Breath as the Mirror of Our body, is the Answer Really Blowing in the Wind? Recent Technologies in Exhaled Breath Analysis Systems as Non-invasive Sensing Platforms

2021 ◽  
pp. 116329
Author(s):  
Tutku Beduk ◽  
Ceren Durmus ◽  
Simge Balaban Hanoglu ◽  
Duygu Beduk ◽  
Khaled Nabil Salama ◽  
...  
Keyword(s):  
Breath Analysis ◽  
Exhaled Breath ◽  
Non Invasive ◽  
Sensing Platforms ◽  
Exhaled Breath Analysis

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 Ruling out SARS-CoV-2 infection using exhaled breath analysis by electronic nose in a public health setting

2021 ◽  
Author(s):  
Rianne de Vries ◽  
René M. Vigeveno ◽  
Simone Mulder ◽  
Niloufar Farzan ◽  
Demi R. Vintges ◽  
...  
Keyword(s):  
Public Health ◽  
Electronic Nose ◽  
Breath Analysis ◽  
Test Facility ◽  
Exhaled Breath ◽  
Non Invasive ◽  
Flight Mass Spectrometry ◽  
Exhaled Breath Analysis ◽  
Invasive Method ◽  
Rule Out

AbstractBackgroundRapid and accurate detection of SARS-CoV-2 infected individuals is crucial for taking timely measures and minimizing the risk of further SARS-CoV-2 spread. We aimed to assess the accuracy of exhaled breath analysis by electronic nose (eNose) for the discrimination between individuals with and without a SARS-CoV-2 infection.MethodsThis was a prospective real-world study of individuals presenting to public test facility for SARS-CoV-2 detection by molecular amplification tests (TMA or RT-PCR). After sampling of a combined throat/nasopharyngeal swab, breath profiles were obtained using a cloud-connected eNose. Data-analysis involved advanced signal processing and statistics based on independent t-tests followed by linear discriminant and ROC analysis. Data from the training set were tested in a validation, a replication and an asymptomatic set.FindingsFor the analysis 4510 individuals were available. In the training set (35 individuals with; 869 without SARS-CoV-2), the eNose sensors were combined into a composite biomarker with a ROC-AUC of 0.947 (CI:0.928-0.967). These results were confirmed in the validation set (0.957; CI:0.942-0.971, n=904) and externally validated in the replication set (0.937; CI:0.926-0.947, n=1948) and the asymptomatic set (0.909; CI:0.879-0.938, n=754). Selecting a cut-off value of 0.30 in the training set resulted in a sensitivity/specificity of 100/78, >99/84, 98/82% in the validation, replication and asymptomatic set, respectively.InterpretationeNose represents a quick and non-invasive method to reliably rule out SARS-CoV-2 infection in public health test facilities and can be used as a screening test to define who needs an additional confirmation test.FundingMinistry of Health, Welfare and SportResearch in contextEvidence before this studyElectronic nose technology is an emerging diagnostic tool for diagnosis and phenotyping of a wide variety of diseases, including inflammatory respiratory diseases, lung cancer, and infections.As of Feb 13, 2021, our search of PubMed using keywords “COVID-19” OR “SARS-CoV-2” AND “eNose” OR “electronic nose” OR “exhaled breath analysis” yielded 4 articles (1-4) that have assessed test characteristics of electronic nose to diagnose COVID-19. In these small studies the obtained signals using sensor-based technologies, two-dimensional gas chromatography and time-of-flight mass spectrometry, or proton transfer reaction time-of-flight mass spectrometry, provided adequate discrimination between patients with and without COVID-19.Added value of this studyWe prospectively studied the accuracy of exhaled breath analysis by electronic nose (eNose) to diagnose or rule out a SARS-CoV-2 infection in individuals with and without symptoms presenting to a public test facility. In the training set with 904 individuals, the eNose sensors were combined into a composite biomarker with a ROC-AUC of 0.948. In three independent validation cohorts of 3606 individuals in total, eNose was able to reliably rule out SARS-CoV-2 infection in 70-75% of individuals, with a sensitivity ranging between 98-100%, and a specificity between 78-84%. No association was found between cycle thresholds values, as semi-quantitative measure of viral load, and eNose variables.Implications of all the available evidenceThe available findings, including those from our study, support the use of eNose technology to distinguish between individuals with and without a SARS-CoV-2 infection with high accuracy. Exhaled breath analysis by eNose represents a quick and non-invasive method to reliably rule out a SARS-CoV-2 infection in public health test facilities. The results can be made available within seconds and can therefore be used as screening instrument. The eNose can reliably rule out a SARS-CoV-2 infection, eliminating the need for additional time-consuming, stressful, and expensive diagnostic tests in the majority of individuals.

