Sliding-mode disturbance observers for an artificial pancreas without meal announcement

[EN] Carbohydrate counting is not only a burden for patients with type 1 diabetes, but estimation errors in meal announcement could also degrade the outcomes of the current hybrid closed-loop systems. Therefore, removing meal announcement is desirable. A novel control system is addressed here to fac...

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Detalles Bibliográficos
Autores: Sala-Mira, Iván|||0000-0002-6228-5190, Diez, José-Luís|||0000-0002-5659-1212, Ricarte Benedito, Beatriz|||0000-0001-8094-1908, Bondía Company, Jorge|||0000-0001-7286-3719
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/159149
Acceso en línea:https://riunet.upv.es/handle/10251/159149
Access Level:acceso abierto
Palabra clave:Unannounced artificial pancreas
Sliding mode observer
Meal detection
Postprandial control
MATEMATICA APLICADA
INGENIERIA DE SISTEMAS Y AUTOMATICA
Descripción
Sumario:[EN] Carbohydrate counting is not only a burden for patients with type 1 diabetes, but estimation errors in meal announcement could also degrade the outcomes of the current hybrid closed-loop systems. Therefore, removing meal announcement is desirable. A novel control system is addressed here to face postprandial control without meal announcement. The proposed system grounds on two applications of the sliding mode observers in dealing with disturbances: first, the equivalent output technique is used to reconstruct the meal rate of glucose appearance via a first order sliding mode observer; second, a super-twisting -based residual generator is used to detect the meals. Subsequently, a bolusing algorithm uses the information of the two observers to trigger a series of boluses based on a proportional-derivative-like strategy. An in silico validation with 30 patients in a 30-day scenario reveals that the meal detector algorithm achieves a low rate of false positives per day (0.1 (0.1), mean (SD)) and a detection time of 28.5(6.2) min. Additionally, the bolusing algorithm fulfills a non-statistically different mean glucose than the hybrid counterpart with bolus misestimation (146.69 (12.20) mg/dLvs. 144.28 (11.01) mg/dL,p>0.05), without increasing hypoglycemia (0.029 (0.077) vs. 0.004 (0.014)%, p > 0,05), although at the expense of a slightly higher time in hyperglycemia (22.51(8.72) % vs. 18.65 (7.89)%, p <0.05) due to the conservative tuning of the bolusing algorithm for the sake of safety.