New contributions towards meal and exercise announcement-free artificial pancreas systems
- Autores: Iván Sala Mira
- Directores de la Tesis: José Luis Díez Ruano (dir. tes.), Jorge Bondía Company (dir. tes.)
- Lectura: En la Universitat Politècnica de València ( España ) en 2023
- Idioma: español
- Tribunal Calificador de la Tesis: José Luis Guzmán Sánchez (presid.), Jesús Andrés Picó Marco (secret.), Fabricio Garelli (voc.)
- Programa de doctorado: Programa de Doctorado en Automática, Robótica e Informática Industrial por la Universitat Politècnica de València
- Materias:
- Enlaces
- Tesis en acceso abierto en: RiuNet
- Resumen
Exogenous insulin infusions are vital for people with type 1 diabetes to partially make up for the inability of the pancreas to secrete insulin. However, current intensive therapies may restrict patients' quality of life. People with this disease have to constantly make decisions about insulin doses to bring glucose levels to a safe range. If unsuccessful, they may suffer from chronic and acute complications related to abnormally high and low glucose values. The automatic regulation of glucose with artificial pancreas systems promised to reduce patients' self-control burdens while improving time in normoglycemia and decreasing variability. However, these promises are fulfilled only partially. Although this technology outperforms the glycemic outcomes achieved by conventional therapies, meal intake and physical activity limit its daytime performance. Indeed, commercially available systems only can handle them with the support of the patients. For meals, patients must announce the carbohydrate content to the system. For exercise, they must notify the activity or take preventive actions like changing glucose setpoint or decreasing basal well ahead before exercise. These demands do not help reduce the patient's burden. They even can compromise the system performance when the patient misestimates the carbohydrate content, omits the meal announcement, or cannot plan the exercise event.
Hence, this thesis proposes new methods to eliminate the need for meal and exercise announcements, thus reducing patient intervention in artificial pancreas systems for a better quality of life. From a control perspective, meals and exercise can be regarded as disturbances; therefore, this thesis exploits methods from the disturbance rejection and fault accommodation literature to achieve the thesis goal. Specifically, the following three applications must be highlighted: 1) a super-twisting-based residual generator has been developed to detect unannounced meals as the first step to their compensations; 2) a sliding-mode disturbance observer has been designed to estimate the glucose meal appearance, which is fed into a bolusing algorithm to compensate the meals; 3) the internal model principle is employed to mitigate the effects of meal intakes and exercise, supplementing insulin infusions with carbohydrate recommendations.
As a result, the contributions of this thesis pave the way for the development of announcement-free artificial pancreas systems, releasing patients from the burden of diabetes management.
