Presentaciones a Congresos

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Artificial Pancreas: first clinical trials in Argentina
(2017-07) Sánchez-Peña, Ricardo; Colmegna, Patricio; Grosembacher, Luis; Breton, Marc; De Battista, Hernán; Garelli, Fabricio; Belloso, Waldo H.; Campos-Náñez, Enrique; Simonovich, Ventura; Beruto, Valeria; Scibona, Paula; Cherñavvsky, Daniel
"The first clinical trials using an Artificial Pancreas (AP) in Latin America have been defined in 2 stages. The first stage was carried out in November 2016 with the UVA controller (developed by the Center for Diabetes Technology and already clinically tested), and the second will be performed during the first semester of 2017 with the ARG (Automatic Regulation of Glucose) algorithm (developed by ITBA, UNQ, and UNLP in Argentina). Both tests are based on the DiAs (Diabetes Assistant) from the UVA, and are performed in the HIBA on 5 patients with Type 1 Diabetes Mellitus (T1DM), for 36 hours. For the first stage, Open-Loop (OL) insulin boluses were applied before meals and patient's physical activity was included. On the other hand, for the second stage, patients will not be involved in physical activity, but no OL insulin boluses will be injected before meals. In this work, experimental results from the first stage with the UVA controller, and preliminary results with the ARG control algorithm tested on the UVA/Padova simulator are presented. Due to the final paper deadline, the experimental results from the second stage are not included here, but will be presented at the IFAC World Congress."
Control-oriented linear parameter-varying model for glucose control in type 1 diabetes
(2016) Colmegna, Patricio; Sánchez-Peña, Ricardo; Gondhalekar, Ravi
"The contribution of this paper is a controller design oriented model of insulin-glucose dynamics in Type 1 Diabetes Mellitus (T1DM). The novelty of the proposed model is to more effectively include the time-varying nature, and also the inter-patient variability, associated with the glucose control problem. Importantly, this is achieved in a manner that straightforwardly facilitates well-known and standard controller synthesis procedures. In that way, an average Linear Parameter-Varying (LPV) model that captures the dynamics from the insulin delivery input to the subcutaneous-glucose concentration output is constructed based on the Universities of Virginia (UVA)/Padova metabolic simulator. In addition, a system-oriented reinterpretation of the classical ad-hoc 1800 rule is applied to adapt the model’s gain."
LPV control of glucose for diabetes type I
(2010) Sánchez-Peña, Ricardo; Ghersin, Alejandro S.
"This paper considers the problem of automatically controlling the glucose level in a Diabetes type I patient. Three issues have been considered: model uncertainty, timevarying/nonlinear phenomena and controller implementation. To that end, the dynamical model of the insulin/glucose relation is framed as a Linear Parameter Varying system and a controller is designed based on it. In addition, this framework allows not only a better performance than other classical methods, but also provides stability and performance guarantees. Design computations are based on convex Linear Matrix Inequality (LMI) optimization. Implementation is based on a low order controller whose dynamics adapts according to the glucose levels measured in real-time."
Unannounced meal analysis of the ARG algorithm
(2019-07) Fushimi, Emilia; Colmegna, Patricio; De Battista, Hernán; Garelli, Fabricio; Sánchez-Peña, Ricardo
"One of the main challenges in automatic glycemic regulation in patients with type 1 diabetes (T1D) is to dispense with carbohydrate counting. In this context, we propose to equip a previously introduced switched Linear Quadratic Gaus-sian (LQG) controller—the so-called Automatic Regulation of Glucose (ARG) algorithm—with an automatic switching signal generator (SSG). The ARG algorithm not only regulates the basal insulin infusion rate but also generates feedback insulin spikes at meal times, i.e., no open-loop insulin boluses are needed to mitigate postprandial glucose excursions. However, in its former version, it was required to announce the meal time. In this work, the performance of the ARG algorithm combined with the proposed SSG is assessed in silico with unannounced meals. In addition, the response of the SSG is estimated using clinical data obtained with the ARG algorithm in the first-ever artificial pancreas (AP) trials carried out in Latin America."

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