{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,6,13]],"date-time":"2024-06-13T11:14:54Z","timestamp":1718277294655},"reference-count":177,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T00:00:00Z","timestamp":1709078400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T00:00:00Z","timestamp":1709078400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program","award":["2017BT01G167"]},{"name":"Science and Technology Research Project of Henan Province","award":["22210222001"]},{"name":"Guangzhou University Engineering Technology Research Center","award":["2021GCZX002"]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1007\/s11517-024-03042-x","type":"journal-article","created":{"date-parts":[[2024,2,29]],"date-time":"2024-02-29T00:02:43Z","timestamp":1709164963000},"page":"1615-1638","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Recent advances in the precision control strategy of artificial pancreas"],"prefix":"10.1007","volume":"62","author":[{"given":"Wuyi","family":"Ming","sequence":"first","affiliation":[]},{"given":"Xudong","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Guojun","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yinxia","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Yongxin","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Hongmei","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Haofang","family":"Liang","sequence":"additional","affiliation":[]},{"given":"Yuan","family":"Yang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,28]]},"reference":[{"issue":"3","key":"3042_CR1","doi-asserted-by":"publisher","first-page":"233","DOI":"10.4236\/ajcm.2018.83019","volume":"8","author":"JM Ntaganda","year":"2018","unstructured":"Ntaganda JM, Minani F, Banzi W, Mpinganzima L, Niyobuhungiro J, Gahutu JB, Rutaganda E, Kambutse I, Dusabejambo V (2018) Simplified mathematical model of glucose-insulin system. Am J Computat Math 8(3):233\u2013244. https:\/\/doi.org\/10.4236\/ajcm.2018.83019","journal-title":"Am J Computat Math"},{"issue":"1084","key":"3042_CR2","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1136\/postgradmedj-2015-133281","volume":"92","author":"F Zaccardi","year":"2016","unstructured":"Zaccardi F, Webb DR, Yates T, Davies MJ (2016) Pathophysiology of type 1 and type 2 diabetes mellitus: a 90-year perspective. Postgrad Med J 92(1084):63\u201369. https:\/\/doi.org\/10.1136\/postgradmedj-2015-133281","journal-title":"Postgrad Med J"},{"key":"3042_CR3","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/B978-0-444-53480-4.00015-1","volume":"126","author":"U Alam","year":"2014","unstructured":"Alam U, Asghar O, Azmi S, Malik RA (2014) General aspects of diabetes mellitus. Handb Clin Neurol 126:211\u2013222. https:\/\/doi.org\/10.1016\/B978-0-444-53480-4.00015-1","journal-title":"Handb Clin Neurol"},{"issue":"9","key":"3042_CR4","doi-asserted-by":"publisher","first-page":"1259","DOI":"10.1007\/s00228-021-03097-x","volume":"77","author":"AS Alzahrani","year":"2021","unstructured":"Alzahrani AS, Price MJ, Greenfield SM, Paudyal V (2021) Global prevalence and types of complementary and alternative medicines use amongst adults with diabetes: systematic review and meta-analysis. Eur J Clin Pharmacol 77(9):1259\u20131274. https:\/\/doi.org\/10.1007\/s00228-021-03097-x","journal-title":"Eur J Clin Pharmacol"},{"key":"3042_CR5","doi-asserted-by":"publisher","first-page":"104800","DOI":"10.1016\/j.jmbbm.2021.104800","volume":"124","author":"S Asadullah","year":"2021","unstructured":"Asadullah S, Mei S, Yang K, Hu X, Wang F, Yu B, Wu Z, Wei J (2021) Tantalum oxide submicro-particles into microporous coating on polyimide possessing antibacterial property and inducing cellular response for orthopedic application. J Mech Behav Biomed Mater 124:104800. https:\/\/doi.org\/10.1016\/j.jmbbm.2021.104800","journal-title":"J Mech Behav Biomed Mater"},{"issue":"3","key":"3042_CR6","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1016\/j.diabres.2010.01.026","volume":"87","author":"P Zhang","year":"2010","unstructured":"Zhang P, Zhang X, Brown J, Vistisen D, Sicree R, Shaw J, Nichols G (2010) Global healthcare expenditure on diabetes for 2010 and 2030. Diabetes Res Clin Pract 87(3):293\u2013301. https:\/\/doi.org\/10.1016\/j.diabres.2010.01.026","journal-title":"Diabetes Res Clin Pract"},{"issue":"S2","key":"3042_CR7","doi-asserted-by":"publisher","first-page":"S2","DOI":"10.1089\/dia.2018.0101","volume":"20","author":"SK Garg","year":"2018","unstructured":"Garg SK, Rewers AH, Akturk HK (2018) Ever-increasing insulin-requiring patients globally. Diabetes Technol Ther 20(S2):S2-1. https:\/\/doi.org\/10.1089\/dia.2018.0101","journal-title":"Diabetes Technol Ther"},{"issue":"6","key":"3042_CR8","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1016\/S2213-8587(17)30097-9","volume":"5","author":"C Bommer","year":"2017","unstructured":"Bommer C, Heesemann E, Sagalova V, Manne-Goehler J, Atun R, B\u00e4rnighausen T, Vollmer S (2017) The global economic burden of diabetes in adults aged 20\u201379 years: a cost-of-illness study. The Lancet Diabetes & Endocrinology 5(6):423\u2013430. https:\/\/doi.org\/10.1016\/S2213-8587(17)30097-9","journal-title":"The Lancet Diabetes & Endocrinology"},{"key":"3042_CR9","unstructured":"Organization WH, et al (1999) Definition, diagnosis and classification of diabetes mellitus and its complications: report of a WHO consultation. Part 1, diagnosis and classification of diabetes mellitus, Tech. rep., World Health Organization"},{"issue":"1","key":"3042_CR10","doi-asserted-by":"publisher","first-page":"4","DOI":"10.2337\/cd23-as01","volume":"41","author":"AD Association","year":"2023","unstructured":"Association AD et al (2023) Standards of care in diabetes-2023 abridged for primary care providers. Clin Diabetes 41(1):4\u201331. https:\/\/doi.org\/10.2337\/cd23-as01","journal-title":"Clin Diabetes"},{"key":"3042_CR11","doi-asserted-by":"publisher","first-page":"104141","DOI":"10.1016\/j.jbi.2022.104141","volume":"132","author":"E Estremera","year":"2022","unstructured":"Estremera E, Cabrera A, Beneyto A, Vehi J (2022) A simulator with realistic and challenging scenarios for virtual T1D patients undergoing CSII and MDI therapy. J Biomed Inf 132:104141. https:\/\/doi.org\/10.1016\/j.jbi.2022.104141","journal-title":"J Biomed Inf"},{"key":"3042_CR12","doi-asserted-by":"publisher","first-page":"604028","DOI":"10.3389\/fendo.2021.604028","volume":"12","author":"S Hu","year":"2021","unstructured":"Hu S, Yang H, Chen Z, Leng X, Li C, Qiao L, Lv W, Li T (2021) Clinical outcome and cost-effectiveness analysis of CSII versus MDI in children and adolescent with type 1 diabetes mellitus in a public health care system of China. Front Endocrinol 12:604028. https:\/\/doi.org\/10.3389\/fendo.2021.604028","journal-title":"Front Endocrinol"},{"issue":"6","key":"3042_CR13","doi-asserted-by":"publisher","first-page":"650","DOI":"10.1093\/jpepsy\/jsj088","volume":"31","author":"JM Valenzuela","year":"2006","unstructured":"Valenzuela JM, Patino AM, McCullough J, Ring C, Sanchez J, Eidson M, Nemery R, Delamater AM (2006) Insulin pump therapy and health-related quality of life in children and adolescents with type 1 diabetes. J Pediatr Psychol 31(6):650\u2013660. https:\/\/doi.org\/10.1093\/jpepsy\/jsj088","journal-title":"J Pediatr Psychol"},{"issue":"5","key":"3042_CR14","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1016\/j.amjms.2019.08.008","volume":"358","author":"ND Sora","year":"2019","unstructured":"Sora ND, Shashpal F, Bond EA, Jenkins AJ (2019) Insulin pumps: review of technological advancement in diabetes management. Am J Med Sci 358(5):326\u2013331. https:\/\/doi.org\/10.1016\/j.amjms.2019.08.008","journal-title":"Am J Med Sci"},{"key":"3042_CR15","doi-asserted-by":"publisher","unstructured":"Zhang Y, Sun J, Liu L, Qiao H (2021) A review of biosensor technology and algorithms for glucose monitoring. J Diabetes Complications 35(8):107929. https:\/\/doi.org\/10.1016\/j.jdiacomp.2021.107929","DOI":"10.1016\/j.jdiacomp.2021.107929"},{"issue":"2","key":"3042_CR16","doi-asserted-by":"publisher","first-page":"108385","DOI":"10.1016\/j.jdiacomp.2022.108385","volume":"37","author":"P Oriot","year":"2023","unstructured":"Oriot P, Hermans MP (2023) Intermittent-scanned continuous glucose monitoring with low glucose alarms decreases hypoglycemia incidence in middle-aged adults with type 1 diabetes in real-life setting. J Diabetes Complications 37(2):108385. https:\/\/doi.org\/10.1016\/j.jdiacomp.2022.108385","journal-title":"J Diabetes Complications"},{"issue":"6","key":"3042_CR17","doi-asserted-by":"publisher","first-page":"708","DOI":"10.1016\/S1471-4892(02)00216-3","volume":"2","author":"E Renard","year":"2002","unstructured":"Renard E (2002) Implantable closed-loop glucose-sensing and insulin delivery: the future for insulin pump therapy. Curr Opin Pharmacol 2(6):708\u2013716. https:\/\/doi.org\/10.1016\/S1471-4892(02)00216-3","journal-title":"Curr Opin Pharmacol"},{"issue":"7","key":"3042_CR18","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1080\/17434440.2020.1784724","volume":"17","author":"J Fuchs","year":"2020","unstructured":"Fuchs J, Hovorka R (2020) Closed-loop control in insulin pumps for type-1 diabetes mellitus: safety and efficacy. Expert Rev Med Devices 17(7):707\u2013720. https:\/\/doi.org\/10.1080\/17434440.2020.1784724","journal-title":"Expert Rev Med Devices"},{"key":"3042_CR19","doi-asserted-by":"publisher","first-page":"1437","DOI":"10.1007\/s11517-019-01972-5","volume":"57","author":"A Bhattacharjee","year":"2019","unstructured":"Bhattacharjee A, Easwaran A, Leow MK, Cho N (2019) Design of an online-tuned model based compound controller for a fully automated artificial pancreas. Med Biol Eng Comput 57:1437\u20131449. https:\/\/doi.org\/10.1007\/s11517-019-01972-5","journal-title":"Med Biol Eng Comput"},{"key":"3042_CR20","doi-asserted-by":"publisher","first-page":"107061","DOI":"10.1016\/j.cmpb.2022.107061","volume":"226","author":"I