scholarly journals Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities

Biosensors ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 476
Author(s):  
Kaushiki Dixit ◽  
Somayeh Fardindoost ◽  
Adithya Ravishankara ◽  
Nishat Tasnim ◽  
Mina Hoorfar
Keyword(s):  
Blood Glucose ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Breath Analysis ◽  
Blood Glucose Monitoring ◽  
Diabetes Diagnosis ◽  
Exhaled Breath ◽  
Non Invasive ◽  
Exhaled Breath Analysis ◽  
Diabetes Monitoring

With the global population prevalence of diabetes surpassing 463 million cases in 2019 and diabetes leading to millions of deaths each year, there is a critical need for feasible, rapid, and non-invasive methodologies for continuous blood glucose monitoring in contrast to the current procedures that are either invasive, complicated, or expensive. Breath analysis is a viable methodology for non-invasive diabetes management owing to its potential for multiple disease diagnoses, the nominal requirement of sample processing, and immense sample accessibility; however, the development of functional commercial sensors is challenging due to the low concentration of volatile organic compounds (VOCs) present in exhaled breath and the confounding factors influencing the exhaled breath profile. Given the complexity of the topic and the skyrocketing spread of diabetes, a multifarious review of exhaled breath analysis for diabetes monitoring is essential to track the technological progress in the field and comprehend the obstacles in developing a breath analysis-based diabetes management system. In this review, we consolidate the relevance of exhaled breath analysis through a critical assessment of current technologies and recent advancements in sensing methods to address the shortcomings associated with blood glucose monitoring. We provide a detailed assessment of the intricacies involved in the development of non-invasive diabetes monitoring devices. In addition, we spotlight the need to consider breath biomarker clusters as opposed to standalone biomarkers for the clinical applicability of exhaled breath monitoring. We present potential VOC clusters suitable for diabetes management and highlight the recent buildout of breath sensing methodologies, focusing on novel sensing materials and transduction mechanisms. Finally, we portray a multifaceted comparison of exhaled breath analysis for diabetes monitoring and highlight remaining challenges on the path to realizing breath analysis as a non-invasive healthcare approach.

Indole as a new tentative marker in exhaled breath for non-invasive blood glucose monitoring of diabetic subjects

2021 ◽  
Author(s):  
Herbert Fink ◽  
Tim Maihöfer ◽  
Jeffrey Bender ◽  
Jochen Schulat
Keyword(s):  
Blood Glucose ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Blood Glucose Monitoring ◽  
Glucose Measurement ◽  
Diabetic Patients ◽  
Exhaled Breath ◽  
Invasive Approach ◽  
Test Strips ◽  
Non Invasive

Abstract Blood glucose monitoring (BGM) is the most important part of diabetes management. In classical BGM, glucose measurement by test strips involves invasive finger pricking. We present results of a clinical study that focused on a non-invasive approach based on volatile organic compounds (VOCs) in exhaled breath. Main objective was the discovery of markers for prediction of blood glucose levels (BGL) in diabetic patients. Exhaled breath was measured repeatedly in 60 diabetic patients (30 type 1, 30 type 2) in fasting state and after a standardized meal. Proton Transfer Reaction Time of Flight Mass Spectrometry (PTR-ToF-MS) was used to sample breath every 15 minutes for a total of six hours. BGLs were tested in parallel via BGM test strips. VOC signals were plotted against glucose trends for each subject to identify correlations. Exhaled indole (a bacterial metabolite of tryptophan) showed significant mean correlation to BGL (with negative trend) and significant individual correlation in 36 patients. The type of diabetes did not affect this result. Additional experiments of one healthy male subject by ingestion of lactulose and 13C-labeled glucose (n=3) revealed that exhaled indole does not directly originate from food digestion by intestinal microbiota. As indole has been linked to human glucose metabolism, it might be a tentative marker in breath for non-invasive BGM. Clinical studies with greater diversity are required for confirmation of such results and further investigation of metabolic pathways.

