Non-Invasive Monitoring of Glucose Level Changes Utilizing a mm-Wave Radar System

George Shaker, Karly Smith, Ala Eldin Omer, Shuo Liu, Clement Csech, Udeshaya Wadhwa, Safieddin Safavi-Naeini and Richard Hughson
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George Shaker: Department of Mechanical and Mechatronics Engineering, Department of Electrical and Computer Engineering, University of Waterloo, Ontario, Canada & Research Institute for Aging, Waterloo, Ontario, Canada
Karly Smith: Department of Systems Design Engineering, University of Waterloo, Ontario, Canada
Ala Eldin Omer: Department of Electrical and Computer Engineering, University of Waterloo, Ontario, Canada
Shuo Liu: Department of Nanotechnology Engineering, University of Waterloo, Ontario, Canada
Clement Csech: Department of Biomechanics and Bioengineering, Universite de Technologie de Compiegne, Compiegne, France
Udeshaya Wadhwa: Department of Mechanical and Mechatronics Engineering, University of Waterloo, Ontario, Canada
Safieddin Safavi-Naeini: Department of Electrical and Computer Engineering, University of Waterloo, Ontario, Canada
Richard Hughson: Department of Applied Health Sciences, Faculty of Science, University of Waterloo, Ontario, Canada & Research Institute for Aging, Waterloo, Ontario, Canada

International Journal of Mobile Human Computer Interaction (IJMHCI), 2018, vol. 10, issue 3, 10-29

Abstract: This article discusses recent developments in the authors' experiments using Google's Soli alpha kit to develop a non-invasive blood glucose detection system. The Soli system (co-developed by Google and Infineon) is a 60 GHz mm-wave radar that promises a small, mobile, and wearable platform intended for gesture recognition. They have retrofitted the setup for the system and their experiments outline a proof-of-concept prototype to detect changes of the dielectric properties of solutions with different levels of glucose and distinguish between different concentrations. Preliminary results indicated that mm-waves are suitable for glucose detection among biological mediums at concentrations similar to blood glucose concentrations of diabetic patients. The authors discuss improving the repeatability and scalability of the system, other systems of glucose detection, and potential user constraints of implementation.

Date: 2018
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