Sala-Mira","year":"2022","unstructured":"Sala-Mira I, Garcia P, D\u00edez J-L, Bondia J (2022) Internal model control based module for the elimination of meal and exercise announcements in hybrid artificial pancreas systems. Comput Methods Programs Biomed 226:107061. https:\/\/doi.org\/10.1016\/j.cmpb.2022.107061","journal-title":"Comput Methods Programs Biomed"},{"issue":"1","key":"3042_CR21","doi-asserted-by":"publisher","first-page":"1018","DOI":"10.1016\/j.ifacol.2019.06.196","volume":"52","author":"JB J\u00f8rgensen","year":"2019","unstructured":"J\u00f8rgensen JB, Boiroux D, Mahmoudi Z (2019) An artificial pancreas based on simple control algorithms and physiological insight. IFAC-PapersOnLine 52(1):1018\u20131023. https:\/\/doi.org\/10.1016\/j.ifacol.2019.06.196","journal-title":"IFAC-PapersOnLine"},{"key":"3042_CR22","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.conengprac.2014.02.012","volume":"28","author":"K Mythreyi","year":"2014","unstructured":"Mythreyi K, Subramanian SC, Kumar RK (2014) Nonlinear glucose-insulin control considering delays-Part II: control algorithm. Control Eng Pract 28:26\u201333. https:\/\/doi.org\/10.1016\/j.conengprac.2014.02.012","journal-title":"Control Eng Pract"},{"issue":"1","key":"3042_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-022-22531-3","volume":"12","author":"JW Dietrich","year":"2022","unstructured":"Dietrich JW, Dasgupta R, Anoop S, Jebasingh F, Kurian ME, Inbakumari M, Boehm BO, Thomas N (2022) SPINA Carb: a simple mathematical model supporting fast in-vivo estimation of insulin sensitivity and beta cell function. Sci Rep 12(1):1\u201313. https:\/\/doi.org\/10.1038\/s41598-022-22531-3","journal-title":"Sci Rep"},{"issue":"12","key":"3042_CR24","doi-asserted-by":"publisher","first-page":"2093","DOI":"10.3390\/s16122093","volume":"16","author":"A Facchinetti","year":"2016","unstructured":"Facchinetti A (2016) Continuous glucose monitoring sensors: past, present and future algorithmic challenges. Sensors 16(12):2093. https:\/\/doi.org\/10.3390\/s16122093","journal-title":"Sensors"},{"issue":"4","key":"3042_CR25","doi-asserted-by":"publisher","first-page":"2133","DOI":"10.1152\/physrev.00063.2017","volume":"98","author":"MC Petersen","year":"2018","unstructured":"Petersen MC, Shulman GI (2018) Mechanisms of insulin action and insulin resistance. Physiol Rev 98(4):2133\u20132223. https:\/\/doi.org\/10.1152\/physrev.00063.2017","journal-title":"Physiol Rev"},{"issue":"7","key":"3042_CR26","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1038\/nrendo.2011.32","volume":"7","author":"R Hovorka","year":"2011","unstructured":"Hovorka R (2011) Closed-loop insulin delivery: from bench to clinical practice. Nat Rev Endocrinol 7(7):385\u2013395. https:\/\/doi.org\/10.1038\/nrendo.2011.32","journal-title":"Nat Rev Endocrinol"},{"issue":"1","key":"3042_CR27","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1109\/51.897829","volume":"20","author":"RS Parker","year":"2001","unstructured":"Parker RS, Doyle FJ, Peppas NA (2001) The intravenous route to blood glucose control. IEEE Eng Med Biol Mag 20(1):65\u201373. https:\/\/doi.org\/10.1109\/51.897829","journal-title":"IEEE Eng Med Biol Mag"},{"issue":"1","key":"3042_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1741-7015-9-120","volume":"9","author":"D Elleri","year":"2011","unstructured":"Elleri D, Dunger DB, Hovorka R (2011) Closed-loop insulin delivery for treatment of type 1 diabetes. BMC Med 9(1):1\u20139. https:\/\/doi.org\/10.1186\/1741-7015-9-120","journal-title":"BMC Med"},{"issue":"1","key":"3042_CR29","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1089\/dia.2012.0185","volume":"15","author":"R Hovorka","year":"2013","unstructured":"Hovorka R, Nodale M, Haidar A, Wilinska ME (2013) Assessing performance of closed-loop insulin delivery systems by continuous glucose monitoring: drawbacks and way forward. Diabetes Technology & Therapeutics 15(1):4\u201312. https:\/\/doi.org\/10.1089\/dia.2012.0185","journal-title":"Diabetes Technology & Therapeutics"},{"issue":"4","key":"3042_CR30","doi-asserted-by":"publisher","first-page":"E67","DOI":"10.1111\/aor.12068","volume":"37","author":"Y Tsukamoto","year":"2013","unstructured":"Tsukamoto Y, Kinoshita Y, Kitagawa H, Munekage M, Munekage E, Takezaki Y, Yatabe T, Yamashita K, Yamazaki R, Okabayashi T et al (2013) Evaluation of a novel artificial pancreas: closed loop glycemic control system with continuous blood glucose monitoring. Artif Organs 37(4):E67\u2013E73. https:\/\/doi.org\/10.1111\/aor.12068","journal-title":"Artif Organs"},{"issue":"3","key":"3042_CR31","first-page":"91","volume":"6","author":"A Clemens","year":"1979","unstructured":"Clemens A (1979) Feedback control dynamics for glucose controlled insulin infusion system. Medical Progress Through Technology 6(3):91\u201398","journal-title":"Medical Progress Through Technology"},{"issue":"6","key":"3042_CR32","doi-asserted-by":"publisher","first-page":"1401","DOI":"10.1177\/193229681200600621","volume":"6","author":"S Laxminarayan","year":"2012","unstructured":"Laxminarayan S, Reifman J, Steil GM (2012) Use of a food and drug administration-approved type 1 diabetes mellitus simulator to evaluate and optimize a proportional-integral-derivative controller. J Diabetes Sci Technol 6(6):1401\u20131412. https:\/\/doi.org\/10.1177\/193229681200600621","journal-title":"J Diabetes Sci Technol"},{"issue":"2","key":"3042_CR33","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1109\/10.740877","volume":"46","author":"RS Parker","year":"1999","unstructured":"Parker RS, Doyle FJ, Peppas NA (1999) A model-based algorithm for blood glucose control in type I diabetic patients. IEEE Trans Biomed Eng 46(2):148\u2013157. https:\/\/doi.org\/10.1109\/10.740877","journal-title":"IEEE Trans Biomed Eng"},{"issue":"4","key":"3042_CR34","doi-asserted-by":"publisher","first-page":"905","DOI":"10.1088\/0967-3334\/25\/4\/010","volume":"25","author":"R Hovorka","year":"2004","unstructured":"Hovorka R, Canonico V, Chassin LJ, Haueter U, Massi-Benedetti M, Federici MO, Pieber TR, Schaller HC, Schaupp L, Vering T et al (2004) Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes. Physiol Meas 25(4):905. https:\/\/doi.org\/10.1088\/0967-3334\/25\/4\/010","journal-title":"Physiol Meas"},{"issue":"6","key":"3042_CR35","doi-asserted-by":"publisher","first-page":"1510","DOI":"10.1002\/aic.12081","volume":"56","author":"Y Wang","year":"2010","unstructured":"Wang Y, Zisser H, Dassau E, Jovanovi\u010d L, Doyle FJ III (2010) Model predictive control with learning-type set-point: application to artificial pancreatic $$\\beta $$-cell. AIChE J 56(6):1510\u20131518. https:\/\/doi.org\/10.1002\/aic.12081","journal-title":"AIChE J"},{"key":"3042_CR36","doi-asserted-by":"publisher","unstructured":"Yasini S, Naghibi-Sistani M-B, Karimpour A, (2008) Active insulin infusion using fuzzy-based closed-loop control, In: 2008 3rd International Conference on Intelligent System and Knowledge Engineering, vol 1, IEEE, pp 429\u2013434. https:\/\/doi.org\/10.1109\/ISKE.2008.4730968","DOI":"10.1109\/ISKE.2008.4730968"},{"key":"3042_CR37","doi-asserted-by":"publisher","unstructured":"Bahremand S, Ko HS, Balouchzadeh R, Felix\u00a0Lee H, Park S, Kwon G (2019) Neural network-based model predictive control for type 1 diabetic rats on artificial pancreas system. Med Biol Eng Comput 57(1):177\u2013191. https:\/\/doi.org\/10.1007\/s11517-018-1872-6","DOI":"10.1007\/s11517-018-1872-6"},{"issue":"4","key":"3042_CR38","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1109\/TCST.2005.847331","volume":"13","author":"KH Ang","year":"2005","unstructured":"Ang KH, Chong G, Li Y (2005) PID control system analysis, design, and technology. IEEE Trans Control Syst Technol 13(4):559\u2013576. https:\/\/doi.org\/10.1109\/TCST.2005.847331","journal-title":"IEEE Trans Control Syst Technol"},{"issue":"6","key":"3042_CR39","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1089\/152091503322640999","volume":"5","author":"GM Steil","year":"2003","unstructured":"Steil GM, Rebrin K, Janowski R, Darwin C, Saad MF (2003) Modeling $$\\beta $$-cell insulin secretion-implications for closed-loop glucose homeostasis. Diabetes Technology & Therapeutics 5(6):953\u2013964. https:\/\/doi.org\/10.1089\/152091503322640999","journal-title":"Diabetes Technology & Therapeutics"},{"issue":"7","key":"3042_CR40","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1038\/nrendo.2011.32","volume":"7","author":"R Hovorka","year":"2011","unstructured":"Hovorka R (2011) Closed-loop insulin delivery: from bench to clinical practice. Nat Rev Endocrinol 7(7):385\u2013395. https:\/\/doi.org\/10.1038\/nrendo.2011.32","journal-title":"Nat Rev Endocrinol"},{"issue":"3","key":"3042_CR41","doi-asserted-by":"publisher","first-page":"31","DOI":"10.3390\/asi3030031","volume":"3","author":"S Mehmood","year":"2020","unstructured":"Mehmood S, Ahmad I, Arif H, Ammara UE, Majeed A (2020) Artificial pancreas control strategies used for type 1 diabetes control and treatment: a comprehensive analysis. Appl Syst Innov 3(3):31. https:\/\/doi.org\/10.3390\/asi3030031","journal-title":"Appl Syst Innov"},{"key":"3042_CR42","doi-asserted-by":"publisher","first-page":"S183","DOI":"10.1016\/S0168-8227(06)70028-6","volume":"74","author":"G Steil","year":"2006","unstructured":"Steil G, Rebrin K, Mastrototaro JJ (2006) Metabolic modelling and the closed-loop insulin delivery problem. Diabetes Res Clin Pract 74:S183\u2013S186. https:\/\/doi.org\/10.1016\/S0168-8227(06)70028-6","journal-title":"Diabetes Res Clin Pract"},{"key":"3042_CR43","doi-asserted-by":"publisher","unstructured":"Alshalalfah A-L, Hamad GB, Mohamed OA (2020) Towards safe and robust closed-loop artificial pancreas using adaptive weighted PID control strategy. In: (2020) 18th IEEE International New Circuits and Systems Conference (NEWCAS). IEEE 