A self-organising fuzzy estimator for hypoglycaemia monitoring in diabetic patients

Hypoglycaemia is the most common complication experienced by patients with Type 1 insulin dependent diabetes mellitus (IDDM). During hypoglycaemia, physiological parameter changes occur in patients, due to the sympathetic nervous system, of which the most predominant parameters are sweating and heart rate. Non-invasive monitoring and detecting hypoglycaemia in diabetic patients requires simultaneous measurements of body functions such as sweating, breathing patterns, recording EEG and heart rate. A hypoglycaemic monitor has been developed to help the physician predict the onset of hypoglycaemia. This paper describes the development of a fuzzy estimator as the main software engine of the hypoglycaemic monitor. The fuzzy estimator consists of an initial static estimator and has been expanded using self organisation to enhance it´s flexibility