Abstract
The latest achievements in sensor technologies for blood glucose level monitoring, pump miniaturization for insulin delivery, and the availability of portable computing devices are paving the way toward the artificial pancreas as a treatment for diabetes patients. This device encompasses a controller unit that oversees the administration of insulin micro-boluses and continuously drives the pump based on blood glucose readings acquired in real time. In order to foster the research on the artificial pancreas and prepare for its adoption as a therapy, the European Union in 2010 funded the AP@home project, following a series of efforts already ongoing in the USA. This paper, authored by members of the AP@home consortium, reports on the technical issues concerning the design and implementation of an architecture supporting the exploitation of an artificial pancreas platform. First a PC-based platform was developed by the authors to prove the effectiveness and reliability of the algorithms responsible for insulin administration. A mobile-based one was then adopted to improve the comfort for the patients. Both platforms were tested on real patients, and a description of the goals, the achievements, and the major shortcomings that emerged during those trials is also reported in the paper.
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References
Abu-Rmileh A, Garcia-Gabin W, Zambrano D (2010) A robust sliding mode controller with internal model for closed-loop artificial pancreas. Med Biol Eng Comput 48(12):1191–1201
Baig MM, Gholamhosseini H, Connolly MJ (2013) A comprehensive survey of wearable and wireless ECG monitoring systems for older adults. Med Biol Eng Comput 51(5):485–495
Capel I, Rigla M, García-Sáez G, Rodríguez-Herrero A, Pons B, Subías D, García-García F, Gallach M, Aguilar M, Pérez-Gandía C, Gómez EJ, Caixàs A, Hernando ME (2014) Artificial pancreas using a personalized rule-based controller achieves overnight normoglycemia in patients with type 1 diabetes. Diabetes Technol Ther 16(3):172–179
Capozzi D, Lanzola G (2010) An agent-based architecture for home care monitoring and education of chronic patients. In: Proceedings of the IEEE complexity in engineering conference (COMPENG’10):138–140
Capozzi D, Lanzola G (2011) Utilizing information technologies for lifelong monitoring in diabetes patients. J Diabetes Sci Technol 5(1):55–62
Capozzi D, Lanzola G (2013) A generic telemedicine infrastructure for monitoring an artificial pancreas trial. Comput Methods Programs Biomed 110(3):343–353
Christiansen M, Bailey T, Watkins E, Liljenquist D, Price D, Nakamura K, Boock R, Peyser T (2013) A new-generation continuous glucose monitoring system: improved accuracy and reliability compared with a previous-generation system. Diabetes Technol Ther 15(10):881–888
Cobelli C, Dalla Man C, Sparacino G, Magni L, De Nicolao G, Kovatchev B (2009) Diabetes: models, signals and control. IEEE Rev Biomed Eng 2:54–96
Cobelli C, Renard E, Kovatchev B (2011) Artificial pancreas: past, present, future. Diabetes 60(11):2672–2682
Dassau E, Zisser H, Palerm CC, Buckingham BA, Jovanovic L, Doyle FJ III (2008) Modular artificial β-cell system: a prototype for clinical research. J Diabetes Sci Technol 2(5):863–872
Del Favero S, Place J, Kropff J, Messori M, Keith-Hynes P, Visentin R, Monaro M, Bruttomesso D, Galasso S, Boscari F, Toffanin C, Di Palma F, Lanzola G, Scarpellini S, Farret A, Kovatchev B, Magni L, Avogaro A, DeVries JH, Cobelli C, Renard E, On behalf of the AP@home Consortium (2014) Multicenter outpatient dinner/overnight reduction of hypoglycaemia and increased time of glucose in target with a wearable artificial pancreas using modular model predictive control algorithm in adults with type 1 diabetes. Submitted for evaluation
