Ultrasound-modulated optical glucose sensing using a 1645 nm laser

Noninvasive Glucose Sensing In Vivo

Blood glucose monitoring is an essential aspect of disease management for individuals with diabetes. Unfortunately, traditional methods require collecting a blood sample and thus are invasive and inconvenient. Recent developments in minimally invasive continuous glucose monitors have provided a more convenient alternative for people with diabetes to track their glucose levels 24/7. Despite this progress, many challenges remain to establish a noninvasive monitoring technique that works accurately and reliably in the wild. This review encompasses the current advancements in noninvasive glucose sensing technology in vivo, delves into the common challenges faced by these systems, and offers an insightful outlook on existing and future solutions.

Switchable preamplifier for dual modal photoacoustic and ultrasound imaging

Photoacoustic (PA) imaging is a high-fidelity biomedical imaging technique based on the principle of molecular-specific optical absorption of biological tissue constitute. Because PA imaging shares the same basic principle as that of ultrasound (US) imaging, the use of PA/US dual-modal imaging can be achieved using a single system. However, because PA imaging is limited to a shallower depth than US imaging due to the optical extinction in biological tissue, the PA signal yields a lower signal-to-noise ratio (SNR) than US images. To selectively amplify the PA signal, we propose a switchable preamplifier for acoustic-resolution PA microscopy implemented on an application-specific integrated circuit. Using the preamplifier, we measured the increments in the SNR with both carbon lead and wire phantoms. Furthermore, in vivo whole-body PA/US imaging of a mouse with a preamplifier showed enhancement of SNR in deep tissues, unveiling deeply located organs and vascular networks. By selectively amplifying the PA signal range to a level similar to that of the US signal without contrast agent administration, our switchable amplifier strengthens the mutual complement between PA/US imaging. PA/US imaging is impending toward clinical translation, and we anticipate that this study will help mitigate the imbalance of image depth between the two imaging modalities.

Non-Invasive Blood Glucose Estimation System Based on a Neural Network with Dual-Wavelength Photoplethysmography and Bioelectrical Impedance Measuring

This study proposed a noninvasive blood glucose estimation system based on dual-wavelength photoplethysmography (PPG) and bioelectrical impedance measuring technology that can avoid the discomfort created by conventional invasive blood glucose measurement methods while accurately estimating blood glucose. The measured PPG signals are converted into mean, variance, skewness, kurtosis, standard deviation, and information entropy. The data obtained by bioelectrical impedance measuring consist of the real part, imaginary part, phase, and amplitude size of 11 types of frequencies, which are converted into features through principal component analyses. After combining the input of seven physiological features, the blood glucose value is finally obtained as the input of the back-propagation neural network (BPNN). To confirm the robustness of the system operation, this study collected data from 40 volunteers and established a database. From the experimental results, the system has a mean squared error of 40.736, a root mean squared error of 6.3824, a mean absolute error of 5.0896, a mean absolute relative difference of 4.4321%, and a coefficient of determination (R Squared, R²) of 0.997, all of which fall within the clinically accurate region A in the Clarke error grid analyses.