Analysis of eeg signals to detect hypoglycaemia

A computer programmed to accept an EEG signal as an input and to perform thereon the steps of obtaining from said signal a plurality of components thereof each comprising a different band of frequencies, obtaining a measure of the varying intensity of each said component, obtaining a long time estimate of the mean of each said intensity measure, obtaining a long time estimate of the variability of each said intensity measure, normalising each said intensity measure by a process arithmetically equivalent to subtracting from the intensity measure the long time estimate of the mean and dividing the result by the long time estimate of the variability so as to generate from each band a normalised feature, using machine analysis of the normalised features to obtain a varying cost function for each time segment, classifying values ofsaid cost function according to the probability of said cost function being indicative of hypoglycemia, integrating the probabilities obtained during a selected time period, and determining in said computer that the EEG signals are indicative of hypoglycemia being present or being impending based on said integration.

A machine instruction set containing instructions for causing a compatible computer to carry out the step of receiving as an input an EEG signal and to perform thereon the steps of obtaining from said signal a plurality of components thereof each comprising a different band of frequencies, obtaining a measure of the varying intensity of each said component, obtaining a long time estimate of the mean of each said intensity measure, obtaining a long time estimate of the variability of each said intensity measure, normalising each said intensity measure by a process arithmetically equivalent to subtracting from the intensity measure the long time estimate of the mean and dividing the result by the long time estimate of the variability so as to generate from each band a normalised feature, using machine analysis of the normalised features to obtain a varying cost function, classifying values of said cost function according to the probability of said cost function being indicative of hypoglycemia, integrating the probabilities obtained during a selected time period, and determining in said computer that the EEG signals are indicative of hypoglycemia being present or being impending based on said integration.

Apparatus for detecting hypoglycemia or impending hypoglycemia by analysis of an EEG, said apparatus comprising one or more EEG measuring electrodes for gathering an EEG signal, a computer for receiving said EEG signals, said computer being programmed so as to carry out the steps of obtaining from said signal a plurality of components thereof each component comprising a different band of frequencies, obtaining a measure of the varying intensity of each said component, obtaining a long time estimate of the mean of each said intensity measure, obtaining a long time estimate of the variability of each said intensity measure, normalising each said intensity measure by a process arithmetically equivalent to subtracting from the intensity measure the long time estimate of the mean and dividing the result by the long time estimate of the variability so as to generate from each band a normalised feature, using machine analysis of the normalised features to obtain a varying cost function, classifying values of said cost function according to the probability of said cost function being indicative of hypoglycemia, integrating the probabilities obtained during a selected time period, and determining in said computer that the EEG signals are indicative of hypoglycemia being present or being impending based on said integration.