2020:146\u2013149. https:\/\/doi.org\/10.1109\/NEWCAS49341.2020.9159828","DOI":"10.1109\/NEWCAS49341.2020.9159828"},{"issue":"3","key":"3042_CR44","doi-asserted-by":"publisher","first-page":"857","DOI":"10.1109\/TBME.2008.915665","volume":"55","author":"G Marchetti","year":"2008","unstructured":"Marchetti G, Barolo M, Jovanovic L, Zisser H, Seborg DE (2008) An improved PID switching control strategy for type 1 diabetes. IEEE Trans Biomed Eng 55(3):857\u2013865. https:\/\/doi.org\/10.1109\/TBME.2008.915665","journal-title":"IEEE Trans Biomed Eng"},{"issue":"1","key":"3042_CR45","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1530\/acta.0.0980081","volume":"98","author":"RA DeFronzo","year":"1981","unstructured":"DeFronzo RA, Binder C, Wahren J, Felig P, Ferrannini E, Faber OK (1981) Sensitivity of insulin secretion to feedback inhibition by hyperinsulinaemia. Eur J Endocrinol 98(1):81\u201386. https:\/\/doi.org\/10.1530\/acta.0.0980081","journal-title":"Eur J Endocrinol"},{"issue":"4","key":"3042_CR46","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1016\/S0019-0578(07)60103-7","volume":"41","author":"J-C Shen","year":"2002","unstructured":"Shen J-C (2002) New tuning method for PID controller. ISA Trans 41(4):473\u2013484. https:\/\/doi.org\/10.1016\/S0019-0578(07)60103-7","journal-title":"ISA Trans"},{"key":"3042_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.matpr.2022.11.196","author":"AK Patra","year":"2022","unstructured":"Patra AK, Nanda A, Agrawal R (2022) Automated artificial pancreas (AP) based on the JAYA optimized PID controller (JAYA-PIDC). Mater Today: Proc. https:\/\/doi.org\/10.1016\/j.matpr.2022.11.196","journal-title":"Mater Today: Proc"},{"key":"3042_CR48","doi-asserted-by":"publisher","unstructured":"Li C, Hu R (2007) PID control based on BP neural network for the regulation of blood glucose level in diabetes. In: (2007) IEEE 7Th International Symposium on Bioinformatics and Bioengineering. IEEE 2007:1168\u20131172. https:\/\/doi.org\/10.1109\/BIBE.2007.4375709","DOI":"10.1109\/BIBE.2007.4375709"},{"issue":"2","key":"3042_CR49","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1016\/j.arcontrol.2012.09.007","volume":"36","author":"BW Bequette","year":"2012","unstructured":"Bequette BW (2012) Challenges and recent progress in the development of a closed-loop artificial pancreas. Annua Rev Control 36(2):255\u2013266. https:\/\/doi.org\/10.1016\/j.arcontrol.2012.09.007","journal-title":"Annua Rev Control"},{"issue":"10","key":"3042_CR50","doi-asserted-by":"publisher","first-page":"2909","DOI":"10.2337\/dc13-0010","volume":"36","author":"JL Sherr","year":"2013","unstructured":"Sherr JL, Cengiz E, Palerm CC, Clark B, Kurtz N, Roy A, Carria L, Cantwell M, Tamborlane WV, Weinzimer SA (2013) Reduced hypoglycemia and increased time in target using closed-loop insulin delivery during nights with or without antecedent afternoon exercise in type 1 diabetes. Diabetes Care 36(10):2909\u20132914. https:\/\/doi.org\/10.2337\/dc13-0010","journal-title":"Diabetes Care"},{"issue":"5","key":"3042_CR51","doi-asserted-by":"publisher","first-page":"1359","DOI":"10.1177\/193229681300700528","volume":"7","author":"GM Steil","year":"2013","unstructured":"Steil GM, Grodsky GM (2013) The artificial pancreas: is it important to understand how the $$\\beta $$ cell controls blood glucose? J Diabetes Sci Technol 7(5):1359\u20131369. https:\/\/doi.org\/10.1177\/193229681300700528","journal-title":"J Diabetes Sci Technol"},{"issue":"4","key":"3042_CR52","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1109\/TITB.2003.821326","volume":"7","author":"F Chee","year":"2003","unstructured":"Chee F, Fernando TL, Savkin AV, Van Heeden V (2003) Expert PID control system for blood glucose control in critically ill patients. IEEE Trans Inf Technol Biomed 7(4):419\u2013425. https:\/\/doi.org\/10.1109\/TITB.2003.821326","journal-title":"IEEE Trans Inf Technol Biomed"},{"issue":"42","key":"3042_CR53","doi-asserted-by":"publisher","first-page":"10311","DOI":"10.1021\/acs.iecr.5b01237","volume":"54","author":"LM Huyett","year":"2015","unstructured":"Huyett LM, Dassau E, Zisser HC, Doyle FJ III (2015) Design and evaluation of a robust PID controller for a fully implantable artificial pancreas. Ind Eng Chem Res 54(42):10311\u201310321. https:\/\/doi.org\/10.1021\/acs.iecr.5b01237","journal-title":"Ind Eng Chem Res"},{"issue":"8","key":"3042_CR54","doi-asserted-by":"publisher","first-page":"3147","DOI":"10.1109\/TCSI.2021.3058355","volume":"68","author":"A-L Alshalalfah","year":"2021","unstructured":"Alshalalfah A-L, Hamad GB, Mohamed OA (2021) Towards safe and robust closed-loop artificial pancreas using improved PID-based control strategies. IEEE Trans Circ Syst I: Regul Pap 68(8):3147\u20133157. https:\/\/doi.org\/10.1109\/TCSI.2021.3058355","journal-title":"IEEE Trans Circ Syst I: Regul Pap"},{"issue":"4","key":"3042_CR55","first-page":"54","volume":"7","author":"TMM Ridha","year":"2011","unstructured":"Ridha TMM, Kadhum MQ, Mahdi SM (2011) Back stepping-based-PID-controller designed for an artificial pancreas model. Al-Khawarizmi Eng J 7(4):54\u201360","journal-title":"Al-Khawarizmi Eng J"},{"key":"3042_CR56","doi-asserted-by":"publisher","first-page":"103106","DOI":"10.1016\/j.bspc.2021.103106","volume":"71","author":"N Rosales","year":"2022","unstructured":"Rosales N, De Battista H, Garelli F (2022) Hypoglycemia prevention: PID-type controller adaptation for glucose rate limiting in artificial pancreas system. Biomed Signal Process Control 71:103106. https:\/\/doi.org\/10.1016\/j.bspc.2021.103106","journal-title":"Biomed Signal Process Control"},{"key":"3042_CR57","doi-asserted-by":"publisher","unstructured":"Hu R, Li C (2015) An improved PID algorithm based on insulin-on-board estimate for blood glucose control with type 1 diabetes. Comput Math Methods Med 2015. https:\/\/doi.org\/10.1155\/2015\/281589","DOI":"10.1155\/2015\/281589"},{"issue":"12","key":"3042_CR58","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10916-016-0602-6","volume":"40","author":"J Yadav","year":"2016","unstructured":"Yadav J, Rani A, Singh V (2016) Performance analysis of fuzzy-PID controller for blood glucose regulation in type-1 diabetic patients. J Med Syst 40(12):1\u201315. https:\/\/doi.org\/10.1007\/s10916-016-0602-6","journal-title":"J Med Syst"},{"issue":"8","key":"3042_CR59","doi-asserted-by":"publisher","first-page":"916","DOI":"10.3390\/cryst11080916","volume":"11","author":"D Shen","year":"2021","unstructured":"Shen D, Ming W, Ren X, Xie Z, Zhang Y, Liu X (2021) A cuckoo search algorithm using improved beta distributing and its application in the process of EDM. Crystals 11(8):916. https:\/\/doi.org\/10.3390\/cryst11080916","journal-title":"Crystals"},{"key":"3042_CR60","doi-asserted-by":"publisher","first-page":"1285","DOI":"10.3390\/cryst11080916","volume":"97","author":"W Ming","year":"2018","unstructured":"Ming W, Zhang Y, Li X, Shen D, He W, Ma J, Shen F (2018) Multi-objective optimization based IBCS for surface roughness and textural feature in MCVE piston machining. Int J Adv Manuf Technol 97:1285\u20131304. https:\/\/doi.org\/10.3390\/cryst11080916","journal-title":"Int J Adv Manuf Technol"},{"issue":"26","key":"3042_CR61","doi-asserted-by":"publisher","first-page":"8257","DOI":"10.1021\/ie049546a","volume":"43","author":"Y Ramprasad","year":"2004","unstructured":"Ramprasad Y, Rangaiah G, Lakshminarayanan S (2004) Robust PID controller for blood glucose regulation in type I diabetics. Ind Eng Chem Res 43(26):8257\u20138268. https:\/\/doi.org\/10.1021\/ie049546a","journal-title":"Ind Eng Chem Res"},{"issue":"2","key":"3042_CR62","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1504\/IJIMS.2019.098226","volume":"6","author":"Y Xiao","year":"2019","unstructured":"Xiao Y, Ming W, Shen D, He W, Ma J, Jiao J (2019) Wolf pack algorithm for optimisation of cutting parameters in WEDM using Taguchi method. Int J Internet Manuf Serv 6(2):139\u2013154. https:\/\/doi.org\/10.1504\/IJIMS.2019.098226","journal-title":"Int J Internet Manuf Serv"},{"key":"3042_CR63","doi-asserted-by":"publisher","unstructured":"Shijo JK, Palani TK, Kumar SS, (2018) Design of controllers for T1DM blood glucose insulin dynamics based on constrained firefly algorithm, In: 2018 4th International conference on electrical energy systems (ICEES), IEEE, pp 116\u2013120. https:\/\/doi.org\/10.1109\/ICEES.2018.8443246","DOI":"10.1109\/ICEES.2018.8443246"},{"key":"3042_CR64","doi-asserted-by":"publisher","unstructured":"Kushner T, Wayne Bequette B, Cameron F, Forlenza G, Maahs D, Sankaranarayanan S, (2019) Models, devices, properties, and verification of artificial pancreas systems, Automated Reasoning for Systems Biology and Medicine 93\u2013131. https:\/\/doi.org\/10.1007\/978-3-030-17297-8-4","DOI":"10.1007\/978-3-030-17297-8-4"},{"key":"3042_CR65","doi-asserted-by":"publisher","unstructured":"Crecil\u00a0Dias C, Kamath S, Vidyasagar S (2020) Blood glucose regulation and control of insulin and glucagon infusion using single model predictive control for type 1 diabetes mellitus. IET Syst Biol 14(3):133\u2013146. https:\/\/doi.org\/10.1049\/iet-syb.2019.0101","DOI":"10.1049\/iet-syb.2019.0101"},{"key":"3042_CR66","doi-asserted-by":"publisher","unstructured":"Patek SD, Magni E, Dassau E, Karvetski C, Toffanin C, De Nicolao G, Del Favero S, Breton M, Dalla\u00a0Man C, Renard E et al (2012) Modular closed-loop control of diabetes. IEEE Trans Biomed Eng 59(11):2986\u20132999. https:\/\/doi.org\/10.1109\/TBME.2012.2192930","DOI":"10.1109\/TBME.2012.2192930"},{"issue":"13","key":"3042_CR67","doi-asserted-by":"publisher","first-page":"5865","DOI":"10.1021\/acs.iecr.9b05979","volume":"59","author":"MF Villa-Tamayo","year":"2020","unstructured":"Villa-Tamayo MF, Rivadeneira PS (2020) Adaptive impulsive offset-free MPC to handle parameter variations for type 1 diabetes treatment. Ind Eng Chem Res 59(13):5865\u20135876. https:\/\/doi.org\/10.1021\/acs.iecr.9b05979","journal-title":"Ind Eng Chem Res"},{"key":"3042_CR68","doi-asserted-by":"publisher","unstructured":"Jacobs PG, El Youssef J, Castle JR, Engle JM, Branigan DL, Johnson P, Massoud R, Kamath A, Ward WK (2011) Development of a fully automated closed loop artificial pancreas control system with dual pump delivery of insulin and glucagon. In: (2011) Annual international conference of the IEEE engineering in medicine and biology society. IEEE 2011:397\u2013400. https:\/\/doi.org\/10.1109\/IEMBS.2011.6090127","DOI":"10.1109\/IEMBS.2011.6090127"},{"key":"3042_CR69","doi-asserted-by":"publisher","unstructured":"Parker R, J.