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Montain ME, Blanco AM, Bandoni JA. Optimal drug infusion profiles using a Particle Swarm Optimization algorithm. Comput Chem Eng 2015. [DOI: 10.1016/j.compchemeng.2015.05.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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2
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Montain ME, Blanco AM, Bandoni JA. Integrated Dynamic Physiological Model for Drug Infusion Simulation Studies. Ind Eng Chem Res 2014. [DOI: 10.1021/ie5008823] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- M. Elisa Montain
- Planta Piloto de Ingeniería Química, PLAPIQUI (UNS−CONICET) Camino La Carrindanga km. 7, 8000 Bahía Blanca, Argentina
| | - Aníbal M. Blanco
- Planta Piloto de Ingeniería Química, PLAPIQUI (UNS−CONICET) Camino La Carrindanga km. 7, 8000 Bahía Blanca, Argentina
| | - J. Alberto Bandoni
- Planta Piloto de Ingeniería Química, PLAPIQUI (UNS−CONICET) Camino La Carrindanga km. 7, 8000 Bahía Blanca, Argentina
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Lee JJ, Dassau E, Zisser H, Doyle FJ. Design and in silico evaluation of an intraperitoneal-subcutaneous (IP-SC) artificial pancreas. Comput Chem Eng 2014; 70:180-188. [PMID: 25267863 DOI: 10.1016/j.compchemeng.2014.02.024] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Prandial glucose regulation is a major challenge for the artificial pancreas using subcutaneous insulin (without a feedforward bolus) due to insulin's slow absorption-peak (50-60 min). Intraperitoneal insulin, with a fast absorption peak (20-25 min), has been suggested as an alternative to address these limitations. An artificial pancreas using intraperitoneal insulin was designed and evaluated on 100 in silico subjects and compared with two designs using subcutaneous insulin with and without a feedforward bolus, following the three meal (40-70 g-carbohydrates) evaluation protocol. The design using intraperitoneal insulin resulted in a significantly lower postprandial blood glucose peak (38 mg/dL) and longer time in the clinically accepted region (13%) compared to the design using subcutaneous insulin without a feedforward bolus and comparable results to a subcutaneous feedforward bolus design. This superior regulation with minimal user interaction may improve the quality of life for people with type 1 diabetes mellitus.
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Affiliation(s)
- Justin J Lee
- Department of Chemical Engineering, The University of California, Santa Barbara, CA 93106-5080, USA.,Sansum Diabetes Research Institute, 2219 Bath Street, Santa Barbara, CA 93105-4321, USA
| | - Eyal Dassau
- Department of Chemical Engineering, The University of California, Santa Barbara, CA 93106-5080, USA.,Sansum Diabetes Research Institute, 2219 Bath Street, Santa Barbara, CA 93105-4321, USA
| | - Howard Zisser
- Department of Chemical Engineering, The University of California, Santa Barbara, CA 93106-5080, USA.,Sansum Diabetes Research Institute, 2219 Bath Street, Santa Barbara, CA 93105-4321, USA
| | - Francis J Doyle
- Department of Chemical Engineering, The University of California, Santa Barbara, CA 93106-5080, USA.,Sansum Diabetes Research Institute, 2219 Bath Street, Santa Barbara, CA 93105-4321, USA
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Ionescu CM, Nascu I, De Keyser R. Lessons learned from closed loops in engineering: towards a multivariable approach regulating depth of anaesthesia. J Clin Monit Comput 2013; 28:537-46. [PMID: 24271330 DOI: 10.1007/s10877-013-9535-5] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2013] [Accepted: 11/15/2013] [Indexed: 11/29/2022]
Abstract
In this paper is presented a brief state of art regarding the multivariable formulation for controlling the depth of anaesthesia by means of two intravenously administrated drugs, i.e. propofol and remifentanil. In a feasibility study of determining a suitable variable to quantify analgesia levels in patients undergoing cardiac surgery, the bispectral index and an electromyogram-based surrogate variable are proposed as the controlled variables. The study is carried on in the context of implementing a multivariable predictive control algorithm. The simulation results show that such a paradigm is feasible, although it does not guarantee perfect knowledge of the analgesia level-in other words, the variable is not validated against typical evaluations of the pain levels (e.g. clinical scores).
