Abstract: 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.

Abstract: 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.

Abstract: A method of determining the location in time of maxima and/or minima of an oscillatory signal. The method may have application to measurement of biological signals, in particular measurement of heart rate from a pulsatile blood signal. The method includes a first stage including the steps of observation over a measurement period, identifying large local maxima or minima and computing an average interval between the identified local maxima or minima. One or more exclusion periods are located in time in the oscillatory signal, having a duration dependent on the average interval, the exclusion periods used to reject false maxima or minima. Maxima or minima may also be detected as an absolute maximum or minimum between crossing points of a fast and a slow moving average of the oscillatory signal. An exclusion period may also be used to reject false maxima or minima when crossing points are used. Apparatus for performing the method is also claimed.

Abstract: A method of determining the location in time of maxima and/or minima of an oscillatory signal. The method may have application to measurement of biological signals, in particular measurement of heart rate from a pulsatile blood signal. The method includes a first stage including the steps of observation over a measurement period, identifying large local maxima or minima and computing an average interval between the identified local maxima or minima. One or more exclusion periods are located in time in the oscillatory signal, having a duration dependent on the average interval, the exclusion periods used to reject false maxima or minima. Maxima or minima may also be detected as an absolute maximum or minimum between crossing points of a fast and a slow moving average of the oscillatory signal. An exclusion period may also be used to reject false maxima or minima when crossing points are used. Apparatus for performing the method is also claimed.