\u00a0Doyle, Harting J, Peppas N, (1996) Model predictive control for infusion pump insulin delivery, In: Proceedings of 18th annual international conference of the IEEE engineering in medicine and biology society, vol 5, IEEE, pp 1822\u20131823. https:\/\/doi.org\/10.1109\/IEMBS.1996.646272","DOI":"10.1109\/IEMBS.1996.646272"},{"key":"3042_CR70","doi-asserted-by":"publisher","unstructured":"Parker R, Gatzke E, Doye F, (2000) Advanced model predictive control (MPC) for type I diabetic patient blood glucose control, In: Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No. 00CH36334), vol 5, IEEE, pp 3483\u20133487. https:\/\/doi.org\/10.1109\/ACC.2000.879216","DOI":"10.1109\/ACC.2000.879216"},{"key":"3042_CR71","doi-asserted-by":"publisher","unstructured":"Lynch SM, Bequette BW, (2001) Estimation-based model predictive control of blood glucose in type I diabetics: a simulation study, In: Proceedings of the IEEE 27th annual Northeast bioengineering conference (Cat. No. 01CH37201), IEEE, pp 79\u201380. https:\/\/doi.org\/10.1109\/NEBC.2001.924729","DOI":"10.1109\/NEBC.2001.924729"},{"key":"3042_CR72","doi-asserted-by":"publisher","unstructured":"Boiroux D, Hagdrup M, Mahmoudi Z, Poulsen K, Madsen H, J\u00f8rgensen JB (2016) An ensemble nonlinear model predictive control algorithm in an artificial pancreas for people with type 1 diabetes. In: (2016) European Control Conference (ECC). IEEE 2016:2115\u20132120. https:\/\/doi.org\/10.1109\/ECC.2016.7810604","DOI":"10.1109\/ECC.2016.7810604"},{"issue":"7","key":"3042_CR73","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1016\/j.ifacol.2022.07.561","volume":"55","author":"AT Reenberg","year":"2022","unstructured":"Reenberg AT, Ritschel TK, Lindkvist EB, Laugesen C, Svensson J, Ranjan AG, N\u00f8rgaard K, J\u00f8rgensen JB (2022) Nonlinear model predictive control and system identification for a dual-hormone artificial pancreas. IFAC-PapersOnLine 55(7):915\u2013921. https:\/\/doi.org\/10.1016\/j.ifacol.2022.07.561","journal-title":"IFAC-PapersOnLine"},{"issue":"27","key":"3042_CR74","doi-asserted-by":"publisher","first-page":"192","DOI":"10.1016\/j.ifacol.2018.11.644","volume":"51","author":"D Boiroux","year":"2018","unstructured":"Boiroux D, J\u00f8rgensen JB (2018) A nonlinear model predictive control strategy for glucose control in people with type 1 diabetes. IFAC-PapersOnLine 51(27):192\u2013197. https:\/\/doi.org\/10.1016\/j.ifacol.2018.11.644","journal-title":"IFAC-PapersOnLine"},{"key":"3042_CR75","doi-asserted-by":"publisher","unstructured":"Messori M, Ellis M, Cobelli C, Christofides PD, Magni L (2015) Improved postprandial glucose control with a customized model predictive controller. In: (2015) American Control Conference (ACC). IEEE 2015:5108\u20135115. https:\/\/doi.org\/10.1109\/ACC.2015.7172136","DOI":"10.1109\/ACC.2015.7172136"},{"key":"3042_CR76","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1016\/j.automatica.2018.01.025","volume":"91","author":"R Gondhalekar","year":"2018","unstructured":"Gondhalekar R, Dassau E, Doyle FJ III (2018) Velocity-weighting & velocity-penalty MPC of an artificial pancreas: improved safety & performance. Automatica 91:105\u2013117. https:\/\/doi.org\/10.1016\/j.automatica.2018.01.025","journal-title":"Automatica"},{"key":"3042_CR77","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1016\/j.jprocont.2018.05.003","volume":"68","author":"D Boiroux","year":"2018","unstructured":"Boiroux D, B\u00e1tora V, Hagdrup M, Wendt SL, Poulsen NK, Madsen H, J\u00f8rgensen JB (2018) Adaptive model predictive control for a dual-hormone artificial pancreas. J Process Control 68:105\u2013117. https:\/\/doi.org\/10.1016\/j.jprocont.2018.05.003","journal-title":"J Process Control"},{"key":"3042_CR78","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.conengprac.2018.05.006","volume":"77","author":"GP Incremona","year":"2018","unstructured":"Incremona GP, Messori M, Toffanin C, Cobelli C, Magni L (2018) Model predictive control with integral action for artificial pancreas. Control Eng Pract 77:86\u201394. https:\/\/doi.org\/10.1016\/j.conengprac.2018.05.006","journal-title":"Control Eng Pract"},{"issue":"7","key":"3042_CR79","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1109\/TBME.2015.2497273","volume":"63","author":"S Schaller","year":"2015","unstructured":"Schaller S, Lippert J, Schaupp L, Pieber TR, Schuppert A, Eissing T (2015) Robust PBPK\/PD-based model predictive control of blood glucose. IEEE Trans Biomed Eng 63(7):1492\u20131504. https:\/\/doi.org\/10.1109\/TBME.2015.2497273","journal-title":"IEEE Trans Biomed Eng"},{"key":"3042_CR80","doi-asserted-by":"publisher","first-page":"100067","DOI":"10.1016\/j.ifacsc.2019.100067","volume":"9","author":"TB Arad\u00f3ttir","year":"2019","unstructured":"Arad\u00f3ttir TB, Boiroux D, Bengtsson H, Kildegaard J, Jensen ML, J\u00f8rgensen JB, Poulsen NK (2019) Model predictive control for dose guidance in long acting insulin treatment of type 2 diabetes. IFAC J Syst Control 9:100067. https:\/\/doi.org\/10.1016\/j.ifacsc.2019.100067","journal-title":"IFAC J Syst Control"},{"key":"3042_CR81","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/j.measurement.2019.04.087","volume":"143","author":"W Ming","year":"2019","unstructured":"Ming W, Shen F, Zhang H, Li X, Ma J, Du J, Lu Y (2019) Defect detection of LGP based on combined classifier with dynamic weights. Measurement 143:211\u2013225. https:\/\/doi.org\/10.1016\/j.measurement.2019.04.087","journal-title":"Measurement"},{"issue":"27","key":"3042_CR82","doi-asserted-by":"publisher","first-page":"27ra27","DOI":"10.1126\/scitranslmed.3000619","volume":"2","author":"FH El-Khatib","year":"2010","unstructured":"El-Khatib FH, Russell SJ, Nathan DM, Sutherlin RG, Damiano ER (2010) A bihormonal closed-loop artificial pancreas for type 1 diabetes. Sci Transl Med 2(27):27ra27-27ra27. https:\/\/doi.org\/10.1126\/scitranslmed.3000619","journal-title":"Sci Transl Med"},{"issue":"2","key":"3042_CR83","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1109\/TBME.2009.2024409","volume":"57","author":"Y Wang","year":"2009","unstructured":"Wang Y, Dassau E, Doyle FJ (2009) Closed-loop control of artificial pancreatic $$\\beta $$-cell in type 1 diabetes mellitus using model predictive iterative learning control. IEEE Trans Biomed Eng 57(2):211\u2013219. https:\/\/doi.org\/10.1109\/TBME.2009.2024409","journal-title":"IEEE Trans Biomed Eng"},{"key":"3042_CR84","doi-asserted-by":"publisher","unstructured":"Zarkogianni K, Mougiakakou SG, Prountzou A, Vazeou A, Bartsocas CS, Nikita KS (2007) An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods. In: (2007) 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE 2007:5971\u20135974. https:\/\/doi.org\/10.1109\/IEMBS.2007.4353708","DOI":"10.1109\/IEMBS.2007.4353708"},{"key":"3042_CR85","doi-asserted-by":"publisher","unstructured":"Ning H, Wang Y (2015) Bihormonal artificial pancreas system based on switching model predictive control, in, (2015) 34th Chinese Control Conference (CCC). IEEE, pp 4156\u20134161. https:\/\/doi.org\/10.1177\/1932296817721519","DOI":"10.1177\/1932296817721519"},{"issue":"4","key":"3042_CR86","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1109\/TBME.2018.2866392","volume":"66","author":"D Shi","year":"2018","unstructured":"Shi D, Dassau E, Doyle FJ (2018) Adaptive zone model predictive control of artificial pancreas based on glucose-and velocity-dependent control penalties. IEEE Trans Biomed Eng 66(4):1045\u20131054. https:\/\/doi.org\/10.1109\/TBME.2018.2866392","journal-title":"IEEE Trans Biomed Eng"},{"issue":"6","key":"3042_CR87","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1089\/dia.2013.0231","volume":"16","author":"RA Harvey","year":"2014","unstructured":"Harvey RA, Dassau E, Bevier WC, Seborg DE, Jovanovi\u010d L, Doyle FJ III, Zisser HC (2014) Clinical evaluation of an automated artificial pancreas using zone-model predictive control and health monitoring system. Diabetes Technology & Therapeutics 16(6):348\u2013357. https:\/\/doi.org\/10.1089\/dia.2013.0231","journal-title":"Diabetes Technology & Therapeutics"},{"key":"3042_CR88","doi-asserted-by":"publisher","unstructured":"Turksoy K, Bayrak ES, Quinn L, Littlejohn E, Cinar A (2013) Adaptive multivariable closed-loop control of blood glucose concentration in patients with type 1 diabetes. In 2013 American Control Conference. IEEE, pp 2905\u20132910. https:\/\/doi.org\/10.1109\/ACC.2013.6580275","DOI":"10.1109\/ACC.2013.6580275"},{"key":"3042_CR89","doi-asserted-by":"publisher","unstructured":"Feng J, Turksoy K, Cinar A (2016) Performance assessment of model-based artificial pancreas control systems. Prediction methods for blood glucose concentration: design, use and evaluation 243\u2013265. https:\/\/doi.org\/10.1007\/978-3-319-25913-0-13","DOI":"10.1007\/978-3-319-25913-0-13"},{"issue":"10","key":"3042_CR90","doi-asserted-by":"publisher","first-page":"2458","DOI":"10.1111\/dom.13408","volume":"20","author":"R Nimri","year":"2018","unstructured":"Nimri R, Dassau E, Segall T, Muller I, Bratina N, Kordonouri O, Bello R, Biester T, Dovc K, Tenenbaum A et al (2018) Adjusting insulin doses in patients with type 1 diabetes who use insulin pump and continuous glucose monitoring: variations among countries and physicians. Diabetes Obes Metab 