 The aim of this study is based on recent pilot studies carried out at Odense University Hospital showing that the acute changes in electroencephalographic EEG signals i.e. electrical activity inthe brain elicited by insulin-induced hypoglycemia in patients with type 1 diabetes can be reliable detected by real-time processing of these EEG signals using mathematical algorithms and state of the art noise and artifact reduction. These preliminary results also showed that the hypoglycemia-induced EEG changes are detectable 15-30 min before deterioration in cognitive function impedes an adequate response to warning. We hypothesize that these observations apply to the majority of patients with type 1 diabetes, and therefore, that it is possible to develop an automated device to detect hypoglycemic episodes by continuous real-time monitoring and processing of EEG signals. To test our hypothesis, the specific aims of the present proposal are: 