Meal detection and meal size estimation for type 1 diabetes treatment: A variable state dimension approach

Jinyu Xie, Qian Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

To compensate the glucose variability caused by meals is essential in developing Artificial Pancreas for type 1 diabetes. Most existing algorithms rely on meal announcements and determine the insulin doses based on an Insulin-to-Carbohydrate ratio (I:C ratio). However, patients, especially young patients, often forget to provide meal information under natural living conditions. A Variable State Dimension (VSD) based algorithm is developed to detect meals which are unknown to the controller (unannounced meals). The algorithm is evaluated using an FDA-approved UVa/Padova simulator and has demonstrated to achieve 95% success rate in meal detection with less than 17% false alarm rate. In addition, the average meal size estimation error is no more than 13%. We then integrate the VSD-based meal detection and estimation algorithm with our previous published glucose dynamics model consisting of both insulin and carbohydrate inputs. The goodness of fit for 30min-ahead glucose predictions using meal information provided by the VSD-based algorithm has increased by 86% in average compared to the prediction using a model without meal input based on plasma blood glucose (BG) data. Simulation results also show that compared to several meal detection/estimation algorithms in the literature, the VSD-based algorithm has comparable or shorter detection time.

Original languageEnglish (US)
Title of host publicationAdaptive and Intelligent Systems Control; Advances in Control Design Methods; Advances in Non-Linear and Optimal Control; Advances in Robotics; Advances in Wind Energy Systems; Aerospace Applications; Aerospace Power Optimization; Assistive Robotics; Automotive 2
Subtitle of host publicationHybrid Electric Vehicles; Automotive 3: Internal Combustion Engines; Automotive Engine Control; Battery Management; Bio Engineering Applications; Biomed and Neural Systems; Connected Vehicles; Control of Robotic Systems
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791857243
DOIs
StatePublished - Jan 1 2015
EventASME 2015 Dynamic Systems and Control Conference, DSCC 2015 - Columbus, United States
Duration: Oct 28 2015Oct 30 2015

Publication series

NameASME 2015 Dynamic Systems and Control Conference, DSCC 2015
Volume1

Other

OtherASME 2015 Dynamic Systems and Control Conference, DSCC 2015
Country/TerritoryUnited States
CityColumbus
Period10/28/1510/30/15

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Mechanical Engineering
  • Control and Systems Engineering

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