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Evaluating Pressure Induced Sensor Attenuation Detection in Artificial Pancreas Algorithms

Project Description

Artificial pancreas technology relies on Continuous Glucose Monitoring sensors that measure blood glucose levels and use  computer programs to adjust the amount of insulin being delivered by a pump to the patient. The algorithms controlling the artificial pancreas system have a predictive capability that enables them to adjust the ongoing rate of insulin delivery based on the measured sensor glucose levels. However, they  can also fail, as the program and sensor can both malfunction, leading to potential serious patient outcomes.   We propose to analyze existing artificial pancreas control algorithms in two distinct ways. First, we will study real patient data to determine whether the algorithm is capable of accurately predicting Pressure Induced Sensor Attenuation events. We will also find aberrations in the data that indicate sensor failure that could lead to pump control failure. To find additional issues with artificial pancreas control, we will develop simulated data sets that effectively “trick” the control algorithm, to see what can induce failure. This will drive the development of safer pump control programs.

Area of Study

Metabolism and Endocrinology


Adolescents; Adults; School Age Children; Young Adults


Bioengineering; Clinical Trials

Disease or Symptom




Mentor Location

Barbara Davis Center 1775 Aurora Ct Aurora, CO 80045

Mentor Contact Number


Mentor Email


Mentor Name

Maahs, David

Funding Department/Program




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Created at 11/13/2015 11:58 AM by Ross, Randy
Last modified at 8/14/2019 12:56 PM by Zoghby, Caitlin