20(10):2458\u20132466. https:\/\/doi.org\/10.1111\/dom.13408","journal-title":"Diabetes Obes Metab"},{"issue":"7","key":"3042_CR91","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1038\/s42255-020-0212-y","volume":"2","author":"NS Tyler","year":"2020","unstructured":"Tyler NS, Mosquera-Lopez CM, Wilson LM, Dodier RH, Branigan DL, Gabo VB, Guillot FH, Hilts WW, El Youssef J, Castle JR et al (2020) An artificial intelligence decision support system for the management of type 1 diabetes. Nat Metab 2(7):612\u2013619. https:\/\/doi.org\/10.1038\/s42255-020-0212-y","journal-title":"Nat Metab"},{"key":"3042_CR92","doi-asserted-by":"publisher","DOI":"10.1109\/JESTIE.2022.3198504","author":"E Mohammadi","year":"2022","unstructured":"Mohammadi E, Alizadeh M, Asgarimoghaddam M, Wang X, Sim\u00f5es MG (2022) A review on application of artificial intelligence techniques in microgrids. IEEE J Emerg Sel Top Power Electron. https:\/\/doi.org\/10.1109\/JESTIE.2022.3198504","journal-title":"IEEE J Emerg Sel Top Power Electron"},{"issue":"10","key":"3042_CR93","doi-asserted-by":"publisher","first-page":"5097","DOI":"10.3390\/app12105097","volume":"12","author":"S Selvarajan","year":"2022","unstructured":"Selvarajan S, Manoharan H, Hasanin T, Alsini R, Uddin M, Shorfuzzaman M, Alsufyani A (2022) Biomedical signals for healthcare using Hadoop infrastructure with artificial intelligence and fuzzy logic interpretation. Appl Sci 12(10):5097. https:\/\/doi.org\/10.3390\/app12105097","journal-title":"Appl Sci"},{"key":"3042_CR94","doi-asserted-by":"publisher","unstructured":"Al-Fandi M, Jaradat MA, Sardahi Y, Al-Ebbini L, Khaleel M, (2011) Intelligent control of glucose concentration based on an implantable insulin delivery system for type i diabetes, In: 2011 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), IEEE, pp 1\u20136. https:\/\/doi.org\/10.1109\/AEECT.2011.6132531","DOI":"10.1109\/AEECT.2011.6132531"},{"key":"3042_CR95","doi-asserted-by":"publisher","unstructured":"Al-Fandi M, Jaradat MA, Sardahi Y (2012) Optimal pid-fuzzy logic controller for type 1 diabetic patients. In: (2012) 8th International Symposium on Mechatronics and its Applications. IEEE 2012:1\u20137. https:\/\/doi.org\/10.1109\/ISMA.2012.6215171","DOI":"10.1109\/ISMA.2012.6215171"},{"key":"3042_CR96","doi-asserted-by":"publisher","unstructured":"Osgouie KG, Azizi A (2010) Optimizing fuzzy logic controller for diabetes type I by genetic algorithm, In: 2010 the 2nd international conference on computer and automation engineering (ICCAE), vol 2, IEEE, pp 4\u20138. https:\/\/doi.org\/10.1109\/ICCAE.2010.5451208","DOI":"10.1109\/ICCAE.2010.5451208"},{"issue":"2","key":"3042_CR97","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1016\/j.bbe.2018.02.009","volume":"38","author":"S Soylu","year":"2018","unstructured":"Soylu S, Danisman K (2018) In silico testing of optimized fuzzy P+D controller for artificial pancreas. Biocybern Biomed Eng 38(2):399\u2013408. https:\/\/doi.org\/10.1016\/j.bbe.2018.02.009","journal-title":"Biocybern Biomed Eng"},{"key":"3042_CR98","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1109\/ISKE.2008.4730968","volume":"1","author":"S Yasini","year":"2008","unstructured":"Yasini S, Naghibi-Sistani M-B, Karimpour A (2008) Active insulin infusion using fuzzy-based closed-loop control 1:429\u2013434. https:\/\/doi.org\/10.1109\/ISKE.2008.4730968","journal-title":"Active insulin infusion using fuzzy-based closed-loop control"},{"issue":"39","key":"3042_CR99","doi-asserted-by":"publisher","first-page":"15052","DOI":"10.1021\/ie5009647","volume":"53","author":"V Kirubakaran","year":"2014","unstructured":"Kirubakaran V, Radhakrishnan T, Sivakumaran N (2014) Metaheuristic patient estimation based patient-specific fuzzy aggregated artificial pancreas design. Ind Eng Chem Res 53(39):15052-15070.102. https:\/\/doi.org\/10.1021\/ie5009647","journal-title":"Ind Eng Chem Res"},{"issue":"11","key":"3042_CR100","doi-asserted-by":"publisher","first-page":"2201","DOI":"10.1109\/TBME.2006.879461","volume":"53","author":"DU Campos-Delgado","year":"2006","unstructured":"Campos-Delgado DU, Hern\u00e1ndez-Ordo\u00f1ez M, Femat R, Gordillo-Moscoso A (2006) Fuzzy-based controller for glucose regulation in type-1 diabetic patients by subcutaneous route. IEEE Trans Biomed Eng 53(11):2201-2210.103. https:\/\/doi.org\/10.1109\/TBME.2006.879461","journal-title":"IEEE Trans Biomed Eng"},{"key":"3042_CR101","doi-asserted-by":"publisher","first-page":"1973","DOI":"10.1007\/s11517-018-1832-1","volume":"56","author":"A Beneyto","year":"2018","unstructured":"Beneyto A, Vehi J (2018) Postprandial fuzzy adaptive strategy for a hybrid proportional derivative controller for the artificial pancreas. Med Biol Eng Comput 56:1973\u20131986. https:\/\/doi.org\/10.1007\/s11517-018-1832-1","journal-title":"Med Biol Eng Comput"},{"key":"3042_CR102","doi-asserted-by":"publisher","first-page":"105975","DOI":"10.1016\/j.compbiomed.2022.105975","volume":"149","author":"AH Mosavi","year":"2022","unstructured":"Mosavi AH, Mohammadzadeh A, Rathinasamy S, Zhang C, Reuter U, Levente K, Adeli H (2022) Deep learning fuzzy immersion and invariance control for type-I diabetes. Comput Biol Med 149:105975. https:\/\/doi.org\/10.1016\/j.compbiomed.2022.105975","journal-title":"Comput Biol Med"},{"key":"3042_CR103","doi-asserted-by":"publisher","first-page":"107722","DOI":"10.1016\/j.measurement.2020.107722","volume":"158","author":"W Ming","year":"2020","unstructured":"Ming W, Shen F, Li X, Zhang Z, Du J, Chen Z, Chen Y (2020) A comprehensive review of defect detection in 3C glass components. Measurement 158:107722. https:\/\/doi.org\/10.1016\/j.measurement.2020.107722","journal-title":"Measurement"},{"issue":"2","key":"3042_CR104","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1007\/s00449-004-0363-3","volume":"27","author":"AK El-Jabali","year":"2005","unstructured":"El-Jabali AK (2005) Neural network modeling and control of type 1 diabetes mellitus. Bioprocess Biosyst Eng 27(2):75\u201379. https:\/\/doi.org\/10.1007\/s00449-004-0363-3","journal-title":"Bioprocess Biosyst Eng"},{"key":"3042_CR105","doi-asserted-by":"publisher","unstructured":"Mirshekarian S, Shen H, Bunescu R, Marling C (2019) LSTMs and neural attention models for blood glucose prediction: comparative experiments on real and synthetic data. In: 2019 41st annual international conference of the IEEE engineering in medicine and biology society (EMBC). IEEE, pp 706\u2013712. https:\/\/doi.org\/10.1109\/EMBC.2019.8856940","DOI":"10.1109\/EMBC.2019.8856940"},{"key":"3042_CR106","doi-asserted-by":"publisher","first-page":"102120","DOI":"10.1016\/j.artmed.2021.102120","volume":"118","author":"V Felizardo","year":"2021","unstructured":"Felizardo V, Garcia NM, Pombo N, Megdiche I (2021) Data-based algorithms and models using diabetics real data for blood glucose and hypoglycaemia prediction-a systematic literature review. Artif Intell Med 118:102120. https:\/\/doi.org\/10.1016\/j.artmed.2021.102120","journal-title":"Artif Intell Med"},{"issue":"2","key":"3042_CR107","doi-asserted-by":"publisher","first-page":"466","DOI":"10.3390\/s22020466","volume":"22","author":"J Daniels","year":"2022","unstructured":"Daniels J, Herrero P, Georgiou P (2022) A deep learning framework for automatic meal detection and estimation in artificial pancreas systems. Sensors 22(2):466. https:\/\/doi.org\/10.3390\/s22020466","journal-title":"Sensors"},{"issue":"5","key":"3042_CR108","doi-asserted-by":"publisher","first-page":"1851","DOI":"10.1016\/j.jfranklin.2012.02.011","volume":"349","author":"BS Leon","year":"2012","unstructured":"Leon BS, Alanis AY, Sanchez EN, Ornelas-Tellez F, Ruiz-Velazquez E (2012) Inverse optimal neural control of blood glucose level for type 1 diabetes mellitus patients. J Frank Inst 349(5):1851\u20131870. https:\/\/doi.org\/10.1016\/j.jfranklin.2012.02.011","journal-title":"J Frank Inst"},{"issue":"9","key":"3042_CR109","doi-asserted-by":"publisher","first-page":"1122","DOI":"10.1109\/10.709556","volume":"45","author":"Z Trajanoski","year":"1998","unstructured":"Trajanoski Z, Wach P (1998) Neural predictive controller for insulin delivery using the subcutaneous route. IEEE Trans Biomed Eng 45(9):1122\u20131134. https:\/\/doi.org\/10.1109\/10.709556","journal-title":"IEEE Trans Biomed Eng"},{"key":"3042_CR110","doi-asserted-by":"publisher","unstructured":"Ali SF, Padhi R (2009) Optimal blood glucose regulation using single network adaptive critics. In: (2009) IEEE Control Applications, (CCA) & Intelligent Control, (ISIC). IEEE 2009:89\u201394. https:\/\/doi.org\/10.1109\/CCA.2009.5281091","DOI":"10.1109\/CCA.2009.5281091"},{"issue":"2","key":"3042_CR111","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/S1056-8727(00)00137-9","volume":"15","author":"D Dazzi","year":"2001","unstructured":"Dazzi D, Taddei F, Gavarini A, Uggeri E, Negro R, Pezzarossa A (2001) The control of blood glucose in the critical diabetic patient: a neuro-fuzzy method. J Diabetes Complications 15(2):80\u201387. https:\/\/doi.org\/10.1016\/S1056-8727(00)00137-9","journal-title":"J Diabetes Complications"},{"key":"3042_CR112","doi-asserted-by":"publisher","unstructured":"Phee H, Tung W, Quek C (2007) A personalized approach to insulin regulation using brain-inspired neural sematic memory in diabetic glucose control. In: (2007) IEEE congress on evolutionary computation. IEEE 2007:2644\u20132651. https:\/\/doi.org\/10.1109\/CEC.2007.4424804","DOI":"10.1109\/CEC.2007.4424804"},{"issue":"2","key":"3042_CR113","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1177\/1932296818759558","volume":"12","author":"G Cappon","year":"2018","unstructured":"Cappon G, Vettoretti M, Marturano F, Facchinetti A, Sparacino G (2018) A neural-network-based approach to personalize insulin bolus calculation using continuous glucose monitoring. J Diabetes Sci Technol 12(2):265\u2013272. https:\/\/doi.org\/10.1177\/1932296818759558","journal-title":"J