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Sensors 2017, 17(3), 532; doi:10.3390/s17030532

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

Department of Biomedical Engineering, Illinois Institute of Technology, 3255 S. Dearborn St., Chicago, IL 60616, USA
Department of Chemical and Biological Engineering, Illinois Institute of Technology, 10 W. 33rd St., Chicago, IL 60616, USA
College of Nursing, University of Illinois at Chicago, 845 S. Damen Ave., MC 802, Chicago, IL 60612, USA
Integrative Physiology Laboratory, University of Illinois at Chicago, 1640 W. Roosevelt Rd., Chicago, IL 60612, USA
Author to whom correspondence should be addressed.
Academic Editors: Giovanni Sparacino, Andrea Facchinetti and J. Hans DeVries
Received: 25 October 2016 / Revised: 2 March 2017 / Accepted: 3 March 2017 / Published: 7 March 2017
(This article belongs to the Special Issue Glucose Sensors: Revolution in Diabetes Management 2016)
View Full-Text   |   Download PDF [1657 KB, uploaded 8 March 2017]   |  


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. View Full-Text
Keywords: artificial pancreas; wearable sensors; biometric variables; exercise; type 1 diabetes; partial least squares artificial pancreas; wearable sensors; biometric variables; exercise; type 1 diabetes; partial least squares

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Turksoy, K.; Monforti, C.; Park, M.; Griffith, G.; Quinn, L.; Cinar, A. Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System. Sensors 2017, 17, 532.

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