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Affiliation(s)
- Clara M Ionescu
- Department of Electrical Energy, Systems and Automation, Faculty of Engineering and Architecture, Ghent University, Technologiepark 913, 9052, Gent-Zwijnaarde, Belgium,
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Linninger AA. Biomedical systems research—New perspectives opened by quantitative medical imaging. Comput Chem Eng 2012. [DOI: 10.1016/j.compchemeng.2011.07.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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6
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Percival M, Wang Y, Grosman B, Dassau E, Zisser H, Jovanovič L, Doyle F. Development of a multi-parametric model predictive control algorithm for insulin delivery in type 1 diabetes mellitus using clinical parameters. JOURNAL OF PROCESS CONTROL 2011; 21:391-404. [PMID: 21516218 PMCID: PMC3079204 DOI: 10.1016/j.jprocont.2010.10.003] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
A multi-parametric model predictive control (mpMPC) algorithm for subcutaneous insulin delivery for individuals with type 1 diabetes mellitus (T1DM) that is computationally efficient, robust to variations in insulin sensitivity, and involves minimal burden for the user is proposed. System identification was achieved through impulse response tests feasible for ambulatory conditions on the UVa/Padova simulator adult subjects with T1DM. An alternative means of system identification using readily available clinical parameters was also investigated. A safety constraint was included explicitly in the algorithm formulation using clinical parameters typical of those available to an attending physician. Closed-loop simulations were carried out with daily consumption of 200 g carbohydrate. Controller robustness was assessed by subject/model mismatch scenarios addressing daily, simultaneous variation in insulin sensitivity and meal size with the addition of Gaussian white noise with a standard deviation of 10%. A second-order-plus-time-delay transfer function model fit the validation data with a mean (coefficient of variation) root-mean-square-error (RMSE) of 26 mg/dL (19%) for a 3 h prediction horizon. The resulting control law maintained a low risk Low Blood Glucose Index without any information about carbohydrate consumption for 90% of the subjects. Low-order linear models with clinically meaningful parameters thus provided sufficient information for a model predictive control algorithm to control glycemia. The use of clinical knowledge as a safety constraint can reduce hypoglycemic events, and this same knowledge can further improve glycemic control when used explicitly as the controller model. The resulting mpMPC algorithm was sufficiently compact to be implemented on a simple electronic device.
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Affiliation(s)
- M.W. Percival
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, United States
- Sansum Diabetes Research Institute, Santa Barbara, CA 93105-4321, United States
| | - Y. Wang
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, United States
- Sansum Diabetes Research Institute, Santa Barbara, CA 93105-4321, United States
| | - B. Grosman
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, United States
- Sansum Diabetes Research Institute, Santa Barbara, CA 93105-4321, United States
| | - E. Dassau
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, United States
- Sansum Diabetes Research Institute, Santa Barbara, CA 93105-4321, United States
| | - H. Zisser
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, United States
- Sansum Diabetes Research Institute, Santa Barbara, CA 93105-4321, United States
| | - L. Jovanovič
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, United States
- Sansum Diabetes Research Institute, Santa Barbara, CA 93105-4321, United States
| | - F.J. Doyle
- Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, United States
- Sansum Diabetes Research Institute, Santa Barbara, CA 93105-4321, United States
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Sreenivas Y, Yeng TW, Rangaiah GP, Lakshminarayanan S. A Comprehensive Evaluation of PID, Cascade, Model-Predictive, and RTDA Controllers for Regulation of Hypnosis. Ind Eng Chem Res 2009. [DOI: 10.1021/ie800927u] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Yelneedi Sreenivas
- Department of Chemical & Biomolecular Engineering, National University of Singapore, Singapore 117576
| | - Tian Woon Yeng
- Department of Chemical & Biomolecular Engineering, National University of Singapore, Singapore 117576
| | - G. P. Rangaiah
- Department of Chemical & Biomolecular Engineering, National University of Singapore, Singapore 117576
| | - S. Lakshminarayanan
- Department of Chemical & Biomolecular Engineering, National University of Singapore, Singapore 117576
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Yelneedi S, Samavedham L, Rangaiah GP. Advanced Control Strategies for the Regulation of Hypnosis with Propofol. Ind Eng Chem Res 2009. [DOI: 10.1021/ie800695b] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Sreenivas Yelneedi
- Department of Chemical & Biomolecular Engineering, National University of Singapore, Singapore 117576
| | | | - G. P. Rangaiah
- Department of Chemical & Biomolecular Engineering, National University of Singapore, Singapore 117576
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Dua P, Kouramas K, Dua V, Pistikopoulos E. MPC on a chip—Recent advances on the application of multi-parametric model-based control. Comput Chem Eng 2008. [DOI: 10.1016/j.compchemeng.2007.03.008] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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