Diabetes Sci Technol"},{"issue":"1","key":"3042_CR114","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.cmpb.2011.11.006","volume":"106","author":"JF de Canete","year":"2012","unstructured":"de Canete JF, Gonzalez-Perez S, Ramos-Diaz J (2012) Artificial neural networks for closed loop control of in silico and ad hoc type 1 diabetes. Comput Methods Programs Biomed 106(1):55\u201366. https:\/\/doi.org\/10.1016\/j.cmpb.2011.11.006","journal-title":"Comput Methods Programs Biomed"},{"key":"3042_CR115","doi-asserted-by":"publisher","first-page":"2251","DOI":"10.1109\/TBME.2020.3049109","volume":"68","author":"M Sevil","year":"2021","unstructured":"Sevil M, Rashid M, Hajizadeh I, Park M, Quinn L, Cinar A (2021) Physical activity and psychological stress detection and assessment of their effects on glucose concentration predictions in diabetes management. IEEE Trans Biomed Eng 68:2251\u20132260. https:\/\/doi.org\/10.1109\/TBME.2020.3049109","journal-title":"IEEE Trans Biomed Eng"},{"key":"3042_CR116","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1109\/MCS.2017.2766326","volume":"38","author":"K Turksoy","year":"2018","unstructured":"Turksoy K, Littlejohn E, Cinar A (2018) Multimodule, multivariable artificial pancreas for patients with type 1 diabetes: regulating glucose concentration under challenging conditions. IEEE Control Syst Mag 38:105\u2013124. https:\/\/doi.org\/10.1109\/MCS.2017.2766326","journal-title":"IEEE Control Syst Mag"},{"key":"3042_CR117","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1177\/193229681000400221","volume":"4","author":"Y Leal","year":"2010","unstructured":"Leal Y, Garcia-Gabin W, Bondia J, Esteve E, Ricart W, Fernandez-Real J-M, Vehi J (2010) Real-time glucose estimation algorithm for continuous glucose monitoring using autoregressive models, Journal of Diabetes. Sci Technol 4:391\u2013403. https:\/\/doi.org\/10.1177\/193229681000400221","journal-title":"Sci Technol"},{"key":"3042_CR118","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.conengprac.2017.10.013","volume":"71","author":"X Yu","year":"2018","unstructured":"Yu X, Turksoy K, Rashid M, Feng J, Hobbs N, Hajizadeh I, Samadi S, Sevil M, Lazaro C, Maloney Z, Littlejohn E, Quinn L, Cinar A (2018) Model-fusion-based online glucose concentration predictions in people with type 1 diabetes. Control Eng Pract 71:129\u2013141. https:\/\/doi.org\/10.1016\/j.conengprac.2017.10.013","journal-title":"Control Eng Pract"},{"key":"3042_CR119","doi-asserted-by":"publisher","first-page":"297","DOI":"10.3390\/biomedinformatics2020019","volume":"2","author":"MR Askari","year":"2022","unstructured":"Askari MR, Rashid M, Sun X, Sevil M, Shahidehpour A, Kawaji K, Cinar A (2022) Meal and physical activity detection from free-living data for discovering disturbance patterns of glucose levels in people with diabetes. BioMedInformatics 2:297\u2013317. https:\/\/doi.org\/10.3390\/biomedinformatics2020019","journal-title":"BioMedInformatics"},{"key":"3042_CR120","doi-asserted-by":"publisher","first-page":"816316","DOI":"10.3389\/fcdhc.2022.816316","volume":"3","author":"N Hobbs","year":"2022","unstructured":"Hobbs N, Brandt R, Maghsoudipour S, Sevil M, Rashid M, Quinn L, Cinar A (2022) Observational study of glycemic impact of anticipatory and early-race athletic competition stress in type 1 diabetes. Front Clin Diabetes Healthc 3:816316. https:\/\/doi.org\/10.3389\/fcdhc.2022.816316","journal-title":"Front Clin Diabetes Healthc"},{"key":"3042_CR121","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1109\/JBHI.2017.2677953","volume":"21","author":"S Samadi","year":"2017","unstructured":"Samadi S, Turksoy K, Hajizadeh I, Feng J, Sevil M, Cinar A (2017) Meal detection and carbohydrate estimation using continuous glucose sensor data. IEEE J Biomed Health Inf 21:619\u2013627. https:\/\/doi.org\/10.1109\/JBHI.2017.2677953","journal-title":"IEEE J Biomed Health Inf"},{"key":"3042_CR122","doi-asserted-by":"publisher","first-page":"1091","DOI":"10.1177\/1932296819877217","volume":"13","author":"I Hajizadeh","year":"2019","unstructured":"Hajizadeh I, Hobbs N, Samadi S, Sevil M, Rashid M, Brandt R, Askari MR, Maloney Z, Cinar A (2019) Controlling the AP controller: controller performance assessment and modification, Journal of Diabetes. Sci Technol 13:1091\u20131124. https:\/\/doi.org\/10.1177\/1932296819877217","journal-title":"Sci Technol"},{"key":"3042_CR123","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1109\/TCST.2018.2843785","volume":"28","author":"X Yu","year":"2020","unstructured":"Yu X, Littlejohn E, Quinn L, Cinar A, Rashid M, Feng J, Hobbs N, Hajizadeh I, Samadi S, Sevil M, Lazaro C, Maloney Z (2020) Online glucose prediction using computationally efficient sparse kernel filtering algorithms in type-1 diabetes. IEEE Trans Control Syst Technol 28:3\u201315. https:\/\/doi.org\/10.1109\/TCST.2018.2843785","journal-title":"IEEE Trans Control Syst Technol"},{"key":"3042_CR124","doi-asserted-by":"publisher","first-page":"11506","DOI":"10.1021\/acs.iecr.8b06202","volume":"58","author":"I Hajizadeh","year":"2019","unstructured":"Hajizadeh I, Samadi S, Sevil M, Rashid M, Cinar A (2019) Performance assessment and modification of an adaptive model predictive control for automated insulin delivery by a multivariable artificial pancreas. Ind Eng Chem Res 58:11506\u201311520. https:\/\/doi.org\/10.1021\/acs.iecr.8b06202","journal-title":"Ind Eng Chem Res"},{"key":"3042_CR125","doi-asserted-by":"publisher","first-page":"105386","DOI":"10.1016\/j.conengprac.2022.105386","volume":"131","author":"X Sun","year":"2023","unstructured":"Sun X, Rashid M, Askari MR, Cinar A (2023) Adaptive personalized prior-knowledge-informed model predictive control for type 1 diabetes. Control Eng Pract 131:105386. https:\/\/doi.org\/10.1016\/j.conengprac.2022.105386","journal-title":"Control Eng Pract"},{"key":"3042_CR126","doi-asserted-by":"publisher","first-page":"2275","DOI":"10.1109\/TCST.2023.3291560","volume":"31","author":"X Sun","year":"2023","unstructured":"Sun X, Liu J, Cinar A, Yu X, Tan S (2023) Event-triggered model predictive control for artificial pancreas using prior-knowledge-informed hybrid model. IEEE Trans Control Syst Technol 31:2275\u20132287. https:\/\/doi.org\/10.1109\/TCST.2023.3291560","journal-title":"IEEE Trans Control Syst Technol"},{"key":"3042_CR127","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.jprocont.2019.03.009","volume":"77","author":"I Hajizadeh","year":"2019","unstructured":"Hajizadeh I, Rashid M, Cinar A (2019) Plasma-insulin-cognizant adaptive model predictive control for artificial pancreas systems. J Process Control 77:97\u2013113. https:\/\/doi.org\/10.1016\/j.jprocont.2019.03.009","journal-title":"J Process Control"},{"key":"3042_CR128","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.compchemeng.2018.02.002","volume":"112","author":"J Feng","year":"2018","unstructured":"Feng J, Hajizadeh I, Yu X, Rashid M, Turksoy K, Samadi S, Sevil M, Hobbs N, Brandt R, Lazaro C, Maloney Z, Littlejohn E, Philipson LH, Cinar A (2018) Multi-level supervision and modification of artificial pancreas control system. Comput Chem Eng 112:57\u201369. https:\/\/doi.org\/10.1016\/j.compchemeng.2018.02.002","journal-title":"Comput Chem Eng"},{"key":"3042_CR129","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1002\/aic.16435","volume":"65","author":"J Feng","year":"2019","unstructured":"Feng J, Hajizadeh I, Yu X, Rashid M, Samadi S, Sevil M, Hobbs N, Brandt R, Lazaro C, Maloney Z, Littlejohn E, Quinn L, Cinar A (2019) Multi-model sensor fault detection and data reconciliation: a case study with glucose concentration sensors for diabetes. Am Inst Chem Eng 65:629\u2013639. https:\/\/doi.org\/10.1002\/aic.16435","journal-title":"Am Inst Chem Eng"},{"key":"3042_CR130","doi-asserted-by":"publisher","first-page":"9846","DOI":"10.1021\/acs.iecr.7b01618","volume":"56","author":"I Hajizadeh","year":"2017","unstructured":"Hajizadeh I, Rashid M, Turksoy K, Samadi S, Feng J, Frantz N, Sevil M, Cengiz E, Cinar A (2017) Plasma insulin estimation in people with type 1 diabetes mellitus. Ind Eng Chem Res 56:9846\u20139857. https:\/\/doi.org\/10.1021\/acs.iecr.7b01618","journal-title":"Ind Eng Chem Res"},{"key":"3042_CR131","doi-asserted-by":"publisher","first-page":"107153","DOI":"10.1016\/j.cmpb.2022.107153","volume":"226","author":"N Hobbs","year":"2022","unstructured":"Hobbs N, Samadi S, Rashid M, Shahidehpour A, Askari MR, Park M, Quinn L, Cinar A (2022) A physical activity-intensity driven glycemic model for type 1 diabetes. Comput Methods Programs Biomed 226:107153. https:\/\/doi.org\/10.1016\/j.cmpb.2022.107153","journal-title":"Comput Methods Programs Biomed"},{"key":"3042_CR132","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1177\/1932296818789951","volume":"12","author":"I Hajizadeh","year":"2018","unstructured":"Hajizadeh I, Rashid M, Turksoy K, Samadi S, Feng J, Sevil M, Hobbs N, Lazaro C, Maloney Z, Littlejohn E, Cinar A (2018) Incorporating unannounced meals and exercise in adaptive learning of personalized models for multivariable artificial pancreas systems, Journal of Diabetes. Sci Technol 12:953\u2013966. https:\/\/doi.org\/10.1177\/1932296818789951","journal-title":"Sci Technol"},{"key":"3042_CR133","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.arcontrol.2020.10.004","volume":"50","author":"MR Askari","year":"2020","unstructured":"Askari MR, Hajizadeh I, Rashid M, Hobbs N, Zavala VM, Cinar A (2020) Adaptive-learning model predictive control for complex physiological systems: automated insulin delivery in diabetes. Annua Rev Control 50:1\u201312. https:\/\/doi.org\/10.1016\/j.arcontrol.2020.10.004","journal-title":"Annua Rev Control"},{"key":"3042_CR134","doi-asserted-by":"publisher","first-page":"104551","DOI":"10.1016\/j.bspc.2022.104551","volume":"82","author":"X Sun","year":"2023","unstructured":"Sun X, Cinar A, Liu J, Rashid M, Yu X (2023) Prior-knowledge-embedded