Change search
Refine search result
1 - 10 of 10
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1. Abu-Rmileh, Amjad
    et al.
    Garcia-Gabin, Winston
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Detection and Prevention of Hypoglycemia in Automated Insulin Delivery Systems for Type 1 Diabetes Patients2012In: Advances in Medicine and Biology / [ed] Leon V. Berhardt, Nova Science Publishers, Inc., 2012, p. 249-266Chapter in book (Refereed)
  • 2. Abu-Rmileh, Amjad
    et al.
    Garcia-Gabin, Winston
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hypoglycemia prevention in closed-loop artificial pancreas for patients with type 1 diabetes2011In: Diabetes: Damages and treatments / [ed] Everlon Cid Rigobelo, IN-TECH, 2011, p. 207-226Chapter in book (Refereed)
  • 3.
    Abu-Rmileh, Amjad
    et al.
    Universidad de Gerona.
    Garcia-Gabin, Winston
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Smith Predictor Sliding Mode Closed-loop Glucose Controller in Type 1 Diabetes2011In: Proceedings of the 18th IFAC World Congress, 2011, 2011Conference paper (Refereed)
    Abstract [en]

    Type 1 diabetic patients depend on external insulin delivery to keep their blood glucose within near-normal ranges. In this work, two robust closed-loop controllers for blood glucose control are developed to prevent the life-threatening hypoglycemia, as well as to avoid extended hyperglycemia. The proposed controllers are designed by using the sliding mode control technique in a Smith predictor structure. To improve meal disturbance rejection, a simple feedforward controller is added to inject meal-time insulin bolus. Simulation studies were used to test the controllers, and shown the controllers ability to regulate the blood glucose within the safe limits in the presence of errors in measurements, modeling, and meal estimation.

  • 4. Abu-Rmileh, Amjad
    et al.
    Garcia-Gabin, Winston
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Wiener sliding-mode control for artificial pancreas: A new nonlinear approach to glucose regulation2012In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, ISSN 0169-2607, Vol. 107, no 2, p. 327-340Article in journal (Refereed)
    Abstract [en]

    Type 1 diabetic patients need insulin therapy to keep their blood glucose close to normal. In this paper an attempt is made to show how nonlinear control-oriented model may be used to improve the performance of closed-loop control of blood glucose in diabetic patients. The nonlinear Wiener model is used as a novel modeling approach to be applied to the glucose control problem. The identified Wiener model is used in the design of a robust nonlinear sliding mode control strategy. Two configurations of the nonlinear controller are tested and compared to a controller designed with a linear model. The controllers are designed in a Smith predictor structure to reduce the effect of system time delay. To improve the meal compensation features, the controllers are provided with a simple feedforward controller to inject an insulin bolus at meal time. Different simulation scenarios have been used to evaluate the proposed controllers. The obtained results show that the new approach out-performs the linear control scheme, and regulates the glucose level within safe limits in the presence of measurement and modeling errors, meal uncertainty and patient variations.

  • 5.
    Garcia-Gabin, Winston
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Multivariate Statistical Analysis Approaches for Detection of Insulin Infusion Set Failures2013Report (Other academic)
  • 6.
    Garcia-Gabin, Winston
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Jacobsen, Elling W.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Combining high-level glucose models with intracellular insulin signaling models for improved glucose controlIn: Journal of Diabetes Science and Technology, E-ISSN 1932-2968Article in journal (Refereed)
  • 7.
    Garcia-Gabin, Winston
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Jacobsen, Elling W.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Multilevel model based glucose control for type-1 diabetes patients2013In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013, p. 3917-3920Conference paper (Refereed)
    Abstract [en]

    Diabetes is a disease that involves alterationsat multiple biological levels, ranging from intracellular sig-nalling to organ processes. Since glucose homeostasis is theconsequence of complex interactions that involve a numberof factors, the control of diabetes should be based on amultilevel analysis. In this paper, a novel approach to designof closed-loop glucose controllers based on multilevel models ispresented. A control scheme is proposed based on combininga pharmacokinetic/pharmacodynamic model with an insulinsignal transduction model for type 1 diabetes mellitus patients.Based on this, an insulin feedback control schemes is designed.Two main advantages of explicitly utilizing information at theintracellular level were obtained. First, significant reductionof hypoglycaemic risk by reducing the undershoot in glucoselevels in response to added insulin. Second, robust performancefor inter-patient changes, demonstrated through application ofthe multilevel control strategy to a well establishedin silicopopulation of diabetic patients.

