{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T20:02:01Z","timestamp":1780603321396,"version":"3.54.1"},"reference-count":33,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.bspc.2026.110606","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T19:45:21Z","timestamp":1779479121000},"page":"110606","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Toward clinically interpretable control: Nonlinear MPC for safe and efficient automated insulin delivery"],"prefix":"10.1016","volume":"124","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-1163-8774","authenticated-orcid":false,"given":"Muhammad","family":"Ramzan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8692-173X","authenticated-orcid":false,"given":"Adeel","family":"Iqbal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9330-369X","authenticated-orcid":false,"given":"Ali","family":"Khaqan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4640-8496","authenticated-orcid":false,"given":"Raja Ali","family":"Riaz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0191-9302","authenticated-orcid":false,"given":"Syed Abdul Mannan","family":"Kirmani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9687-1385","authenticated-orcid":false,"given":"Mohammad","family":"Arif","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6113-123X","authenticated-orcid":false,"given":"Tahir","family":"Khurshaid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.bspc.2026.110606_b1","series-title":"Diabetes fact sheet","author":"World Health Organization","year":"2021"},{"key":"10.1016\/j.bspc.2026.110606_b2","doi-asserted-by":"crossref","first-page":"1621","DOI":"10.1177\/193229681300700623","article-title":"Algorithms for a closed-loop artificial pancreas: the case for proportional-integral-derivative control","volume":"7","author":"Steil","year":"2013","journal-title":"J. Diabetes Sci. Technol."},{"key":"10.1016\/j.bspc.2026.110606_b3","series-title":"IDF Diabetes Atlas, 10th edition","author":"Magliano","year":"2021"},{"key":"10.1016\/j.bspc.2026.110606_b4","first-page":"85","article-title":"Global epidemiology of type 2 diabetes and its cardiovascular implications","volume":"15","author":"Zheng","year":"2018","journal-title":"Nat Rev Cardiol"},{"key":"10.1016\/j.bspc.2026.110606_b5","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1088\/0967-3334\/25\/4\/010","article-title":"Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes","volume":"25","author":"Hovorka","year":"2004","journal-title":"Physiol. Meas."},{"key":"10.1016\/j.bspc.2026.110606_b6","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.2337\/dc13-2108","article-title":"Closed-loop artificial pancreas systems: engineering the algorithms","volume":"37","author":"Doyle III","year":"2014","journal-title":"Diabetes Care"},{"key":"10.1016\/j.bspc.2026.110606_b7","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.ifacol.2018.11.644","article-title":"A nonlinear model predictive control strategy for glucose control in people with type 1 diabetes","volume":"51","author":"Boiroux","year":"2018","journal-title":"IFAC-PapersOnLine"},{"key":"10.1016\/j.bspc.2026.110606_b8","series-title":"2021 7th International Conference on Control, Instrumentation and Automation","first-page":"1","article-title":"A nonlinear mpc approach for blood glucose regulation in diabetic patients","author":"Mirzaee","year":"2021"},{"key":"10.1016\/j.bspc.2026.110606_b9","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.1007\/s11517-022-02511-5","article-title":"Extended kalman filter state estimation\u2013based nonlinear explicit model predictive control design for blood glucose regulation of type 1 diabetic patient","volume":"60","author":"Acharya","year":"2022","journal-title":"Med. Biol. Eng. Comput."},{"key":"10.1016\/j.bspc.2026.110606_b10","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/j.bspc.2009.04.003","article-title":"Model predictive control of glucose concentration in type i diabetic patients: An in silico trial","volume":"4","author":"Magni","year":"2009","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.bspc.2026.110606_b11","article-title":"Receding horizon control of type 1 diabetes mellitus by using nonlinear programming","volume":"2018","author":"Khan","year":"2018","journal-title":"Complexity"},{"key":"10.1016\/j.bspc.2026.110606_b12","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1016\/j.ifacol.2022.07.561","article-title":"Nonlinear model predictive control and system identification for a dual-hormone artificial pancreas","volume":"55","author":"Reenberg","year":"2022","journal-title":"IFAC-PapersOnLine"},{"key":"10.1016\/j.bspc.2026.110606_b13","doi-asserted-by":"crossref","DOI":"10.1016\/j.conengprac.2023.105810","article-title":"Model predictive control (mpc) of an artificial pancreas with data-driven learning of multi-step-ahead blood glucose predictors","volume":"144","author":"Aiello","year":"2024","journal-title":"Control Eng. Pract."},{"key":"10.1016\/j.bspc.2026.110606_b14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.arcontrol.2020.10.004","article-title":"Adaptive-learning model predictive control for complex physiological systems: Automated insulin delivery in diabetes","volume":"50","author":"Askari","year":"2020","journal-title":"Annu. Rev. Control."