Model-based personalization scheme of an artificial pancreas for Type 1 diabetes applications

• Published in: 2013 American Control Conference pp. 2911 - 2916
• Main Authors: Joon Bok Lee, Dassau, Eyal, Seborg, Dale E., Doyle, Francis J.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2013
• Subjects: Blood; closed-loop; control-relevant modeling; Diabetes; Insulin; insulin feedback; internal model control (IMC); Measurement; Noise; proportional-integral-derivative (PID) control; Sugar; Tuning; type 1 diabetes mellitus (T1DM)
• ISBN: 1479901776; 9781479901777
• ISSN: 0743-1619
• DOI: 10.1109/ACC.2013.6580276

Automated controllers designed to regulate blood glucose concentrations in people with Type 1 diabetes mellitus (T1DM) must avoid hypoglycemia (blood glucose <;70 mg/dl) while minimizing hyperglycemia (>180 mg/dl), a challenging task. In this paper, a model-based control design approach with a personalized scheme based on readily available clinical factors is applied to a linearized control-relevant model of subject insulin-glucose response profiles. An insulin feedback strategy is included with specific personalization settings and variations in a tuning parameter, τ c . The control strategy is challenged by an unannounced meal disturbance with 50 g carbohydrate content. A set of metrics are introduced as a method of evaluating the performance of different controllers. In-silico simulations of ten subjects in the Food and Drug Administration accepted Universities of Virginia and Padova metabolic simulator indicate that the personalization strategy with a τ c setting of 270 minutes gives very good controller performance. Post-prandial glucose concentration peaks of 183 mg/dl were achieved with 97% of the total simulation time spent within a safe glycemic zone (70-180 mg/dl), without hypoglycemic incidents and without requiring a time-consuming model identification process.