We present an approach to enhance microwave brain imaging with an innovative metamaterial (MM) planar design based on a cross-shaped split-ring resonator (SRR-CS). The proposed metasurface is incorporated in different setups, and its interaction with EM waves is studied both experimentally and by using CST Microwave Studio^® and is compared to a “no MM” case scenario. We show that the MM can enhance the penetration of the transmitted signals into the human head when placed in contact with skin tissue, acting as an impedance-matching layer. In addition, we show that the MM can improve the transceivers’ ability to detect useful “weak” signals when incorporated in a headband scanner for brain imaging by increasing the signal difference from a blood-like dielectric target introduced into the brain volume. Our results suggest that the proposed MM film can be a powerful hardware advance towards the development of scanners for brain haemorrhage detection and monitoring.

The paper presents the first in vivo glucose monitoring animal study in a pig, which correlates radio frequency signal transmission changes with changes in blood glucose concentration in the 58–62 GHz frequency range. The presented non-invasive glucose sensing system consists of two opposite facing patch antennas sandwiching glucose-loaded samples. Prior to the animal study, the system was tested using saline solution samples, for which a linear relationship between changes in transmitted signal and glucose concentration was observed. In the animal study, glucose concentration changes were induced by injecting a known glucose solution in the blood stream. The non-invasive transmission measurements were compared to the glucose levels obtained invasively from the animal. Our results suggest that the system can detect spikes in glucose concentration in the blood, which is an important milestone towards non-invasive glucose monitoring.

This paper presents experimental results that demonstrate the correlation of glucose concentration in water and saline solutions with transmitted electromagnetic (EM) energy in the frequency range of 50–75 GHz. The system is based on placing the aqueous solutions in acrylic holding tanks sandwiched between two open V-band waveguides. The measured samples have clinically relevant range of glucose concentrations, as low as 0.025 wt%. Our measurements show for the first time that it is possible to establish an approximately linear relationship between the signals transmitted through this simple waveguide-based system and the glucose content in the samples. Accurate full-wave EM simulations confirm this linear correlation. The results suggest the possibility of developing a miniaturized non-invasive glucose sensing device based on the transmission of radio waves in this frequency range.

This paper presents reflection and transmission measurements in the 58 - 62 GHz frequency range through a pig's ear while the animal was subject to a blood glucose test. The paper first presents results of reflection measurements when patch antennas are placed at different locations around the ear and before any glucose injection is performed. Second, transmission measurements were taken for different frequencies as the blood glucose was changing over time, showing a good correlation between the recorded signals and the measured glucose levels. The motivation behind these measurements is to design a sensor that can achieve accurate detection of glucose concentration levels without drawing blood (non-invasively).

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.

Electromagnetic (EM) biomedical sensors in the mm-wave frequency range must detect small changes in signals in the presence of tissues, which are correlated to a pathological condition. These signals, however, can suffer from artifacts due to complex EM wave interactions such as diffraction and surface wave propagation, which are often overlooked in the design phase of these sensors. This paper studies the impact of these wave phenomena on the signals transmitted and received from a pair of antennas designed to sense glucose changes via changes in transmission through a sample. Numerical simulations and controlled experiments with glucose solutions demonstrate for the first time that unwanted signal contributions from mm surface waves along the tissue can dominate the received signals but can be reduced with the use of appropriately placed absorbers around the antenna sensors. As a result, the sensitivity of such a sensing system to glucose changes is increased. This finding can be very useful in the design and development of the glucose sensor under study, as well as for other EM-based diagnostic medical applications.