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Abstract

Information derived from ECG signals and EEG signals may be employed in combination to reliably predict the onset, or to indicate the presence of, hypoglycemia in a human patient. In one embodiment, ECG and EEG signals are processed and the information derived from them is combined to determine whether a patient suffering from diabetes is undergoing a hypoglycemic event, or whether such an event is imminent. Input data from the patient or a health care provider may also be used to increase the accuracy and reliability of the system. Detection of a hypoglycemic event by the system can result in the output of an alarm signal and/or the delivery or administration of a beneficial agent such as insulin, glucagon or diazoxide to the patient. The system may be implantable, external, or a combination of external and implantable components. The control strategy of the present system is preferably microprocessor based and/or implemented using dedicated electronics. In another embodiment, the glycemic state of the patient is continuously or relatively continuously monitored and controlled by the system. The system may contain any of a number of different types of feedback control systems for monitoring the glycemic state of a patient and controlling same, such as fuzzy logic systems, adaptive systems, reinforcement learning systems, and the like.

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First Claim