In Silico Investigation of SNR and Dermis Sensitivity for Optimum Dual-Channel Near-Infrared Glucose Sensor Designs for Different Skin Colors

A comprehensive review on electromagnetic wave based non-invasive glucose monitoring in microwave frequencies

Diabetes is a chronic disease that affects millions of humans worldwide. This review article provides an analysis of the recent advancements in non-invasive blood glucose monitoring, detailing methods and techniques, with a special focus on Electromagnetic wave microwave glucose sensors. While optical, thermal, and electromagnetic techniques have been discussed, the primary emphasis is focussed on microwave frequency sensors due to their distinct advantages. Microwave sensors exhibit rapid response times, require minimal user intervention, and hold potential for continuous monitoring, renders them extremely potential for real-world applications. Additionally, their reduced susceptibility to physiological interferences further enhances their appeal. This review critically assesses the performance of microwave glucose sensors by considering factors such as accuracy, sensitivity, specificity, and user comfort. Moreover, it sheds light on the challenges and upcoming directions in the growth of microwave sensors, including the need for reduction and integration with wearable platforms. By concentrating on microwave sensors within the broader context of non-invasive glucose monitoring, this article aims to offer significant enlightenment that may drive further innovation in diabetes care.

Exploring the impact and influence of melanin on frequency-domain near-infrared spectroscopy measurements

Significance

Near-infrared spectroscopy (NIRS) is a non-invasive optical method that measures changes in hemoglobin concentration and oxygenation. The measured light intensity is susceptible to reduced signal quality due to the presence of melanin.

Aim

We quantify the influence of melanin concentration on NIRS measurements taken with a frequency-domain near-infrared spectroscopy system using 690 and 830 nm.

Approach

Using a forehead NIRS probe, we measured 35 healthy participants and investigated the correlation between melanin concentration indices, which were determined using a colorimeter, and several key metrics from the NIRS signal. These metrics include signal-to-noise ratio (SNR), two measurements of oxygen saturation (arterial oxygen saturation,SpO 2 , and tissue oxygen saturation,StO 2 ), and optical properties represented by the absorption coefficient (μ a ) and the reduced scattering coefficient (μ s ' ).

Results

We found a significant negative correlation between the melanin index and the SNR estimated in oxy-hemoglobin signals (r s = - 0.489 , p = 0.006 ) andSpO 2 levels (r s = - 0.413 , p = 0.023 ). However, no significant changes were observed in the optical properties andStO 2 (r s = - 0.146 , p = 0.44 ).

Conclusions

We found that estimated SNR andSpO 2 values show a significant decline and dependence on the melanin index, whereasStO 2 and optical properties do not show any correlation with the melanin index.

Non-Invasive Glucose Sensing Technologies and Products: A Comprehensive Review for Researchers and Clinicians

Diabetes Mellitus incidence and its negative outcomes have dramatically increased worldwide and are expected to further increase in the future due to a combination of environmental and social factors. Several methods of measuring glucose concentration in various body compartments have been described in the literature over the years. Continuous advances in technology open the road to novel measuring methods and innovative measurement sites. The aim of this comprehensive review is to report all the methods and products for non-invasive glucose measurement described in the literature over the past five years that have been tested on both human subjects/samples and tissue models. A literature review was performed in the MDPI database, with 243 articles reviewed and 124 included in a narrative summary. Different comparisons of techniques focused on the mechanism of action, measurement site, and machine learning application, outlining the main advantages and disadvantages described/expected so far. This review represents a comprehensive guide for clinicians and industrial designers to sum the most recent results in non-invasive glucose sensing techniques' research and production to aid the progress in this promising field.

Estimation of the Differential Pathlength Factor for Human Skin Using Monte Carlo Simulations

Near-infrared technology is an emerging non-invasive technique utilized for various medical applications. Recently, there have been many attempts to utilize NIR technology for the continues monitoring of blood glucose levels through the skin. Different approaches and designs have been proposed for non-invasive blood glucose measurements. Light photons penetrating the skin can undergo multiple scattering events, and the actual optical pathlength becomes larger than the source-to-detector separation (optode spacing) in the reflection-mode configuration. Thus, the differential pathlength factor (DPF) must be incorporated into the modified Beer-Lambert law. The accurate estimation of the DPF values will lead to an accurate quantification of the physiological variations within the tissue. In this work, the aim was to systematically estimate the DPF for human skin for a range of source-to-detector separations and wavelengths. The Monte Carlo (MC) method was utilized to mimic the different layers of human skin with different optical properties and blood and water volume fractions. This work could help improve the accuracy of the near-infrared technique in the measurement of physiological variations within skin tissue.