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.