful in intensive-care monitoring of EEGs from neonates and in EEG monitoring in general.
