scholarly journals Advances in Biosensors for Continuous Glucose Monitoring Towards Wearables

2021 ◽  
Vol 9 ◽  
Author(s):  
Lucy Johnston ◽  
Gonglei Wang ◽  
Kunhui Hu ◽  
Chungen Qian ◽  
Guozhen Liu
Keyword(s):  
Contact Lenses ◽  
Glucose Monitoring ◽  
Non Invasive ◽  
Bodily Fluids ◽  
Recent Developments ◽  
Low Glucose ◽  
Continuous Glucose Monitors ◽  
Diabetic Person ◽  
Glucose Biosensing ◽  
Blood Glucose Concentrations

Continuous glucose monitors (CGMs) for the non-invasive monitoring of diabetes are constantly being developed and improved. Although there are multiple biosensing platforms for monitoring glucose available on the market, there is still a strong need to enhance their precision, repeatability, wearability, and accessibility to end-users. Biosensing technologies are being increasingly explored that use different bodily fluids such as sweat and tear fluid, etc., that can be calibrated to and therefore used to measure blood glucose concentrations accurately. To improve the wearability of these devices, exploring different fluids as testing mediums is essential and opens the door to various implants and wearables that in turn have the potential to be less inhibiting to the wearer. Recent developments have surfaced in the form of contact lenses or mouthguards for instance. Challenges still present themselves in the form of sensitivity, especially at very high or low glucose concentrations, which is critical for a diabetic person to monitor. This review summarises advances in wearable glucose biosensors over the past 5 years, comparing the different types as well as the fluid they use to detect glucose, including the CGMs currently available on the market. Perspectives on the development of wearables for glucose biosensing are discussed.

scholarly journals Continuous Non-Invasive Glucose Monitoring via Contact Lenses: Current Approaches and Future Perspectives

Biosensors ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 189
Author(s):  
David Bamgboje ◽  
Iasonas Christoulakis ◽  
Ioannis Smanis ◽  
Gaurav Chavan ◽  
Rinkal Shah ◽  
...  
Keyword(s):  
Embedded System ◽  
Contact Lenses ◽  
Glucose Monitoring ◽  
Ease Of Use ◽  
Biofuel Cell ◽  
Glucose Measurement ◽  
Rf Power ◽  
Lacrimal Fluid ◽  
Non Invasive ◽  
Invasive Techniques

Diabetes mellitus (DM) is a chronic disease that must be carefully managed to prevent serious complications such as cardiovascular disease, retinopathy, nephropathy and neuropathy. Self-monitoring of blood glucose is a crucial tool for managing diabetes and, at present, all relevant procedures are invasive while they only provide periodic measurements. The pain and measurement intermittency associated with invasive techniques resulted in the exploration of painless, continuous, and non-invasive techniques of glucose measurement that would facilitate intensive management. The focus of this review paper is the existing solutions for continuous non-invasive glucose monitoring via contact lenses (CLs) and to carry out a detailed, qualitative, and comparative analysis to inform prospective researchers on viable pathways. Direct glucose monitoring via CLs is contingent on the detection of biomarkers present in the lacrimal fluid. In this review, emphasis is given on two types of sensors: a graphene-AgNW hybrid sensor and an amperometric sensor. Both sensors can detect the presence of glucose in the lacrimal fluid by using the enzyme, glucose oxidase. Additionally, this review covers fabrication procedures for CL biosensors. Ever since Google published the first glucose monitoring embedded system on a CL, CL biosensors have been considered state-of-the-art in the medical device research and development industry. The CL not only has to have a sensory system, it must also have an embedded integrated circuit (IC) for readout and wireless communication. Moreover, to retain mobility and ease of use of the CLs used for continuous glucose monitoring, the power supply to the solid-state IC on such CLs must be wireless. Currently, there are four methods of powering CLs: utilizing solar energy, via a biofuel cell, or by inductive or radiofrequency (RF) power. Although, there are many limitations associated with each method, the limitations common to all, are safety restrictions and CL size limitations. Bearing this in mind, RF power has received most of the attention in reported literature, whereas solar power has received the least attention in the literature. CLs seem a very promising target for cutting edge biotechnological applications of diagnostic, prognostic and therapeutic relevance.