Del Favero S, Bruttomesso D, Di Palma F, Lanzola G, Visentin R, Filippi A, Scotton R, Toffanin C, Messori M, Scarpellini S, Keith-Hynes P, Kovatchev BP, DeVries JH, Renard E, Magni L, Avogaro A, Cobelli C, On behalf of the AP@home Consortium (2014) First use of model predictive control in outpatient wearable artificial pancreas. Diabetes Care 37(5):1212–1215
DeSalvo D, Buckingham B (2013) Continuous glucose monitoring: current use and future directions. Curr Diab Rep 13(5):657–662
Dua P, Doyle FJ III, Pistikopoulos EN (2009) Multi-objective blood glucose control for type 1 diabetes. Med Biol Eng Comput 47(3):343–352
Friedman CP, Wyatt JC (2006) Challenges of evaluation in biomedical informatics. In: Hannah KJ, Ball MJ (eds) Evaluation methods in biomedical informatics, chap 1. Springer, New York, pp 1–20. ISBN: 978-0-387-30677-3
Friedman CP, Wyatt JC (2006) The design of demonstration studies. In: Hannah KJ, Ball MJ (eds) Evaluation methods in biomedical informatics, chap 7. Springer, New York, pp 188–223. ISBN: 978-0-387-30677-3
Galvanin F, Barolo M, Macchietto S, Bezzo F (2011) Optimal design of clinical tests for the identification of physiological models of type 1 diabetes in the presence of model mismatch. Med Biol Eng Comput 49(3):263–277
Heinemann L, Benesch C, DeVries JH (2011) AP@home: a novel European approach to bring the artificial pancreas home. J Diabetes Sci Technol 5(6):1363–1372
Hernando ME, García-Sáez G, Martínez-Sarriegui I, Rodríguez-Herrero A, Pérez-Gandía C, Rigla M, de Leiva A, Capel I, Pons B, Gómez EJ (2009) Automatic data processing to achieve a safe telemedical artificial pancreas. J Diabetes Sci Technol 3(5):1039–1046
Hovorka R, Canonico V, Chassin LJ, Haueter U, Massi-Benedetti M, Federici MO, Pieber TR, Schaller HC, Schaupp L, Vering T, Wilinska ME (2004) Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes. Physiol Meas 25:905–920
Hughes CS, Patek SD, Breton MD, Kovatchev BP (2010) Hypoglycemia prevention via pump attenuation and red-yellow-green “traffic” lights using continuous glucose monitoring and insulin pump data. J Diabetes Sci Technol 4(5):1146–1155
Keith-Hynes P, Guerlain S, Mize B, Hughes-Karvetski C, Khan M, McElwee-Malloy M, Kovatchev BP (2013) DiAs user interface: a patient-centric interface for mobile artificial pancreas systems. J Diabetes Sci Technol 7(6):1416–1426
Lane JE, Shivers JP, Zisser H (2013) Continuous glucose monitors: current status and future developments. Curr Opin Endocrinol Diabetes Obes 20(2):106–111
Lanzola G, Capozzi D, D’Annunzio G, Ferrari P, Bellazzi R, Larizza C (2007) Going mobile with a multiaccess service for the management of diabetic patients. J Diabetes Sci Technol 1(5):730–737
Lanzola G, Capozzi D, Serina N, Magni L, Bellazzi R (2011) Bringing the artificial pancreas home: telemedicine aspects. J Diabetes Sci Technol 5(6):1381–1386
Lanzola G, Scarpellini S, Di Palma F, Toffanin C, Del Favero S, Magni L, Bellazzi R (2014) Monitoring artificial pancreas trials through agent-based technologies: a case report. J Diabetes Sci Technol 8(2):216–224
Lodwig V, Kulzer B, Schnell O, Heinemann L (2014) Current trends in continuous glucose monitoring. J Diabetes Sci Technol 8(2):390–396
