Rensselaer researchers have developed a simple algorithm designed to safely modulate insulin delivery and prevent hypoglycemia in outpatients using a continuous glucose monitor (CGM) and insulin pump. This technology applies a Kalman filter to the readings from a CGM to estimate the value and rate of change of the glucose level. This estimate is then used to predict current or impending low blood glucose levels. Then it suspends baseline insulin delivery if the algorithm identifies a risk of hyperglycemia. The algorithm also incorporates a set of safety rules that must be met before insulin delivery is suspended. This technology could help patients with type 1 diabetes maintain better control of their blood sugar level to prevent the sluggishness, coma and seizures associated with hypoglycemia. Applications include continuous glucose monitoring to help prevent hypoglycemia in patients using an insulin pump. Advantages of the technology include: the capability for outpatient monitoring - no similar algorithms have been tested in the US in outpatient trials; improved performance compared to simple threshold shutoff; simplicity of the algorithm.