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

2018 ◽  
Vol 10 (3) ◽  
pp. 10-29 ◽  
Author(s):  
George Shaker ◽  
Karly Smith ◽  
Ala Eldin Omer ◽  
Shuo Liu ◽  
Clement Csech ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Detection System ◽  
Diabetic Patients ◽  
Glucose Detection ◽  
60 Ghz ◽  
Non Invasive ◽  
Wave Radar ◽  
Recent Developments ◽  
Blood Glucose Concentrations ◽  
Different Levels

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.

scholarly journals Machine Learning and Radiomics Applications in Esophageal Cancers Using Non-Invasive Imaging Methods—A Critical Review of Literature

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2469
Author(s):  
Chen-Yi Xie ◽  
Chun-Lap Pang ◽  
Benjamin Chan ◽  
Emily Yuen-Yuen Wong ◽  
Qi Dou ◽  
...  
Keyword(s):  
Machine Learning ◽  
Quantitative Imaging ◽  
Risk Groups ◽  
Review Of Literature ◽  
Primary Tumors ◽  
Non Invasive ◽  
Significant Difference ◽  
Recent Developments ◽  
Health Significance ◽  
Imaging Markers

Esophageal cancer (EC) is of public health significance as one of the leading causes of cancer death worldwide. Accurate staging, treatment planning and prognostication in EC patients are of vital importance. Recent advances in machine learning (ML) techniques demonstrate their potential to provide novel quantitative imaging markers in medical imaging. Radiomics approaches that could quantify medical images into high-dimensional data have been shown to improve the imaging-based classification system in characterizing the heterogeneity of primary tumors and lymph nodes in EC patients. In this review, we aim to provide a comprehensive summary of the evidence of the most recent developments in ML application in imaging pertinent to EC patient care. According to the published results, ML models evaluating treatment response and lymph node metastasis achieve reliable predictions, ranging from acceptable to outstanding in their validation groups. Patients stratified by ML models in different risk groups have a significant or borderline significant difference in survival outcomes. Prospective large multi-center studies are suggested to improve the generalizability of ML techniques with standardized imaging protocols and harmonization between different centers.

scholarly journals Nanoparticles as Adjuvants and Nanodelivery Systems for mRNA-Based Vaccines

Pharmaceutics ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 45
Author(s):  
Iman M. Alfagih ◽  
Basmah Aldosari ◽  
Bushra AlQuadeib ◽  
Alanood Almurshedi ◽  
Mariyam M. Alfagih
Keyword(s):  
Messenger Rna ◽  
Immune Cell ◽  
Natural Infection ◽  
Immunological Response ◽  
Infection Process ◽  
Dual Function ◽  
Therapeutic Vaccines ◽  
Non Invasive ◽  
Recent Developments

Messenger RNA (mRNA)-based vaccines have shown promise against infectious diseases and several types of cancer in the last two decades. Their promise can be attributed to their safety profiles, high potency, and ability to be rapidly and affordably manufactured. Now, many RNA-based vaccines are being evaluated in clinical trials as prophylactic and therapeutic vaccines. However, until recently, their development has been limited by their instability and inefficient in vivo transfection. The nanodelivery system plays a dual function in RNA-based vaccination by acting as a carrier system and as an adjuvant. That is due to its similarity to microorganisms structurally and size-wise; the nanodelivery system can augment the response by the immune system via simulating the natural infection process. Nanodelivery systems allow non-invasive mucosal administration, targeted immune cell delivery, and controlled delivery, reducing the need for multiple administrations. They also allow co-encapsulating with immunostimulators to improve the overall adjuvant capacity. The aim of this review is to discuss the recent developments and applications of biodegradable nanodelivery systems that improve RNA-based vaccine delivery and enhance the immunological response against targeted diseases.

scholarly journals Enhanced Accuracy of Continuous Glucose Monitoring during Exercise through Physical Activity Tracking Integration

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3757 ◽  
Author(s):  
Alejandro José Laguna Sanz ◽  
José Luis Díez ◽  
Marga Giménez ◽  
Jorge Bondia
Keyword(s):  
Physical Activity ◽  
Estimation Error ◽  
Glucose Monitoring ◽  
Linear Regression Models ◽  
Activity Tracking ◽  
Metabolic Equivalent ◽  
Optimal Inputs ◽  
Input Model ◽  
Continuous Glucose Monitors ◽  
Monitoring Devices

Current Continuous Glucose Monitors (CGM) exhibit increased estimation error during periods of aerobic physical activity. The use of readily-available exercise monitoring devices opens new possibilities for accuracy enhancement during these periods. The viability of an array of physical activity signals provided by three different wearable devices was considered. Linear regression models were used in this work to evaluate the correction capabilities of each of the wearable signals and propose a model for CGM correction during exercise. A simple two-input model can reduce CGM error during physical activity (17.46% vs. 13.8%, p < 0.005) to the magnitude of the baseline error level (13.61%). The CGM error is not worsened in periods without physical activity. The signals identified as optimal inputs for the model are “Mets” (Metabolic Equivalent of Tasks) from the Fitbit Charge HR device, which is a normalized measurement of energy expenditure, and the skin temperature reading provided by the Microsoft Band 2 device. A simpler one-input model using only “Mets” is also viable for a more immediate implementation of this correction into market devices.

Non-invasive glucose monitoring using open electromagnetic waveguides

2012 ◽  
Author(s):  
M. Hofmann ◽  
M. Bloss ◽  
R. Weigel ◽  
G. Fischer ◽  
D. Kissinger
Keyword(s):  
Glucose Monitoring ◽  
Non Invasive
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