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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Main Authors: Aleix Beneyto, Vicenç Puig, B. Wayne Bequette, Josep Vehi
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/21/21/7117
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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
collection DOAJ
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.
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spelling doaj.art-72f58f5d88a944ca8eaa771f1af2db1f2023-11-22T21:36:52ZengMDPI AGSensors1424-82202021-10-012121711710.3390/s21217117A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas SystemsAleix Beneyto0Vicenç Puig1B. Wayne Bequette2Josep Vehi3Department of Electrical, Electronic and Automatic Engineering, University of Girona, 17004 Girona, SpainAutomatic Control Department-Campus de Terrassa, Universitat Politècnica de Catalunya (UPC), 08222 Terrassa, SpainDepartment of Chemical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USADepartment of Electrical, Electronic and Automatic Engineering, University of Girona, 17004 Girona, SpainThe 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.https://www.mdpi.com/1424-8220/21/21/7117artificial pancreashybrid automatonKalman filterpatient in the looptype 1 diabetes
spellingShingle Aleix Beneyto
Vicenç Puig
B. Wayne Bequette
Josep Vehi
A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems
Sensors
artificial pancreas
hybrid automaton
Kalman filter
patient in the loop
type 1 diabetes
title 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_short 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
topic artificial pancreas
hybrid automaton
Kalman filter
patient in the loop
type 1 diabetes
url https://www.mdpi.com/1424-8220/21/21/7117
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