Abstract: A system for adjusting blood glucose level including an insulin delivery device configured to release insulin into the body of a person, and an EEG monitor having an EEG sensing part including EEG electrodes. The EEG monitor can be arranged in the ear region of the person with the EEG sensing part arranged subcutaneously at the scalp or arranged in the ear canal. The EEG monitor includes an EEG signal processor arranged at the ear and adapted for identifying onset of hypoglycemia. The system further includes a wireless link between the EEG monitor and the insulin delivery device. The EEG monitor is configured to submit a warning signal to the insulin delivery device if an upcoming onset of hypoglycemia is identified. The warning message will cause the insulin delivery device to restrict insulin delivery for a predetermined time, and a warning is provided to the person or to a caregiver.

Abstract: An EEG monitor (1) including electrodes (17) adapted for capturing EEG signals and a signal processing part (11) which is adapted for analyzing and classifying the EEG signals captured. The signal processing part (11) is adapted for identifying electrical signals captured by the electrodes (17) that are derived from muscular activity related to the process of chewing.

Abstract: Apparatus for detecting hypoglycemia or impending hypoglycemia by analysis of an EEG comprises at least one EEG measuring electrode (10) for gathering an EEG signal and a computer (12) for receiving said EEG signals programmed to obtain a plurality of signal components each comprising a different band of frequencies, obtain a measure of the varying intensity of each said component, obtain a long time estimate of the mean of each intensity measure, obtain a long time estimate of the variability of each intensity measure, normalise each intensity measure e.g.

Abstract: An EEG monitor (1) including electrodes (17) adapted for capturing EEG signals and a signal processing part (11) which is adapted for analyzing and classifying the EEG signals captured. The signal processing part (11) is adapted for identifying electrical signals captured by the electrodes (17) that are derived from muscular activity related to the process of chewing.

Abstract: A system for adjusting blood glucose level including an insulin delivery device configured to release insulin into the body of a person, and an EEG monitor having an EEG sensing part including EEG electrodes. The EEG monitor can be arranged in the ear region of the person with the EEG sensing part arranged subcutaneously at the scalp or arranged in the ear canal. The EEG monitor includes an EEG signal processor arranged at the ear and adapted for identifying onset of hypoglycemia. The system further includes a wireless link between the EEG monitor and the insulin delivery device. The EEG monitor is configured to submit a warning signal to the insulin delivery device if an upcoming onset of hypoglycemia is identified. The warning message will cause the insulin delivery device to restrict insulin delivery for a predetermined time, and a warning is provided to the person or to a caregiver.

Abstract: Apparatus for detecting hypoglycemia or impending hypoglycemia by analysis of an EEG comprises at least one EEG measuring electrode (10) for gathering an EEG signal and a computer (12) for receiving said EEG signals programmed to obtain a plurality of signal components each comprising a different band of frequencies, obtain a measure of the varying intensity of each said component, obtain a long time estimate of the mean of each intensity measure, obtain a long time estimate of the variability of each intensity measure, normalise each intensity measure e.g.

Abstract: Features indicative of hypoglycaemia in EEG signals are detected by: —dividing EEG signals into a sequence of time segments, —for each time segment determining whether a pattern of EEG signals is present which is indicative of hypoglycaemia and, where a pattern of EEG signals indicative of hypoglycaemia is determined to be present in a time segment, recording this as an event, —integrating the number of events recorded during a selected number of preceding time segments which together constitute a selected time period, optionally in a time weighted manner, and—determining that the EEG signals are indicative that hypoglycaemia is present based on said integration when the said integrated number of events exceeds a preset threshold number and/or when there exists a threshold level of matching between a curve of said integration over time and a previously established ideal model of said curve indicative of hypoglycaemia.

Abstract: Apparatus for capturing EEG signals comprising an implantable signal capture unit (34) connected to a proximal end of at least one implantable electrode (32) is implanted by passing a tubular guide sheath (24,26) along a subcutaneous path from an implantation site, passing the distal end of a said electrode through said guide sheath to bring said signal capture unit to said implantation site, and withdrawing said guide sheath from the electrode whilst progressively axially splitting the guide sheath to enable its removal. The signal capture unit may have a housing having at least two electrode contacts on its for capturing EEG signals in operative connection with circuitry within said housing for receiving said EEG signals and for wireless transmission thereof for reception at a location exterior to the body of the patient.

Abstract: Features indicative of hypoglycaemia in EEG signals are detected by: —dividing EEG signals into a sequence of time segments, —for each time segment determining whether a pattern of EEG signals is present which is indicative of hypoglycaemia and, where a pattern of EEG signals indicative of hypoglycaemia is determined to be present in a time segment, recording this as an event, —integrating the number of events recorded during a selected number of preceding time segments which together constitute a selected time period, optionally in a time weighted manner, and—determining that the EEG signals are indicative that hypoglycaemia is present based on said integration when the said integrated number of events exceeds a preset threshold number and/or when there exists a threshold level of matching between a curve of said integration over time and a previously established ideal model of said curve indicative of hypoglycaemia.