Luijf YM, DeVries JH, Zwinderman K, Leelarathna L, Nodale M, Caldwell K, Kumareswaran K, Elleri D, Allen J, Wilinska M, Evans M, Hovorka R, Doll W, Ellmerer M, Mader JK, Renard E, Place J, Farret A, Cobelli C, Del Favero S, Dalla Man C, Avogaro A, Bruttomesso D, Filippi A, Scotton R, Magni L, Lanzola G, Di Palma F, Soru P, Toffanin C, De Nicolao G, Arnolds S, Benesch C, Heinemann L (2013) Day and night closed loop control in adults with type 1 diabetes mellitus: a comparison of two closed loop algorithms driving continuous subcutaneous insulin infusion versus patient self management. Diabetes Care 36(12):3882–3887
Muro M, Amoretti M, Zanichelli F, Conte G (2012) Towards a flexible middleware for context-aware pervasive and wearable systems. Med Biol Eng Comput 50(11):1127–1136
Nicolucci A, Maione A, Franciosi M, Amoretti R, Busetto E, Capani F, Bruttomesso D, Di Bartolo P, Girelli A, Leonetti F, Morviducci L, Ponzi P, Vitacolonna E (2008) Quality of life and treatment satisfaction in adults with type 1 diabetes: a comparison between continuous subcutaneous insulin infusion and multiple daily injections. Diabet Med 25(2):213–220
Patek SD, Magni L, Dassau E, Hughes-Karvetski C, Toffanin C, De Nicolao G, Del Favero S, Breton M, Dalla Man C, Renard E, Zisser H, Doyle FJ III, Cobelli C, Kovatchev BP (2012) Modular closed-loop control of diabetes. IEEE Trans Biomed Eng 59(11):2986–2999
Peyser T, Dassau E, Breton M, Skyler JS (2014) The artificial pancreas: current status and future prospects in the management of diabetes. Ann N Y Acad Sci 1311:102–123
Reade C (1989) Elements of functional programming. Addison-Wesley, ISBN 978-0201129151
Schreier G (2014) The internet of things for personalized health. Stud Health Technol Inform 200:22–31
Shao X, Ke Q, Jiang J (2009) The research of mobile database synchronization technology based on SyncML. J Computational Inf Syst 5(2):535–542
Shashaj B, Sulli N (2009) Difference in insulin usage patterns with pubertal development in children with type 1 diabetes during transition from multiple daily injections to continuous subcutaneous insulin infusion (CSII) and through the CSII treatment. Diabetes Technol Ther 11(12):767–774
Soru P, De Nicolao G, Toffanin C, Dalla Man C, Cobelli C, Magni L (2012) MPC based artificial pancreas: strategies for individualization and meal compensation. Annu Rev Control 36(1):118–128
Sparacino G, Zanon M, Facchinetti A, Zecchin C, Maran A, Cobelli C (2012) Italian contributions to the development of continuous glucose monitoring sensors for diabetes management. Sensors 12(10):13753–13780
Toffanin C, Messori M, Di Palma F, De Nicolao G, Cobelli C, Magni L (2013) Artificial pancreas: model predictive control design from clinical experience. J Diabetes Sci Technol 7(6):1470–1483
Zanon M, Sparacino G, Facchinetti A, Riz M, Talary MS, Suri RE, Caduff A, Cobelli C (2012) Non-invasive continuous glucose monitoring: improving accuracy of point and trend estimates of the multisensor system. Med Biol Eng Compu 50(10):1047–1057
Zheng JW, Zhang ZB, Wu TH, Zhang Y (2007) A wearable mobihealth care system supporting real-time diagnosis and alarm. Med Biol Eng Comput 45(9):877–885
Acknowledgments
This research was funded through FP7 Grant Number 247138 from the European Commission to the AP@home consortium, http://www.apathome.eu.
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No competing financial interests exist involving any of the authors of the paper.
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Lanzola, G., Toffanin, C., Di Palma, F. et al. Designing an artificial pancreas architecture: the AP@home experience. Med Biol Eng Comput 53, 1271–1283 (2015). https://doi.org/10.1007/s11517-014-1231-1
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DOI: https://doi.org/10.1007/s11517-014-1231-1