model predictive control for blood glucose regulation: towards efficient and safe artificial pancreas. Biomed Signal Process Control 82:104551. https:\/\/doi.org\/10.1016\/j.bspc.2022.104551","journal-title":"Biomed Signal Process Control"},{"key":"3042_CR135","doi-asserted-by":"publisher","first-page":"104933","DOI":"10.1016\/j.conengprac.2021.104933","volume":"116","author":"X Sun","year":"2021","unstructured":"Sun X, Rashid M, Hobbs N, Askari MR, Brandt R, Shahidehpour A, Cinar A (2021) Prior informed regularization of recursively updated latent-variables-based models with missing observations. Control Eng Pract 116:104933. https:\/\/doi.org\/10.1016\/j.conengprac.2021.104933","journal-title":"Control Eng Pract"},{"key":"3042_CR136","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1177\/1932296818763959","volume":"12","author":"I Hajizadeh","year":"2018","unstructured":"Hajizadeh I, Rashid M, Samadi S, Feng J, Sevil M, Hobbs N, Lazaro C, Maloney Z, Brandt R, Yu X, Turksoy K, Littlejohn E, Cengiz E, Cinar A (2018) Adaptive and personalized plasma insulin concentration estimation for artificial pancreas systems, Journal of Diabetes. Sci Technol 12:639\u2013649. https:\/\/doi.org\/10.1177\/1932296818763959","journal-title":"Sci Technol"},{"key":"3042_CR137","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.jprocont.2017.04.004","volume":"60","author":"J Feng","year":"2017","unstructured":"Feng J, Turksoy K, Samadi S, Hajizadeh I, Littlejohn E, Cinar A (2017) Hybrid online sensor error detection and functional redundancy for systems with time-varying parameters. J Process Control 60:115\u2013127. https:\/\/doi.org\/10.1016\/j.jprocont.2017.04.004","journal-title":"J Process Control"},{"key":"3042_CR138","doi-asserted-by":"publisher","first-page":"106565","DOI":"10.1016\/j.compchemeng.2019.106565","volume":"130","author":"M Rashid","year":"2019","unstructured":"Rashid M, Samadi S, Sevil M, Hajizadeh I, Kolodziej P, Hobbs N, Maloney Z, Brandt R, Feng J, Park M, Quinn L, Cinar A (2019) Simulation software for assessment of nonlinear and adaptive multivariable control algorithms: glucose-insulin dynamics in type 1 diabetes. Comput Chem Eng 130:106565. https:\/\/doi.org\/10.1016\/j.compchemeng.2019.106565","journal-title":"Comput Chem Eng"},{"key":"3042_CR139","doi-asserted-by":"publisher","first-page":"1482","DOI":"10.1177\/19322968221102183","volume":"17","author":"MR Askari","year":"2023","unstructured":"Askari MR, Rashid M, Sun X, Sevil M, Shahidehpour A, Kawaji K, Cinar A (2023) Detection of meals and physical activity events from free-living data of people with diabetes, Journal of Diabetes. Sci Technol 17:1482\u20131492. https:\/\/doi.org\/10.1177\/19322968221102183","journal-title":"Sci Technol"},{"key":"3042_CR140","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.jprocont.2019.05.003","volume":"80","author":"I Hajizadeh","year":"2019","unstructured":"Hajizadeh I, Rashid M, Samadi S, Sevil M, Hobbs N, Brandt R, Cinar A (2019) Adaptive personalized multivariable artificial pancreas using plasma insulin estimates. J Process Control 80:26\u201340. https:\/\/doi.org\/10.1016\/j.jprocont.2019.05.003","journal-title":"J Process Control"},{"key":"3042_CR141","doi-asserted-by":"publisher","first-page":"5914","DOI":"10.1021\/acs.iecr.1c04739","volume":"61","author":"X Sun","year":"2022","unstructured":"Sun X, Cinar A, Yu X, Rashid M, Liu J (2022) Kernel-regularized latent-variable regression models for dynamic processes. Ind Eng Chem Res 61:5914\u20135926. https:\/\/doi.org\/10.1021\/acs.iecr.1c04739","journal-title":"Ind Eng Chem Res"},{"key":"3042_CR142","doi-asserted-by":"publisher","first-page":"532","DOI":"10.3390\/s17030532","volume":"17","author":"K Turksoy","year":"2017","unstructured":"Turksoy K, Monforti C, Park M, Griffith G, Quinn L, Cinar A (2017) Use of wearable sensors and biometric variables in an artificial pancreas system. Sensors 17:532. https:\/\/doi.org\/10.3390\/s17030532","journal-title":"Sensors"},{"key":"3042_CR143","doi-asserted-by":"publisher","first-page":"1007-P","DOI":"10.2337\/db20-1007-P","volume":"69","author":"M Rashid","year":"2020","unstructured":"Rashid M, Sevil M, Hobbs N, Hajizadeh I, Askari MR, Brandt R, Park M, Quinn LT, Cinar A (2020) 1007-P: clinical evaluation of multivariable automated insulin delivery. Diabetes Mellitus 69:1007-P. https:\/\/doi.org\/10.2337\/db20-1007-P","journal-title":"Diabetes Mellitus"},{"key":"3042_CR144","doi-asserted-by":"publisher","first-page":"12859","DOI":"10.1109\/JSEN.2020.3000772","volume":"20","author":"M Sevil","year":"2020","unstructured":"Sevil M, Rashid M, Maloney Z, Hajizadeh I, Samadi S, Askari MR, Hobbs N, Brandt R, Park M, Quinn L, Cinar A (2020) Determining physical activity characteristics from wristband data for use in automated insulin delivery systems. IEEE Sens J 20:12859\u201312870. https:\/\/doi.org\/10.1109\/JSEN.2020.3000772","journal-title":"IEEE Sens J"},{"key":"3042_CR145","doi-asserted-by":"publisher","first-page":"188","DOI":"10.3390\/signals1020011","volume":"1","author":"M Sevil","year":"2020","unstructured":"Sevil M, Rashid M, Askari MR, Maloney Z, Hajizadeh I, Cinar A (2020) Detection and characterization of physical activity and psychological stress from wristband data. Signals 1:188\u2013208. https:\/\/doi.org\/10.3390\/signals1020011","journal-title":"Signals"},{"key":"3042_CR146","doi-asserted-by":"publisher","first-page":"105898","DOI":"10.1016\/j.cmpb.2020.105898","volume":"199","author":"M Sevil","year":"2021","unstructured":"Sevil M, Rashid M, Hajizadeh I, Askari MR, Hobbs N, Brandt R, Park M, Quinn L, Cinar A (2021) Discrimination of simultaneous psychological and physical stressors using wristband biosignals. Comput Methods Programs Biomed 199:105898. https:\/\/doi.org\/10.1016\/j.cmpb.2020.105898","journal-title":"Comput Methods Programs Biomed"},{"key":"3042_CR147","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1007\/s11892-017-0920-1","volume":"17","author":"A Cinar","year":"2017","unstructured":"Cinar A (2017) Multivariable adaptive artificial pancreas system in type 1 diabetes. Curr Diab Rep 17:88. https:\/\/doi.org\/10.1007\/s11892-017-0920-1","journal-title":"Curr Diab Rep"},{"key":"3042_CR148","doi-asserted-by":"publisher","first-page":"167","DOI":"10.3390\/signals4010009","volume":"4","author":"M Abdel-Latif","year":"2023","unstructured":"Abdel-Latif M, Askari MR, Rashid MM, Park M, Sharp L, Quinn L, Cinar A (2023) Multi-task classification of physical activity and acute psychological stress for advanced diabetes treatment. Signals 4:167\u2013192. https:\/\/doi.org\/10.3390\/signals4010009","journal-title":"Signals"},{"key":"3042_CR149","doi-asserted-by":"publisher","first-page":"662","DOI":"10.1089\/dia.2018.0072","volume":"20","author":"K Turksoy","year":"2018","unstructured":"Turksoy K, Hajizadeh I, Hobbs N, Kilkus J, Littlejohn E, Samadi S, Feng J, Sevil M, Lazaro C, Ritthaler J, Hibner B, Devine N, Quinn L, Cinar A (2018) Multivariable artificial pancreas for various exercise types and intensities. Diabetes Technol Ther 20:662\u2013671. https:\/\/doi.org\/10.1089\/dia.2018.0072","journal-title":"Diabetes Technol Ther"},{"key":"3042_CR150","doi-asserted-by":"publisher","first-page":"352","DOI":"10.3390\/a15100352","volume":"15","author":"MR Askari","year":"2022","unstructured":"Askari MR, Abdel-Latif M, Rashid M, Sevil M, Cinar A (2022) Detection and classification of unannounced physical activities and acute psychological stress events for interventions in diabetes treatment. Algorithms 15:352. https:\/\/doi.org\/10.3390\/a15100352","journal-title":"Algorithms"},{"key":"3042_CR151","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1016\/j.jcjd.2021.02.002","volume":"45","author":"D Majdpour","year":"2021","unstructured":"Majdpour D, Tsoukas MA, Yale J-F, El Fathi A, Rutkowski J, Rene J, Garfield N, Legault L, Haidar A (2021) Fully automated artificial pancreas for adults with type 1 diabetes using multiple hormones: exploratory experiments. Can J Diabetes 45:734\u2013742. https:\/\/doi.org\/10.1016\/j.jcjd.2021.02.002","journal-title":"Can J Diabetes"},{"key":"3042_CR152","doi-asserted-by":"publisher","first-page":"27","DOI":"10.4093\/dmj.2022.0271","volume":"47","author":"JH Yoo","year":"2023","unstructured":"Yoo JH, Kim JH (2023) Advances in continuous glucose monitoring and integrated devices for management of diabetes with insulin-based therapy: improvement in glycemic control. Diabetes\/Metabolism Research and Reviews 47:27\u201341. https:\/\/doi.org\/10.4093\/dmj.2022.0271","journal-title":"Diabetes\/Metabolism Research and Reviews"},{"key":"3042_CR153","doi-asserted-by":"publisher","first-page":"597","DOI":"10.2337\/dc19-1922","volume":"43","author":"A Haidar","year":"2020","unstructured":"Haidar A, Tsoukas MA, Bernier-Twardy S, Yale J-F, Rutkowski J, Bossy A, Pytka E, El Fathi A, Strauss N, Legault L (2020) A novel dual-hormone insulin-and-pramlintide artificial pancreas for type 1 diabetes: a randomized controlled crossover trial. Diabetes Care 43:597\u2013606. https:\/\/doi.org\/10.2337\/dc19-1922","journal-title":"Diabetes Care"},{"key":"3042_CR154","doi-asserted-by":"publisher","unstructured":"Soylu S, Danisman K, Sacu IE, Alci M (2013) Closed-loop control of blood glucose level in type-1 diabetics: a simulation study. Int Conf Electr Eng 43:371\u2013375. https:\/\/doi.org\/10.1109\/ELECO.2013.6713864","DOI":"10.1109\/ELECO.2013.6713864"},{"key":"3042_CR155","doi-asserted-by":"publisher","unstructured":"Janez A, Battelino T, Klupa T, Kocsis G, Kuricov\u00e1 M, Lali\u0107 N, Stoian AP, Pr\u00e1zn\u00fd M, Raheli\u0107 D, \u0160oupal J, Tankova T, Zelinska N (2021) Hybrid closed-loop systems for the treatment of type 1 diabetes: a collaborative. Expert Group Position Statement for Clinical Use in Central and Eastern Europe, Diabetes Therapy 