Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System

An artificial pancreas (AP) computes the optimal insulin dose to be infused through an insulin pump in people with Type 1 Diabetes (T1D) based on information received from a continuous glucose monitoring (CGM) sensor. It has been recognized that exercise is a major challenge in the development of an...

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Main Authors: Kamuran Turksoy, Colleen Monforti, Minsun Park, Garett Griffith, Laurie Quinn, Ali Cinar
Format: Article
Language:English
Published: MDPI AG 2017-03-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/17/3/532
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author Kamuran Turksoy
Colleen Monforti
Minsun Park
Garett Griffith
Laurie Quinn
Ali Cinar
author_facet Kamuran Turksoy
Colleen Monforti
Minsun Park
Garett Griffith
Laurie Quinn
Ali Cinar
author_sort Kamuran Turksoy
collection DOAJ
description An artificial pancreas (AP) computes the optimal insulin dose to be infused through an insulin pump in people with Type 1 Diabetes (T1D) based on information received from a continuous glucose monitoring (CGM) sensor. It has been recognized that exercise is a major challenge in the development of an AP system. The use of biometric physiological variables in an AP system may be beneficial for prevention of exercise-induced challenges and better glucose regulation. The goal of the present study is to find a correlation between biometric variables such as heart rate (HR), heat flux (HF), skin temperature (ST), near-body temperature (NBT), galvanic skin response (GSR), and energy expenditure (EE), 2D acceleration-mean of absolute difference (MAD) and changes in glucose concentrations during exercise via partial least squares (PLS) regression and variable importance in projection (VIP) in order to determine which variables would be most useful to include in a future artificial pancreas. PLS and VIP analyses were performed on data sets that included seven different types of exercises. Data were collected from 26 clinical experiments. Clinical results indicate ST to be the most consistently important (important for six out of seven tested exercises) variable over all different exercises tested. EE and HR are also found to be important variables over several types of exercise. We also found that the importance of GSR and NBT observed in our experiments might be related to stress and the effect of changes in environmental temperature on glucose concentrations. The use of the biometric measurements in an AP system may provide better control of glucose concentration.
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spelling doaj.art-dcf4bc0007214b06844a13335f4a1c0c2022-12-22T04:01:18ZengMDPI AGSensors1424-82202017-03-0117353210.3390/s17030532s17030532Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas SystemKamuran Turksoy0Colleen Monforti1Minsun Park2Garett Griffith3Laurie Quinn4Ali Cinar5Department of Biomedical Engineering, Illinois Institute of Technology, 3255 S. Dearborn St., Chicago, IL 60616, USADepartment of Chemical and Biological Engineering, Illinois Institute of Technology, 10 W. 33rd St., Chicago, IL 60616, USACollege of Nursing, University of Illinois at Chicago, 845 S. Damen Ave., MC 802, Chicago, IL 60612, USAIntegrative Physiology Laboratory, University of Illinois at Chicago, 1640 W. Roosevelt Rd., Chicago, IL 60612, USACollege of Nursing, University of Illinois at Chicago, 845 S. Damen Ave., MC 802, Chicago, IL 60612, USADepartment of Biomedical Engineering, Illinois Institute of Technology, 3255 S. Dearborn St., Chicago, IL 60616, USAAn artificial pancreas (AP) computes the optimal insulin dose to be infused through an insulin pump in people with Type 1 Diabetes (T1D) based on information received from a continuous glucose monitoring (CGM) sensor. It has been recognized that exercise is a major challenge in the development of an AP system. The use of biometric physiological variables in an AP system may be beneficial for prevention of exercise-induced challenges and better glucose regulation. The goal of the present study is to find a correlation between biometric variables such as heart rate (HR), heat flux (HF), skin temperature (ST), near-body temperature (NBT), galvanic skin response (GSR), and energy expenditure (EE), 2D acceleration-mean of absolute difference (MAD) and changes in glucose concentrations during exercise via partial least squares (PLS) regression and variable importance in projection (VIP) in order to determine which variables would be most useful to include in a future artificial pancreas. PLS and VIP analyses were performed on data sets that included seven different types of exercises. Data were collected from 26 clinical experiments. Clinical results indicate ST to be the most consistently important (important for six out of seven tested exercises) variable over all different exercises tested. EE and HR are also found to be important variables over several types of exercise. We also found that the importance of GSR and NBT observed in our experiments might be related to stress and the effect of changes in environmental temperature on glucose concentrations. The use of the biometric measurements in an AP system may provide better control of glucose concentration.http://www.mdpi.com/1424-8220/17/3/532artificial pancreaswearable sensorsbiometric variablesexercisetype 1 diabetespartial least squares
spellingShingle Kamuran Turksoy
Colleen Monforti
Minsun Park
Garett Griffith
Laurie Quinn
Ali Cinar
Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System
Sensors
artificial pancreas
wearable sensors
biometric variables
exercise
type 1 diabetes
partial least squares
title Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System
title_full Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System
title_fullStr Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System
title_full_unstemmed Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System
title_short Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System
title_sort use of wearable sensors and biometric variables in an artificial pancreas system
topic artificial pancreas
wearable sensors
biometric variables
exercise
type 1 diabetes
partial least squares
url http://www.mdpi.com/1424-8220/17/3/532
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