Models, Devices, Properties, and Verification of Artificial Pancreas Systems

Kushner, Taisa; Bequette, B. Wayne; Cameron, Faye; Forlenza, Gregory P.; Maahs, David M.; Sankaranarayanan, Sriram

doi:10.1007/978-3-030-17297-8_4

Cited by 11 publications

(7 citation statements)

References 120 publications

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“…Riddell et al [208] claimed that recently approved HCL devices/systems are appropriate for the prolonged aerobic exercise if a temporary (higher level) glucose target is set well before the start of the exercise (i.e., 45-90 min before the exercise starting time). The comprehensive description, functionalities, examples, and working methodologies of the HCL systems can be found in several recent studies [209][210][211][212][213]. The comprehensive description about the advantages and disadvantages of different controllers discussed in this study are summarized in Table 3.…”

Section: Lesson Learned and Discussionmentioning

confidence: 99%

Artificial Pancreas Control Strategies Used for Type 1 Diabetes Control and Treatment: A Comprehensive Analysis

Mehmood

Ahmad

Arif

et al. 2020

ASI

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This paper presents a comprehensive survey about the fundamental components of the artificial pancreas (AP) system including insulin administration and delivery, glucose measurement (GM), and control strategies/algorithms used for type 1 diabetes mellitus (T1DM) treatment and control. Our main focus is on the T1DM that emerges due to pancreas’s failure to produce sufficient insulin due to the loss of beta cells (β-cells). We discuss various insulin administration and delivery methods including physiological methods, open-loop, and closed-loop schemes. Furthermore, we report several factors such as hyperglycemia, hypoglycemia, and many other physical factors that need to be considered while infusing insulin in human body via AP systems. We discuss three prominent control algorithms including proportional-integral- derivative (PID), fuzzy logic, and model predictive, which have been clinically evaluated and have all shown promising results. In addition, linear and non-linear insulin infusion control schemes have been formally discussed. To the best of our knowledge, this is the first work which systematically covers recent developments in the AP components with a solid foundation for future studies in the T1DM field.

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Section: Lesson Learned and Discussionmentioning

confidence: 99%

Artificial Pancreas Control Strategies Used for Type 1 Diabetes Control and Treatment: A Comprehensive Analysis

Mehmood

Ahmad

Arif

et al. 2020

ASI

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“…The model predictive control (MPC) model utilizes the prediction model to predict the effects of proposed manipulated input changes on the desired output [ 21 ]. Note that MPC is not a single exact algorithm, it is instead composed of several algorithms tailored based on the desired goals.…”

Section: Description Of the Device Propertiesmentioning

confidence: 99%

An overview of advancements in closed-loop artificial pancreas system

Dermawan

Purbayanto

2022

Heliyon

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“…Linear dynamical models with thousands, and even millions, of dimensions have been verified [25]- [27]. Nonlinear models of realistic systems ranging from engine control systems [28]- [31] to biomedical processes have been analyzed [32]- [34]. Software tools to solve the reachability problem have been developed [26], [35], [35]- [40].…”

Section: B Reachability and Symmetry: Brief Literature Reviewmentioning

confidence: 99%

Symmetry Abstractions for Hybrid Systems and their Applications

Sibai¹,

Mitra²

2020

Preprint

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A symmetry of a dynamical system is a map that transforms one trajectory to another trajectory. We introduce a new type of abstraction for hybrid automata based on symmetries. The abstraction combines different modes in a concrete automaton A , whose trajectories are related by symmetries, into a single mode in the abstract automaton B. The abstraction sets the guard and reset of an abstract edge to be the union of the symmetry-transformed guards and resets of the concrete edges. We establish the soundness of the abstraction using a forward simulation relation (FSR) and present several examples. Our abstraction results in simpler automata, that are more amenable for formal analysis and design. We illustrate an application of this abstraction in making reachability analysis faster and enabling unbounded time safety verification. We show how a fixed point of the reachable set computation of B can be used to answer reachability queries for A , even if the latter visits an infinite and unbounded sequences of modes. We present our implementation of the abstraction construction, the fixed point check, and the map that transforms abstract reachable sets to concrete ones in a software tool. Finally, we show the advantage of our method over existing ones, and the different aspects of our abstraction, in a sequence of experiments including scenarios with linear and nonlinear agents following waypoints.

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Models, Devices, Properties, and Verification of Artificial Pancreas Systems

Cited by 11 publications

References 120 publications

Artificial Pancreas Control Strategies Used for Type 1 Diabetes Control and Treatment: A Comprehensive Analysis

Artificial Pancreas Control Strategies Used for Type 1 Diabetes Control and Treatment: A Comprehensive Analysis

An overview of advancements in closed-loop artificial pancreas system

Symmetry Abstractions for Hybrid Systems and their Applications

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