  • 8.
    Garcia-Gabin, Winston
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Jacobsen, Elling W.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Multilevel Model of Type 1 Diabetes Mellitus Patients for Model-Based Glucose Controllers2013In: Journal of Diabetes Science and Technology, E-ISSN 1932-2968, Vol. 7, no 1, p. 193-205Article in journal (Refereed)
    Abstract [en]

    Glucose homeostasis is the result of complex interactions across different biological levels. This multilevel characteristic should be considered when analyzing and designing closed-loop glucose control algorithms. Classic control schemes use only a pharmacokinetic-pharmacodynamic (PKPD) perspective to describe the gluco-regulatory system. A multilevel model combining a PKPD model with an insulin signaling model is proposed for patients with type 1 diabetes mellitus T1DM (T1DM). The PKPD Dalla Man model for T1DM is expanded to include an intracellular level involving insulin signaling to control glucose uptake through glucose transporter type 4 (GLUT4) translocation. A model-based controller is then designed and used as an example to illustrate the feasibility of the proposal. Two significant results were obtained for the controller explicitly utilizing multilevel information. No hypo-glycemic events were registered and an excellent performance for interpatient variability was achieved. Controller performance was evaluated using two indexes. The glucose was kept inside the range (70-180) mg/dl more than 99% of the time, and the intrapatient variability measured using control variability grid analysis was solid with 90% of the population inside the target zone. Multilevel models open new possibilities for designing glucose control algorithms. They allow controllers to take into account variables that have a strong influence on glucose homeostasis. A model-based controller was used for demonstrating how improved knowledge of the multilevel nature of diabetes increases the robustness and performance of glucose control algorithms. Using the proposed multi-level approach, a reduction of the hypoglycemic risk and robust behaviour for intrapatient variability was demonstrated.

  • 9.
    Rojas, Ruben
    et al.
    Electrical Engineering Department, Universidad de Los.
    Garcia-Gabin, Winston
    KTH, School of Electrical Engineering (EES), Automatic Control.
    B. Wayne B., Bequette
    Chemical and Biological Engineering Department, Rensselaer Polytechnic.
    Multivariate Statistical Analysis to Detect Insulin Infusion Set Failure2011In: 2011 American Control Conference, ACC 2011, San Francisco, CA, USA, 2011, p. 1952-1957Conference paper (Refereed)
    Abstract [en]

    Multivariate statistical analysis techniques are applied to insulin infusion set failure detection (IISF), a challenging problem faced by individuals with type 1 diabetes that are on continuous insulin infusion pump therapy. Bivariate classification (BC), principal component analysis (PCA), and a combined approach were applied to simulated glucose concentrations for 10 patients, based on a nonlinear physiological model of insulin and glucose dynamics. The PCA algorithm had fewer false alarms than BC, while detecting most drifting (ramp) infusion set failures before complete failure occurred.

  • 10.
    Rojas, Ruben
    et al.
    Electrical Engineering Department, Universidad de Los Andes.
    Garcia-Gabin, Winston
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Bequette, B. Wayne
    Chemical and Biological Engineering Department, Rensselaer Polytechnic.
    Mean Glucose Slope,  Principal Component Analysis Classification to Detect Insulin Infusion Set Failure2011In: 18th IFAC World Congress, Milan, Italy, 2011Conference paper (Refereed)
    Abstract [en]

    The bivariate classification technique using the mean glucose slope (MGS) and the first component of the principal component analysis (PCA), is applied to insulin infusion set failure detection (IISF), a challenging problem faced by individuals with type 1 diabetes that are on continuous insulin infusion pump therapy. The objective of this study was to determine if the proposed approach could be used to distinguish between normal patient data and data from patients under IISF online, in a reasonably short period of time. The proposed approach was applied to simulated glucose concentrations for 10 patients, based on a nonlinear physiological model of insulin and glucose dynamics. Although it presents few false alarms, it was capable of detecting most drifting (ramp) infusion set failures before complete failure occurred.

1 - 10 of 10
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf