人工胰腺的探索：技术与治疗相结合
Quest for the artificial pancreas: combining technology with treatment.
作者信息
Harvey Rebecca A, Wang Youqing, Grosman Benyamin, Percival Matthew W, Bevier Wendy, Finan Daniel A, Zisser Howard, Seborg Dale E, Jovanovic Lois, Doyle Francis J, Dassau Eyal
机构信息
Chemical Engineering, Northeastern University, Boston, Massachusetts, USA.
出版信息
IEEE Eng Med Biol Mag. 2010 Mar-Apr;29(2):53-62. doi: 10.1109/MEMB.2009.935711.
Abstract
The various components of the artificial pancreas puzzle are being put into place. Features such as communication, control, modeling, and learning are being realized presently. Steps have been set in motion to carry the conceptual design through simulation to clinical implementation. The challenging pieces still to be addressed include stress and exercise; as integral parts of the ultimate goal, effort has begun to shift toward overcoming the remaining hurdles to the full artificial pancreas. The artificial pancreas is close to becoming a reality, driven by technology, and the expectation that lives will be improved.
摘要
人工胰腺难题的各个组成部分正在逐步就位。诸如通信、控制、建模和学习等功能目前正在得以实现。已经启动了相关步骤，以将概念设计从模拟推进到临床应用。仍有待解决的具有挑战性的部分包括压力和运动；作为最终目标的组成部分，人们已开始努力克服全面实现人工胰腺的剩余障碍。在技术以及改善生活的期望推动下，人工胰腺已接近成为现实。
相似文献
1
Quest for the artificial pancreas: combining technology with treatment.
IEEE Eng Med Biol Mag. 2010 Mar-Apr;29(2):53-62. doi: 10.1109/MEMB.2009.935711.
2
Artificial Pancreas: Current Progress and Future Outlook in the Treatment of Type 1 Diabetes.
Drugs. 2019 Jul;79(10):1089-1101. doi: 10.1007/s40265-019-01149-2.
3
[The artificial pancreas, a dream on the point of becoming reality].
Rev Infirm. 2017 Apr;66(230):35-37. doi: 10.1016/j.revinf.2017.02.010.
4
An artificial pancreas for automated blood glucose control in patients with Type 1 diabetes.
Ther Deliv. 2015;6(5):609-19. doi: 10.4155/tde.15.12.
5
A Novel Needle-Injectable Millimeter scale Wireless Electrochemical Glucose Sensing Platform for Artificial Pancreas Applications.
Sci Rep. 2019 Nov 22;9(1):17421. doi: 10.1038/s41598-019-53680-7.
6
First application of a transcutaneous optical single-port glucose monitoring device in patients with type 1 diabetes mellitus.
Biosens Bioelectron. 2017 Feb 15;88:240-248. doi: 10.1016/j.bios.2016.08.039. Epub 2016 Aug 13.
7
The artificial pancreas: current status and future prospects in the management of diabetes.
Ann N Y Acad Sci. 2014 Apr;1311:102-23. doi: 10.1111/nyas.12431.
8
Advancement of the artificial pancreas through the development of interoperability standards.
J Diabetes Sci Technol. 2013 Jul 1;7(4):1066-70. doi: 10.1177/193229681300700431.
9
Insulin Infusion Sets and Continuous Glucose Monitoring Sensors: Where the Artificial Pancreas Meets the Patient.
Diabetes Technol Ther. 2017 Apr;19(4):206-208. doi: 10.1089/dia.2017.0048.
10
Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.
Artif Intell Med. 2019 Jul;98:109-134. doi: 10.1016/j.artmed.2019.07.007. Epub 2019 Jul 26.
引用本文的文献
1
A new multivariate blood glucose prediction method with hybrid feature clustering and online transfer learning.
Health Inf Sci Syst. 2024 Nov 17;12(1):57. doi: 10.1007/s13755-024-00313-7. eCollection 2024 Dec.
2
Practicing Digital Gastroenterology through Phonoenterography Leveraging Artificial Intelligence: Future Perspectives Using Microwave Systems.
Sensors (Basel). 2023 Feb 18;23(4):2302. doi: 10.3390/s23042302.
3
Utility of Big Data in Predicting Short-Term Blood Glucose Levels in Type 1 Diabetes Mellitus Through Machine Learning Techniques.
