 A number of studies have characterized the changes in the EEG that results from hypoglycemia 16-20, but none have proposed a method of processing and testing in real-time. With a device, which can perform real-time monitoring and processing of EEG signals and automatically detect and warn the patient of hypoglycemia-induced EEG changes, it would be possible for the patient to avoid severe neuroglypenic symptoms e.g. by ingestion of carbohydrates. The construction of an EEG-based hypoglycemia alarm system must fulfill the following criteria. First, the device should be able to distinguish hypoglycemia-induced EEG changes from normal changes in EEG, noise and artifacts with high sensitivity and specificity using a mathematical algorithm that classifies the EEG in real-time. Second, these EEG changes should be observed in the majority of insulin-treated diabetic patients during hypoglycemia. Third, there should be a window between hypoglycemia-induced EEG changes and severe cognitive impairment. Moreover, the device should be fully compatible with normal everyday activities. Thus, the electrodes should be thin and implanted subcutaneously, and the monitoring and processing unit should be small, have sufficient battery power, and capable of communicating with a PDA or cell phone. 