Emilia Fushimi

Links between physical activity, time-in-range and glucose predictability in people with type 1 diabetes

Marcos D. Saavedra, Fernando A. Inthamoussou, Emilia Fushimi, Fabricio Garelli

BACKGROUND: Type 1 diabetes (T1D) management remains particularly challenging in the presence of external disturbances such as stress or physical activity (PA). The glycemic impact of PA is still not fully understood and lacks standardized modeling approaches. This work seeks to describe …

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Real-time physical activity detection module during sensor augmented insulin pump therapy

Eleonora Manzoni, Emilia Fushimi, ELEONORA MARIA AIELLO, Zoey Li et autres

Individuals living with type 1 diabetes (T1D) face important challenges when engaging in physical activity (PA), as it necessitates careful management of blood glucose levels often through insulin adjustments and carbohydrate intake. Integrating PA detection into sensor augmented insulin pumps (SAP) is …

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Model based analytical approach for physical activity quantification in people with type 1 diabetes

Fernando Leonel Da Rosa Jurao, Emilia Fushimi, Fabricio Garelli

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Switched Controllers in Fully Closed Loop Insulin Delivery Systems: Reducing the Trade‐Off Between Prandial Control and Safety

Fernando Leonel Da Rosa Jurao, Emilia Fushimi, Fabricio Garelli

BACKGROUND: One of the main challenges in control algorithm design for full closed-loop automated insulin delivery systems is the trade-off between the effective compensation of meal-related disturbances and ensuring user safety during the postprandial and fasting periods. METHODS: This paper proposes and …

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Robust dual-hormone controller for full closed-loop glucose regulation in people with type 1 diabetes: An in silico study

Emilia Fushimi, Fernando D. Bianchi, Hernán De Battista, Fabricio Garelli

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Identification of Physical Activity Type in People with Diabetes: A Spectrogram-Based Approach

Marcos D. Saavedra, Fernando A. Inthamoussou, Emilia Fushimi, Fabricio Garelli

Background: Individuals with type 1 diabetes (T1D) require close glucose monitoring to prevent both short- and long-term complications. Physical activity (PA) is a significant source of variability in metabolic dynamics, leading to glycemic fluctuations that depend on the type, intensity, and duration …

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Personalized Model Identification for Glucose Dynamics From Clinical Data With Incomplete Inputs

Başak Özaslan, Eleonora M. Aiello, Emilia Fushimi, Francis J. Doyle et autres

OBJECTIVE: A common challenge in model identification with clinical data is incomplete and sometimes imprecise information. In this work, we provide a method to reconstruct the corrupted input data in a clinical dataset and, jointly identify the person-specific parameters of a metabolic …

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Unsupervised Classification and Glucose Prediction from Clinical Trial Data in People with Type 1 Diabetes

Marcos D. Saavedra, Fernando A. Inthamoussou, Emilia Fushimi, Fabricio Garelli

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Reinforcement Learning Adjustment of Conventional Insulin Therapy for People with Type 1 Diabetes

María Cecilia Serafini, Emilia Fushimi, Fabricio Garelli

During the last decades, the use of Automated Insulin Delivery systems (AIDs) for people with Type I Diabetes (TID) has shown great promise and improvement for glycemic control. However, most people with TID still rely on Multiple Daily Injections (MDI) therapy to …

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Online Classification of Unstructured Free-Living Exercise Sessions in People with Type 1 Diabetes

Emilia Fushimi, Eleonora M. Aiello, Sunghyun Cho, Michael C. Riddell et autres

Background: Managing exercise in type 1 diabetes is challenging, in part, because different types of exercises can have diverging effects on glycemia. The aim of this work was to develop a classification model that can classify an exercise event (structured or unstructured) …

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Safety Layer Design for Improved Glucose Regulation in Artificial Pancreas Systems

Fernando Leonel Da Rosa Jurao, Melina Montero, Emilia Fushimi, Nicolás Rosales et autres

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A Dual-Hormone Multicontroller for Artificial Pancreas Systems

Emilia Fushimi, Hernán De Battista, Fabricio Garelli

Artificial pancreas (AP) algorithms can be divided into single-hormone (SH) and dual-hormone (DH). SH algorithms regulate glycemia using insulin as their control input. On the other hand, DH algorithms also use glucagon to counteract insulin. While SH-AP systems are already commercially available, …

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