Abstract

We reported measurement results relating to non-invasive glucose sensing using a novel multiwavelength approach that combines radio frequency and near infrared signals in transmission through aqueous glucose-loaded solutions. Data were collected simultaneously in the 37–39 GHz and 900–1800 nm electromagnetic bands. We successfully detected changes in the glucose solutions with varying glucose concentrations between 80 and 5000 mg/dl. The measurements showed for the first time that, compared to single modality systems, greater accuracy on glucose level prediction can be achieved when combining transmission data from these distinct electromagnetic bands, boosted by machine learning algorithms.

Highlights

  • While some minimally invasive sensing systems are rapidly gaining commercial traction [2,3], the vast majority of people living with diabetes still rely on painful, invasive methods to manage their condition, based on drawing blood or interstitial fluids to measure their blood glucose concentration

  • The antennas are placed in a custom-made 3D printed holder with the sample under test sandwiched between them (Figure 1) The antennas are driven by an MS46122B (Anritsu, Kanagawa, Japan) vector network analyzer (VNA) using a pair of Stability Plus cables (MauryMicrowave, Ontario, CA, USA)

  • The experimental measurements were performed on aqueous glucose solutions with concentrations ranging between 80 mg/dl and 5000 mg/dl

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Summary

Introduction

Invasive systems primarily rely on sampling the glucose in the interstitial fluid, either via implantable enzymatic sensors [4,5] or by attempting to transdermally extract the interstitial fluid with techniques such as inverse iontophoresis, ultrasound, and thermal activation [6,7,8]. These minimally invasive techniques could serve as a steppingstone until a fully non-invasive solution becomes clinically available, as long as issues such as accurate correlation with blood glucose and skin irritation are addressed

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