• DocumentCode
    574870
  • Title

    Challenges and progress in the development of a closed-loop artificial pancreas

  • Author

    Bequette, B. Wayne

  • Author_Institution
    Rensselaer Polytech. Inst., Troy, NY, USA
  • fYear
    2012
  • fDate
    27-29 June 2012
  • Firstpage
    4065
  • Lastpage
    4071
  • Abstract
    Pursuit of a closed-loop artificial pancreas that automatically controls the blood glucose of individuals with type 1 diabetes has intensified during the past six years. Here we discuss the progress and challenges in the major steps towards a closed-loop system. Continuous insulin infusion pumps have been widely available for over two decades, but “smart pump” technology has made the devices easier to use and more powerful. Continuous glucose monitoring (CGM) technology has improved and the devices are more widely available. A number of approaches are currently under study for fully closed-loop systems; most manipulate only insulin, while others manipulate insulin and glucagon. Algorithms include on-off (for prevention of overnight hypoglycemia), proportional-integral-derivative (PID), model predictive control (MPC) and fuzzy logic based learning control. Meals cause the major “disturbance” to blood glucose, and we focus on approaches that our group has developed to predict when a meal is likely to be consumed and its effect.
  • Keywords
    biochemistry; biomedical equipment; blood; closed loop systems; diseases; fuzzy control; learning systems; medical control systems; patient monitoring; predictive control; sugar; three-term control; CGM; MPC; PID control; automatically blood glucose control; closed loop artificial pancrea; continuous glucose monitoring; continuous insulin infusion pump; fuzzy logic; glucagon; learning control; model predictive control; proportional-integral-derivative; smart pump technology; type 1 diabetes; Blood; Diabetes; Insulin; Pancreas; Prediction algorithms; Sensors; Sugar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2012
  • Conference_Location
    Montreal, QC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4577-1095-7
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2012.6315593
  • Filename
    6315593