Non-invasive prediction of lung cancer histological types through exhaled breath analysis by UV-irradiated electronic nose and GC/QTOF/MS

2020 ◽  
Vol 311 ◽  
pp. 127932 ◽  
Author(s):  
Tarik Saidi ◽  
Mohammed Moufid ◽  
Kelvin de Jesus Beleño-Saenz ◽  
Tesfalem Geremariam Welearegay ◽  
Nezha El Bari ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Electronic Nose ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Histological Types ◽  
Non Invasive ◽  
Exhaled Breath Analysis

scholarly journals Modular Breath Analyzer (MBA): Introduction of a Breath Analyzer Platform Based on an Innovative and Unique, Modular eNose Concept for Breath Diagnostics and Utilization of Calibration Transfer Methods in Breath Analysis Studies

Molecules ◽  
2021 ◽  
Vol 26 (12) ◽  
pp. 3776
Author(s):  
Carsten Jaeschke ◽  
Marta Padilla ◽  
Johannes Glöckler ◽  
Inese Polaka ◽  
Martins Leja ◽  
...  
Keyword(s):  
Real Life ◽  
Sensor Arrays ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Calibration Transfer ◽  
Early Disease Detection ◽  
Exhaled Breath Analysis ◽  
Breath Analyzer ◽  
Analysis Experiment ◽  
Before And After

Exhaled breath analysis for early disease detection may provide a convenient method for painless and non-invasive diagnosis. In this work, a novel, compact and easy-to-use breath analyzer platform with a modular sensing chamber and direct breath sampling unit is presented. The developed analyzer system comprises a compact, low volume, temperature-controlled sensing chamber in three modules that can host any type of resistive gas sensor arrays. Furthermore, in this study three modular breath analyzers are explicitly tested for reproducibility in a real-life breath analysis experiment with several calibration transfer (CT) techniques using transfer samples from the experiment. The experiment consists of classifying breath samples from 15 subjects before and after eating a specific meal using three instruments. We investigate the possibility to transfer calibration models across instruments using transfer samples from the experiment under study, since representative samples of human breath at some conditions are difficult to simulate in a laboratory. For example, exhaled breath from subjects suffering from a disease for which the biomarkers are mostly unknown. Results show that many transfer samples of all the classes under study (in our case meal/no meal) are needed, although some CT methods present reasonably good results with only one class.

scholarly journals Electronic nose dataset for COPD detection from smokers and healthy people through exhaled breath analysis

Data in Brief ◽  
2021 ◽  
Vol 35 ◽  
pp. 106767
Author(s):  
Cristhian Manuel Durán Acevedo ◽  
Carlos A. Cuastumal Vasquez ◽  
Jeniffer Katerine Carrillo Gómez
Keyword(s):  
Electronic Nose ◽  
Breath Analysis ◽  
Healthy People ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis

Cancerous glucose metabolism in lung cancer—evidence from exhaled breath analysis

2016 ◽  
Vol 10 (2) ◽  
pp. 026012 ◽  
Author(s):  
Tali Feinberg ◽  
Layah Alkoby-Meshulam ◽  
Jens Herbig ◽  
John C Cancilla ◽  
Jose S Torrecilla ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Glucose Metabolism ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis
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