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.

scholarly journals A Prototype of a Portable Gas Analyzer for Exhaled Acetone Detection

2019 ◽  
Vol 9 (13) ◽  
pp. 2605 ◽  
Author(s):  
Jakub Sorocki ◽  
Artur Rydosz
Keyword(s):  
Sensor Array ◽  
Mechanical Design ◽  
Gas Analyzer ◽  
Computing Power ◽  
Non Invasive ◽  
Gas Sensor Array ◽  
3D Printed ◽  
Diabetes Monitoring ◽  
Acetone Detection ◽  
The Relationship

The paper presents the development of a portable gas analyzer prototype for exhaled acetone detection, employing an application-suited gas sensor array and 3D printing technology. The device provides the functionality to monitor exhaled acetone levels, which could be used as a potential tool for non-invasive diabetes monitoring. The relationship between exhaled acetone concentrations and glucose in blood is confirmed in the literature, including research carried out by the authors. The design process is presented including a general consideration for the sensor array construction, which is the core for sensing gases, as well as requirements for the measurement chamber it is to be placed in. Moreover, the mechanical design of the 3D-printed housing is discussed to ensure the ergonomics of use as a hand-held device while keeping the hardware integrity. Also, the processing hardware is discussed to provide sufficient computing power to handle the stand-alone operation while being energy efficient, enabling long battery-powered operation. Finally, calibration and measurement, as well as the analyzer operation, are shown, validating the proposed class of exhaled acetone-detection capable meters.

scholarly journals Salivary molecular spectroscopy: a rapid and non-invasive monitoring tool for diabetes mellitus during insulin treatment

2019 ◽  
Author(s):  
D.C. Caixeta ◽  
E. M. G. Aguiar ◽  
L. Cardoso-Sousa ◽  
L.M.D Coelho ◽  
S.W. Oliveira ◽  
...  
Keyword(s):  
Ftir Spectroscopy ◽  
Molecular Spectroscopy ◽  
Cost Effective ◽  
Green Technology ◽  
Vibrational Modes ◽  
Roc Curve Analysis ◽  
Monitoring Method ◽  
Non Invasive ◽  
Salivary Biomarkers ◽  
Diabetes Monitoring

AbstractMonitoring of blood glucose is an invasive, painful and costly practice in diabetes. Consequently, the search for a more cost-effective (reagent-free), non-invasive and specific diabetes monitoring method is of great interest. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy has been used in diagnosis of several diseases, however, applications in the monitoring of diabetic treatment are just beginning to emerge. Here, we used ATR-FTIR spectroscopy to evaluate saliva of non-diabetic (ND), diabetic (D) and diabetic 6U-treated of insulin (D6U) rats to identify potential salivary biomarkers related to glucose monitoring. The spectrum of saliva of ND, D and D6U rats displayed several unique vibrational modes and from these, two vibrational modes were pre-validated as potential diagnostic biomarkers by ROC curve analysis with significant correlation with glycemia. Compared to the ND and D6U rats, classification of D rats was achieved with a sensitivity of 100%, and an average specificity of 93.33% and 100% using bands 1452 cm−1 and 836 cm−1, respectively. Moreover, 1452 cm−1 and 836 cm−1 spectral bands proved to be robust spectral biomarkers and highly correlated with glycemia (R2 of 0.801 and 0.788, P < 0.01, respectively). Both PCA-LDA and HCA classifications achieved an accuracy of 95.2%. Spectral salivary biomarkers discovered using univariate and multivariate analysis may provide a novel robust alternative for diabetes monitoring using a non-invasive and green technology.

scholarly journals A Review of Biosensors for Non-Invasive Diabetes Monitoring and Screening in Human Exhaled Breath

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 5963-5974 ◽  
Author(s):  
Fahad Usman ◽  
J. O. Dennis ◽  
A. Y. Ahmed ◽  
Fabrice Meriaudeau ◽  
O. B. Ayodele ◽  
...  
Keyword(s):  
Exhaled Breath ◽  
Non Invasive ◽  
Diabetes Monitoring

X-ray microtomography

1988 ◽  
Vol 46 ◽  
pp. 998-999
Author(s):  
H.W. Deckman ◽  
B.F. Flannery ◽  
J.H. Dunsmuir ◽  
K.D' Amico
Keyword(s):  
Computed Tomography ◽  
Internal Structure ◽  
Imaging Technique ◽  
Three Dimensional ◽  
Tissue Structure ◽  
Individual Element ◽  
X Ray ◽  
Non Invasive ◽  
Panoramic Imaging ◽  
Three Dimensional Images

We have developed a new X-ray microscope which produces complete three dimensional images of samples. The microscope operates by performing X-ray tomography with unprecedented resolution. Tomography is a non-invasive imaging technique that creates maps of the internal structure of samples from measurement of the attenuation of penetrating radiation. As conventionally practiced in medical Computed Tomography (CT), radiologists produce maps of bone and tissue structure in several planar sections that reveal features with 1mm resolution and 1% contrast. Microtomography extends the capability of CT in several ways. First, the resolution which approaches one micron, is one thousand times higher than that of the medical CT. Second, our approach acquires and analyses the data in a panoramic imaging format that directly produces three-dimensional maps in a series of contiguous stacked planes. Typical maps available today consist of three hundred planar sections each containing 512x512 pixels. Finally, and perhaps of most import scientifically, microtomography using a synchrotron X-ray source, allows us to generate maps of individual element.

Non-invasive measurement of a fermentation pattern shift in infants during the first three months of life

2001 ◽  
Vol 120 (5) ◽  
pp. A266-A266
Author(s):  
R BUTLER ◽  
B ZACHARAKIS ◽  
D MOORE ◽  
K CRAWFORD ◽  
G DAVIDSON ◽  
...  
Keyword(s):  
Non Invasive ◽  
Fermentation Pattern ◽  
Invasive Measurement
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