},{"key":"10.1016\/j.bspc.2026.110606_b15","series-title":"A contraction theory approach to observer-based controller design for glucose regulation in type 1 diabetes with intra-patient variability","author":"Dey","year":"2022"},{"key":"10.1016\/j.bspc.2026.110606_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2025.110147","article-title":"Deep reinforcement learning for type 1 diabetes: Dual ppo controller for personalized insulin management","volume":"191","author":"Marchetti","year":"2025","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.bspc.2026.110606_b17","article-title":"A safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning","volume":"20","author":"Zhao","year":"2025","journal-title":"Plos One"},{"key":"10.1016\/j.bspc.2026.110606_b18","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1186\/s13098-022-00962-2","article-title":"Effectiveness and safety of a model predictive control (mpc) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (t1d): systematic review and meta-analysis","volume":"14","author":"Kang","year":"2022","journal-title":"Diabetol. Metab. Syndr."},{"key":"10.1016\/j.bspc.2026.110606_b19","doi-asserted-by":"crossref","DOI":"10.1111\/dom.16499","article-title":"Fully automated insulin delivery systems in type 1 diabetes: A systematic review and meta-analysis","author":"Fan","year":"2025","journal-title":"Diabetes, Obes. Metab."},{"key":"10.1016\/j.bspc.2026.110606_b20","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1186\/s13098-025-01819-0","article-title":"Effectiveness and safety of ai-driven closed-loop systems in diabetes management: a systematic review and meta-analysis","volume":"17","author":"Wang","year":"2025","journal-title":"Diabetol. Metab. Syndr."},{"key":"10.1016\/j.bspc.2026.110606_b21","doi-asserted-by":"crossref","DOI":"10.1016\/j.diabres.2022.110052","article-title":"Long-term outcomes of an advanced hybrid closed-loop system: a focus on different subpopulations","volume":"191","author":"Beato-V\u00edbora","year":"2022","journal-title":"Diabetes Res. Clin. Pract."},{"key":"10.1016\/j.bspc.2026.110606_b22","doi-asserted-by":"crossref","first-page":"9672","DOI":"10.1016\/j.ifacol.2023.10.276","article-title":"Choki-based mpc for blood glucose regulation in artificial pancreas","volume":"56","author":"Sonzogni","year":"2023","journal-title":"IFAC-PapersOnLine"},{"key":"10.1016\/j.bspc.2026.110606_b23","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1016\/j.ifacol.2017.08.271","article-title":"Mpc model individualization in free-living conditions: a proof-of-concept case study","volume":"50","author":"Toffanin","year":"2017","journal-title":"IFAC-PapersOnLine"},{"key":"10.1016\/j.bspc.2026.110606_b24","doi-asserted-by":"crossref","first-page":"1052","DOI":"10.3182\/20100901-3-IT-2016.00289","article-title":"Meal estimation in nonlinear model predictive control for type 1 diabetes","volume":"43","author":"Boiroux","year":"2010","journal-title":"IFAC Proc. Vol."},{"key":"10.1016\/j.bspc.2026.110606_b25","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/s42234-018-0015-6","article-title":"Automated closed-loop control of diabetes: the artificial pancreas","volume":"4","author":"Kovatchev","year":"2018","journal-title":"Bioelectron. Med."},{"key":"10.1016\/j.bspc.2026.110606_b26","doi-asserted-by":"crossref","first-page":"1614","DOI":"10.1210\/clinem\/dgad068","article-title":"The artificial pancreas and type 1 diabetes","volume":"108","author":"Nwokolo","year":"2023","journal-title":"J. Clin. Endocrinol. Metab."},{"key":"10.1016\/j.bspc.2026.110606_b27","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1080\/17434440.2024.2406901","article-title":"Closed-loop systems: recent advancements and lived experiences","volume":"21","author":"Kadiyala","year":"2024","journal-title":"Expert. Rev. Med. Devices"},{"key":"10.1016\/j.bspc.2026.110606_b28","series-title":"Precise insulin delivery for artificial pancreas: A reinforcement learning optimized adaptive fuzzy control approach","author":"Mameche","year":"2025"},{"key":"10.1016\/j.bspc.2026.110606_b29","doi-asserted-by":"crossref","first-page":"1593","DOI":"10.2337\/dci19-0028","article-title":"Clinical targets for continuous glucose monitoring data interpretation: Recommendations from the international consensus on time in range","volume":"42","author":"Battelino","year":"2019","journal-title":"Diabetes Care"},{"key":"10.1016\/j.bspc.2026.110606_b30","doi-asserted-by":"crossref","first-page":"S61","DOI":"10.2337\/dc19-S006","article-title":"6. Glycemic targets: standards of medical care in diabetes\u20142019","volume":"42","author":"Care","year":"2019","journal-title":"Diabetes Care"},{"key":"10.1016\/j.bspc.2026.110606_b31","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1177\/1932296818822496","article-title":"The relationships between time in range, hyperglycemia metrics, and hba1c","volume":"13","author":"Beck","year":"2019","journal-title":"J. Diabetes Sci. Technol."},{"key":"10.1016\/j.bspc.2026.110606_b32","series-title":"Fda interoperability designation\u2014creating options for people with diabetes and pump companies: regulatory, technological, and commercial perspectives","author":"Klonoff","year":"2025"},{"key":"10.1016\/j.bspc.2026.110606_b33","series-title":"Special controls and guidance for integrated continuous glucose monitoring (icgm) and automated insulin dosing (aid) systems","author":"U.S. Food and Drug Administration","year":"2023"}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426011602?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426011602?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T19:33:00Z","timestamp":1780601580000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1746809426011602"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":33,"alternative-id":["S1746809426011602"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110606","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Toward clinically interpretable control: Nonlinear MPC for safe and efficient automated insulin delivery","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110606","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110606"}}