A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems

The use of automated insulin delivery systems has become a reality for people with type 1 diabetes (T1D), with several hybrid systems already on the market. One of the particularities of this technology is that the patient is in the loop. People with T1D are the plant to control and also a plant ope...

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Autores principales:	Aleix Beneyto, Vicenç Puig, B. Wayne Bequette, Josep Vehi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	artificial pancreas hybrid automaton Kalman filter patient in the loop type 1 diabetes Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/72f58f5d88a944ca8eaa771f1af2db1f
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spelling	oai:doaj.org-article:72f58f5d88a944ca8eaa771f1af2db1f2021-11-11T19:07:26ZA Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems10.3390/s212171171424-8220https://doaj.org/article/72f58f5d88a944ca8eaa771f1af2db1f2021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7117https://doaj.org/toc/1424-8220The use of automated insulin delivery systems has become a reality for people with type 1 diabetes (T1D), with several hybrid systems already on the market. One of the particularities of this technology is that the patient is in the loop. People with T1D are the plant to control and also a plant operator, because they may have to provide information to the control loop. The most immediate information provided by patients that affects performance and safety are the announcement of meals and exercise. Therefore, to ensure safety and performance, the human factor impact needs to be addressed by designing fault monitoring strategies. In this paper, a monitoring system is developed to diagnose potential patient modes and faults. The monitoring system is based on the residual generation of a bank of observers. To that aim, a linear parameter varying (LPV) polytopic representation of the system is adopted and a bank of Kalman filters is designed using linear matrix inequalities (LMI). The system uncertainty is propagated using a zonotopic-set representation, which allows determining confidence bounds for each of the observer outputs and residuals. For the detection of modes, a hybrid automaton model is generated and diagnosis is performed by interpreting the events and transitions within the automaton. The developed system is tested in simulation, showing the potential benefits of using the proposed approach for artificial pancreas systems.Aleix BeneytoVicenç PuigB. Wayne BequetteJosep VehiMDPI AGarticleartificial pancreashybrid automatonKalman filterpatient in the looptype 1 diabetesChemical technologyTP1-1185ENSensors, Vol 21, Iss 7117, p 7117 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial pancreas hybrid automaton Kalman filter patient in the loop type 1 diabetes Chemical technology TP1-1185
spellingShingle	artificial pancreas hybrid automaton Kalman filter patient in the loop type 1 diabetes Chemical technology TP1-1185 Aleix Beneyto Vicenç Puig B. Wayne Bequette Josep Vehi A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems
description	The use of automated insulin delivery systems has become a reality for people with type 1 diabetes (T1D), with several hybrid systems already on the market. One of the particularities of this technology is that the patient is in the loop. People with T1D are the plant to control and also a plant operator, because they may have to provide information to the control loop. The most immediate information provided by patients that affects performance and safety are the announcement of meals and exercise. Therefore, to ensure safety and performance, the human factor impact needs to be addressed by designing fault monitoring strategies. In this paper, a monitoring system is developed to diagnose potential patient modes and faults. The monitoring system is based on the residual generation of a bank of observers. To that aim, a linear parameter varying (LPV) polytopic representation of the system is adopted and a bank of Kalman filters is designed using linear matrix inequalities (LMI). The system uncertainty is propagated using a zonotopic-set representation, which allows determining confidence bounds for each of the observer outputs and residuals. For the detection of modes, a hybrid automaton model is generated and diagnosis is performed by interpreting the events and transitions within the automaton. The developed system is tested in simulation, showing the potential benefits of using the proposed approach for artificial pancreas systems.
format	article
author	Aleix Beneyto Vicenç Puig B. Wayne Bequette Josep Vehi
author_facet	Aleix Beneyto Vicenç Puig B. Wayne Bequette Josep Vehi
author_sort	Aleix Beneyto
title	A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems
title_short	A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems
title_full	A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems
title_fullStr	A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems
title_full_unstemmed	A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems
title_sort	hybrid automata approach for monitoring the patient in the loop in artificial pancreas systems
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/72f58f5d88a944ca8eaa771f1af2db1f
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A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems

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