12:3107\u20133135. https:\/\/doi.org\/10.1007\/s13300-021-01160-5","DOI":"10.1007\/s13300-021-01160-5"},{"key":"3042_CR156","doi-asserted-by":"publisher","first-page":"1456","DOI":"10.1177\/19322968231204884","volume":"17","author":"MR Askari","year":"2023","unstructured":"Askari MR, Ahmadasas M, Shahidehpour A, Rashid M, Quinn L, Park M, Cinar A (2023) Multivariable automated insulin delivery system for handling planned and spontaneous physical activities, Journal of Diabetes. Sci Technol 17:1456\u20131469. https:\/\/doi.org\/10.1177\/19322968231204884","journal-title":"Sci Technol"},{"key":"3042_CR157","doi-asserted-by":"publisher","unstructured":"Tamura T, Tadokoro T, Iwata H, Namikawa T, Hanazaki K, Kawano T (2022) Successful treatment of diabetic ketoacidosis secondary to fulminant type 1 diabetes mellitus using a closed-loop artificial pancreas in a pediatric patient, Journal of. Artif Organs 1\u20134. https:\/\/doi.org\/10.1007\/s10047-022-01378-5","DOI":"10.1007\/s10047-022-01378-5"},{"issue":"1","key":"3042_CR158","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.eprac.2022.11.006","volume":"29","author":"MN Pelkey","year":"2023","unstructured":"Pelkey MN, Boyle ME, Long A, Castro JC, Cook CB, Thompson B (2023) Hybrid closed-loop insulin pump technology can be safely used in the inpatient setting. Endocr Pract 29(1):24\u201328. https:\/\/doi.org\/10.1016\/j.eprac.2022.11.006","journal-title":"Endocr Pract"},{"key":"3042_CR159","doi-asserted-by":"publisher","first-page":"104044","DOI":"10.1016\/j.bspc.2022.104044","volume":"79","author":"H Weng","year":"2023","unstructured":"Weng H, Hettiarachchi C, Nolan C, Suominen H, Lenskiy A (2023) Ensuring security of artificial pancreas device system using homomorphic encryption. Biomed Signal Process Control 79:104044. https:\/\/doi.org\/10.1016\/j.bspc.2022.104044","journal-title":"Biomed Signal Process Control"},{"key":"3042_CR160","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.jprocont.2022.11.008","volume":"121","author":"KD Benam","year":"2023","unstructured":"Benam KD, Khoshamadi H, \u00c5m MK, Stavdahl \u00d8, Gros S, Fougner AL (2023) Identifiable prediction animal model for the bi-hormonal intraperitoneal artificial pancreas. J Process Control 121:13\u201329. https:\/\/doi.org\/10.1016\/j.jprocont.2022.11.008","journal-title":"J Process Control"},{"issue":"9","key":"3042_CR161","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1007\/s11886-022-01733-1","volume":"24","author":"K Zhou","year":"2022","unstructured":"Zhou K, Isaacs D (2022) Closed-loop artificial pancreas therapy for type 1 diabetes. Curr Cardiol Rep 24(9):1159\u20131167. https:\/\/doi.org\/10.1007\/s11886-022-01733-1","journal-title":"Curr Cardiol Rep"},{"key":"3042_CR162","doi-asserted-by":"publisher","unstructured":"Nwokolo M, Hovorka R (2023) The artificial pancreas and type 1 diabetes. J Clin Endocrinol Metab dgad068. https:\/\/doi.org\/10.1210\/clinem\/dgad068","DOI":"10.1210\/clinem\/dgad068"},{"issue":"1","key":"3042_CR163","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1177\/19322968211032249","volume":"16","author":"J Schmitzer","year":"2022","unstructured":"Schmitzer J, Strobel C, Blechschmidt R, Tappe A, Peuscher H (2022) Efficient closed loop simulation of do-it-yourself artificial pancreas systems. J Diabetes Sci Technol 16(1):61\u201369. https:\/\/doi.org\/10.1177\/19322968211032249","journal-title":"J Diabetes Sci Technol"},{"key":"3042_CR164","doi-asserted-by":"publisher","first-page":"154953","DOI":"10.1016\/j.metabol.2021.154953","volume":"127","author":"J Ware","year":"2022","unstructured":"Ware J, Hovorka R (2022) Recent advances in closed-loop insulin delivery. Metabolism 127:154953. https:\/\/doi.org\/10.1016\/j.metabol.2021.154953","journal-title":"Metabolism"},{"issue":"12","key":"3042_CR165","doi-asserted-by":"publisher","first-page":"10936","DOI":"10.3390\/s101210936","volume":"10","author":"P Rossetti","year":"2010","unstructured":"Rossetti P, Bondia J, Veh\u00ed J, Fanelli CG (2010) Estimating plasma glucose from interstitial glucose: the issue of calibration algorithms in commercial continuous glucose monitoring devices. Sensors 10(12):10936\u201310952. https:\/\/doi.org\/10.3390\/s101210936","journal-title":"Sensors"},{"issue":"4","key":"3042_CR166","doi-asserted-by":"publisher","first-page":"766","DOI":"10.1177\/1932296817699637","volume":"11","author":"T Siegmund","year":"2017","unstructured":"Siegmund T, Heinemann L, Kolassa R, Thomas A (2017) Discrepancies between blood glucose and interstitial glucose-technological artifacts or physiology: implications for selection of the appropriate therapeutic target. J Diabetes Sci Technol 11(4):766\u2013772. https:\/\/doi.org\/10.1177\/1932296817699637","journal-title":"J Diabetes Sci Technol"},{"issue":"11","key":"3042_CR167","doi-asserted-by":"publisher","first-page":"2672","DOI":"10.2337\/db11-0654","volume":"60","author":"C Cobelli","year":"2011","unstructured":"Cobelli C, Renard E, Kovatchev B (2011) Artificial pancreas: past, present, future. Diabetes 60(11):2672\u20132682. https:\/\/doi.org\/10.2337\/db11-0654","journal-title":"Diabetes"},{"key":"3042_CR168","doi-asserted-by":"publisher","unstructured":"Vosoughi R, Goghari ZS, Jafari AH (2022) Modelling system of two insulin-glucose delays to achieve the dynamics of glucose changes. J Biomed Phys Eng 12(2):189. https:\/\/doi.org\/10.31661\/jbpe.v0i0.1207","DOI":"10.31661\/jbpe.v0i0.1207"},{"key":"3042_CR169","doi-asserted-by":"publisher","first-page":"109845","DOI":"10.1016\/j.chaos.2020.109845","volume":"137","author":"A-BA Al-Hussein","year":"2020","unstructured":"Al-Hussein A-BA, Rahma F, Jafari S (2020) Hopf bifurcation and chaos in time-delay model of glucose-insulin regulatory system. Chaos Solit Fractals 137:109845. https:\/\/doi.org\/10.1016\/j.chaos.2020.109845","journal-title":"Chaos Solit Fractals"},{"issue":"2","key":"3042_CR170","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/j.addr.2003.08.011","volume":"56","author":"GM Steil","year":"2004","unstructured":"Steil GM, Panteleon AE, Rebrin K (2004) Closed-loop insulin delivery-the path to physiological glucose control. Adv Drug Deliv Rev 56(2):125\u2013144. https:\/\/doi.org\/10.1016\/j.addr.2003.08.011","journal-title":"Adv Drug Deliv Rev"},{"issue":"3","key":"3042_CR171","doi-asserted-by":"publisher","first-page":"593","DOI":"10.2337\/diacare.25.3.593","volume":"25","author":"J Pickup","year":"2002","unstructured":"Pickup J, Keen H (2002) Continuous subcutaneous insulin infusion at 25 years: evidence base for the expanding use of insulin pump therapy in type 1 diabetes. Diabetes Care 25(3):593\u2013598. https:\/\/doi.org\/10.2337\/diacare.25.3.593","journal-title":"Diabetes Care"},{"issue":"4","key":"3042_CR172","doi-asserted-by":"publisher","first-page":"331","DOI":"10.2337\/diab.32.4.331","volume":"32","author":"T Kobayashi","year":"1983","unstructured":"Kobayashi T, Sawano S, Itoh T, Kosaka K, Hirayama H, Kasuya Y (1983) The pharmacokinetics of insulin after continuous subcutaneous infusion or bolus subcutaneous injection in diabetic patients. Diabetes 32(4):331\u2013336. https:\/\/doi.org\/10.2337\/diab.32.4.331","journal-title":"Diabetes"},{"issue":"6","key":"3042_CR173","doi-asserted-by":"publisher","first-page":"657","DOI":"10.2337\/diab.41.6.657","volume":"41","author":"WC Duckworth","year":"1992","unstructured":"Duckworth WC, Saudek CD, Henry RR (1992) Why intraperitoneal delivery of insulin with implantable pumps in NIDDM? Diabetes 41(6):657\u2013661. https:\/\/doi.org\/10.2337\/diab.41.6.657","journal-title":"Diabetes"},{"key":"3042_CR174","doi-asserted-by":"publisher","unstructured":"Guo X, Tan L, Xie Z, Zhang L, Zhang G, Ming W (2024) Simulation and experimentation of renewable dielectric gap flow fields in EDM. Int J Adv Manuf Technol 130:1935\u20131948. https:\/\/doi.org\/10.1007\/s00170-023-12772-5","DOI":"10.1007\/s00170-023-12772-5"},{"key":"3042_CR175","doi-asserted-by":"publisher","unstructured":"Tenorio FS, Martins LEG, Cunha TS (2021) Accuracy of a low-cost continuous subcutaneous insulin infusion pump prototype: in vitro study using combined methodologies. Ann Biomed Eng 49:1761\u20131773. https:\/\/doi.org\/10.1007\/s10439-020-02721-8","DOI":"10.1007\/s10439-020-02721-8"},{"issue":"11","key":"3042_CR176","doi-asserted-by":"publisher","first-page":"877","DOI":"10.1080\/17434440.2022.2150546","volume":"19","author":"DL Rodr\u00edguez-Sarmiento","year":"2022","unstructured":"Rodr\u00edguez-Sarmiento DL, Le\u00f3n-Vargas F, Garc\u00eda-Jaramillo M (2022) Artificial pancreas systems: experiences from concept to commercialisation. Expert Rev Med Devices 19(11):877\u2013894. https:\/\/doi.org\/10.1080\/17434440.2022.2150546","journal-title":"Expert Rev Med Devices"},{"issue":"1","key":"3042_CR177","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.diabet.2018.04.003","volume":"45","author":"A Quintal","year":"2019","unstructured":"Quintal A, Messier V, Rabasa-Lhoret R, Racine E (2019) A critical review and analysis of ethical issues associated with the artificial pancreas. Diabetes Metab 45(1):1\u201310. https:\/\/doi.org\/10.1016\/j.diabet.2018.04.003","journal-title":"Diabetes Metab"}],"container-title":["Medical & Biological Engineering & Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-024-03042-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-024-03042-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-024-03042-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T23:08:31Z","timestamp":1715123311000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-024-03042-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,28]]},"references-count":177,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2024,6]]}},"alternative-id":["3042"],"URL":"https:\/\/doi.org\/10.1007\/s11517-024-03042-x","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,28]]},"assertion":[{"value":"30 June 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 February 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}