Non-Invasive Blood Glucose Monitoring by Means of near Infrared Spectroscopy: Methods for Improving the Reliability of the Calibration Models

1997 ◽  
Vol 20 (5) ◽  
pp. 285-290 ◽  
Author(s):  
U.A. Müller ◽  
B. Mertes ◽  
C. Fischbacher ◽  
K.U. Jageman ◽  
K. Danzer
Keyword(s):  
Blood Glucose ◽  
Near Infrared ◽  
Glucose Monitoring ◽  
Blood Glucose Monitoring ◽  
Least Squares Regression ◽  
Non Invasive ◽  
Infrared Reflection ◽  
Calibration Models ◽  
Infrared Reflection Spectroscopy

The feasibility of using near infrared reflection spectroscopy for non-invasive blood glucose monitoring is discussed. Spectra were obtained using a diode-array spectrometer with a fiberoptic measuring head with a wavelength ranging from 800 nm to 1350 nm. Calibration was performed using partial least-squares regression and radial basis function networks. The results of different methods used to evaluate the quality of the recorded spectra in order to improve the reliability of the calibration models, are presented.

scholarly journals A Review of Non-Invasive Optical Systems for Continuous Blood Glucose Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6820
Author(s):  
Bushra Alsunaidi ◽  
Murad Althobaiti ◽  
Mahbubunnabi Tamal ◽  
Waleed Albaker ◽  
Ibraheem Al-Naib
Keyword(s):  
Blood Glucose ◽  
Glucose Monitoring ◽  
Daily Basis ◽  
Glucose Sensing ◽  
Blood Glucose Monitoring ◽  
Optical Systems ◽  
Glucose Levels ◽  
Non Invasive ◽  
Blood Glucose Levels ◽  
Continuous Blood Glucose Monitoring

The prevalence of diabetes is increasing globally. More than 690 million cases of diabetes are expected worldwide by 2045. Continuous blood glucose monitoring is essential to control the disease and avoid long-term complications. Diabetics suffer on a daily basis with the traditional glucose monitors currently in use, which are invasive, painful, and cost-intensive. Therefore, the demand for non-invasive, painless, economical, and reliable approaches to monitor glucose levels is increasing. Since the last decades, many glucose sensing technologies have been developed. Researchers and scientists have been working on the enhancement of these technologies to achieve better results. This paper provides an updated review of some of the pioneering non-invasive optical techniques for monitoring blood glucose levels that have been proposed in the last six years, including a summary of state-of-the-art error analysis and validation techniques.

Evaluation of a Continuous Blood Glucose Monitor: A Novel and Non-Invasive Wearable Using Bioimpedance Technology

2021 ◽  
pp. 193229682110541
Author(s):  
Farid Sanai ◽  
Arshman S. Sahid ◽  
Jacqueline Huvanandana ◽  
Sandra Spoa ◽  
Lachlan H. Boyle ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Blood Glucose ◽  
Real World ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Self Monitoring ◽  
Non Invasive ◽  
Adult Participants ◽  
Blood Glucose Monitor

Background: Frequent blood glucose level (BGL) monitoring is essential for effective diabetes management. Poor compliance is common due to the painful finger pricking or subcutaneous lancet implantation required from existing technologies. There are currently no commercially available non-invasive devices that can effectively measure BGL. In this real-world study, a prototype non-invasive continuous glucose monitoring system (NI-CGM) developed as a wearable ring was used to collect bioimpedance data. The aim was to develop a mathematical model that could use these bioimpedance data to estimate BGL in real time. Methods: The prototype NI-CGM was worn by 14 adult participants with type 2 diabetes for 14 days in an observational clinical study. Bioimpedance data were collected alongside paired BGL measurements taken with a Food and Drug Administration (FDA)-approved self-monitoring blood glucose (SMBG) meter and an FDA-approved CGM. The SMBG meter data were used to improve CGM accuracy, and CGM data to develop the mathematical model. Results: A gradient boosted model was developed using a randomized 80-20 training-test split of data. The estimated BGL from the model had a Mean Absolute Relative Difference (MARD) of 17.9%, with the Parkes error grid (PEG) analysis showing 99% of values in clinically acceptable zones A and B. Conclusions: This study demonstrated the reliability of the prototype NI-CGM at collecting bioimpedance data in a real-world scenario. These data were used to train a model that could successfully estimate BGL with a promising MARD and clinically relevant PEG result. These results will enable continued development of the prototype NI-CGM as a wearable ring.

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