Sensors (Basel). 2019 Oct 16;19(20):4482. doi: 10.3390/s19204482.
4
Parameter estimation of a meal glucose-insulin model for TIDM patients from therapy historical data.
IET Syst Biol. 2019 Feb;13(1):8-15. doi: 10.1049/iet-syb.2018.5038.
5
Control Limitations in Models of T1DM and the Robustness of Optimal Insulin Delivery.
J Diabetes Sci Technol. 2018 Sep;12(5):926-936. doi: 10.1177/1932296818789950. Epub 2018 Jul 31.
6
Body Mass Index Effect on Differing Responses to Psychological Stress in Blood Glucose Dynamics in Patients With Type 1 Diabetes.
J Diabetes Sci Technol. 2018 May;12(3):657-664. doi: 10.1177/1932296818758103. Epub 2018 Feb 8.
7
State Estimation with Sensor Recalibrations and Asynchronous Measurements for MPC of an Artificial Pancreas to Treat T1DM.
Proc IFAC World Congress. 2014 Aug;47(3):224-230. doi: 10.3182/20140824-6-ZA-1003.01085.
8
MPC Design for Rapid Pump-Attenuation and Expedited Hyperglycemia Response to Treat T1DM with an Artificial Pancreas.
Proc Am Control Conf. 2014 Jun;2014:4224-4230. doi: 10.1109/ACC.2014.6859247. Epub 2014 Jul 21.
9
Moving-horizon-like state estimation via continuous glucose monitor feedback in MPC of an artificial pancreas for type 1 diabetes.
Proc IEEE Conf Decis Control. 2014 Dec;2014:310-315. doi: 10.1109/CDC.2014.7039399. Epub 2015 Feb 12.
10
Periodic zone-MPC with asymmetric costs for outpatient-ready safety of an artificial pancreas to treat type 1 diabetes.
Automatica (Oxf). 2016 Sep;71:237-246. doi: 10.1016/j.automatica.2016.04.015. Epub 2016 Jun 1.
本文引用的文献
1
Real-Time hypoglycemia prediction suite using continuous glucose monitoring: a safety net for the artificial pancreas.
Diabetes Care. 2010 Jun;33(6):1249-54. doi: 10.2337/dc09-1487.
2
Experimental evaluation of a recursive model identification technique for type 1 diabetes.
J Diabetes Sci Technol. 2009 Sep 1;3(5):1192-202. doi: 10.1177/193229680900300526.
3
Enhanced 911/global position system wizard: a telemedicine application for the prevention of severe hypoglycemia--monitor, alert, and locate.
J Diabetes Sci Technol. 2009 Nov 1;3(6):1501-6. doi: 10.1177/193229680900300632.
4
Safety constraints in an artificial pancreatic beta cell: an implementation of model predictive control with insulin on board.
J Diabetes Sci Technol. 2009 May 1;3(3):536-44. doi: 10.1177/193229680900300319.
5
Clinical update on optimal prandial insulin dosing using a refined run-to-run control algorithm.
J Diabetes Sci Technol. 2009 May 1;3(3):487-91. doi: 10.1177/193229680900300312.
6
Modular artificial beta-cell system: a prototype for clinical research.
J Diabetes Sci Technol. 2008 Sep;2(5):863-72. doi: 10.1177/193229680800200518.
7
Closed-loop control and advisory mode evaluation of an artificial pancreatic Beta cell: use of proportional-integral-derivative equivalent model-based controllers.
J Diabetes Sci Technol. 2008 Jul;2(4):636-44. doi: 10.1177/193229680800200415.
8
Physical activity-the major unaccounted impediment to closed loop control.
J Diabetes Sci Technol. 2008 Jan;2(1):169-74. doi: 10.1177/193229680800200127.
9
Telemedicine and diabetes management: current challenges and future research directions.
J Diabetes Sci Technol. 2008 Jan;2(1):98-104. doi: 10.1177/193229680800200114.
10
Closed-loop control of artificial pancreatic Beta -cell in type 1 diabetes mellitus using model predictive iterative learning control.
IEEE Trans Biomed Eng. 2010 Feb;57(2):211-9. doi: 10.1109/TBME.2009.2024409. Epub 2009 Jun 12.
Zotero 插件