Glucose Prediction in Type 1 and Type 2 Diabetic Patients Using Data Driven Techniques

Diabetes mellitus, commonly referred to as diabetes, is a group of metabolic diseases characterized by high blood glucose concentrations resulting from defects in insulin secretion, insulin action or both [American Diabetes Association, 2008a]. Diabetes has been classified into two major categories, namely, type 1 and type 2 diabetes. Type 1 diabetes, which accounts for only 5-10% of those with diabetes, is caused by the cell-mediated autoimmune destruction of the insulin producing β-cells in the pancreas leading to absolute insulin deficiency. On the other hand, type 2 diabetes is a more prevalent category (i.e. accounts for ~90-95% of those with diabetes) and is a combination of resistance to insulin action and an inadequate compensatory insulin secretion. The chronic hypergycemia of diabetes is associated with long-term microvascular (diabetic neuropathy, nephropathy and retinopathy) and macrovascular (coronary artery disease, peripheral arterial disease, and stroke) complications. Diabetes treatment requires the control of clinical and non-clinical variables affecting the blood glucose metabolism [American Diabetes Association, 2008b]. It is widely recognized that the tight glycemic control can prevent or reduce the progress of many long-term complications of diabetes. However, a major limiting factor in the glycemic management of type 1 and insulin treated type 2 diabetes is hypoglycemia, which is the condition where the blood glucose is much lower than normal levels. Thus, for most patients with type 1 diabetes, either using multiple insulin injections or insulin pump therapy, self-monitoring of blood glucose should be carried out three or more times a day, whereas, for patients using less frequent insulin injections or non-insulin therapies, the self-monitoring of blood glucose could be useful in achieving their glycemic targets. Recently, continuous glucose monitoring (CGM) systems have been developed which provide many significant benefits in diabetes management, especially for those patients with hypoglycaemia unawareness. Moreover, diabetes control further necessitates the monitoring and analysis of patient’s contextual information, such as medication, diet, physical activity and his overall lifestyle. For instance, in type 1 diabetic patients, exercise can cause hypoglycemia in the case where the medication dose or the carbohydrate consumption is not altered. In addition to the general guidelines that the patient follows during his daily life, several diabetes management systems have been proposed to further assist the patient in the selfmanagement of the disease. One of the most essential components of a diabetes