scholarly journals Sensors for Enhanced Detection of Acetone as a Potential Tool for Noninvasive Diabetes Monitoring

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2298 ◽  
Author(s):  
Artur Rydosz
Keyword(s):  
Gas Sensors ◽  
Medical Diagnosis ◽  
Point Of View ◽  
Exhaled Breath ◽  
Promising Tool ◽  
Exhaled Breath Analysis ◽  
Volatile Organic ◽  
Diabetes Monitoring ◽  
Acetone Detection ◽  
Potential Tool

Measurement of blood-borne volatile organic compounds (VOCs) occurring in human exhaled breath as a result of metabolic changes or pathological disorders is a promising tool for noninvasive medical diagnosis, such as exhaled acetone measurements in terms of diabetes monitoring. The conventional methods for exhaled breath analysis are based on spectrometry techniques, however, the development of gas sensors has made them more and more attractive from a medical point of view. This review focuses on the latest achievements in gas sensors for exhaled acetone detection. Several different methods and techniques are presented and discussed as well.

scholarly journals Data preprocessing workflow for exhaled breath analysis by GC/MS using open sources

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rosa Alba Sola Martínez ◽  
José María Pastor Hernández ◽  
Gema Lozano Terol ◽  
Julia Gallego-Jara ◽  
Luis García-Marcos ◽  
...  
Keyword(s):  
Biomarker Discovery ◽  
Data Preprocessing ◽  
Exhaled Breath ◽  
Sample Collection ◽  
Clinical Tool ◽  
Chronic Respiratory Diseases ◽  
Current State ◽  
Exhaled Breath Analysis ◽  
High Prevalence ◽  
Volatile Organic

AbstractThe noninvasive diagnosis and monitoring of high prevalence diseases such as cardiovascular diseases, cancers and chronic respiratory diseases are currently priority objectives in the area of health. In this regard, the analysis of volatile organic compounds (VOCs) has been identified as a potential noninvasive tool for the diagnosis and surveillance of several diseases. Despite the advantages of this strategy, it is not yet a routine clinical tool. The lack of reproducible protocols for each step of the biomarker discovery phase is an obstacle of the current state. Specifically, this issue is present at the data preprocessing step. Thus, an open source workflow for preprocessing the data obtained by the analysis of exhaled breath samples using gas chromatography coupled with single quadrupole mass spectrometry (GC/MS) is presented in this paper. This workflow is based on the connection of two approaches to transform raw data into a useful matrix for statistical analysis. Moreover, this workflow includes matching compounds from breath samples with a spectral library. Three free packages (xcms, cliqueMS and eRah) written in the language R are used for this purpose. Furthermore, this paper presents a suitable protocol for exhaled breath sample collection from infants under 2 years of age for GC/MS.

scholarly journals MOS Sensors Array for the Discrimination of Lung Cancer and At-Risk Subjects with Exhaled Breath Analysis

Chemosensors ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 209
Author(s):  
Davide Marzorati ◽  
Luca Mainardi ◽  
Giulia Sedda ◽  
Roberto Gasparri ◽  
Lorenzo Spaggiari ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Survival Rate ◽  
Mortality Rate ◽  
Early Diagnosis ◽  
Gas Sensor ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis

Lung cancer is characterized by a tremendously high mortality rate and a low 5-year survival rate when diagnosed at a late stage. Early diagnosis of lung cancer drastically reduces its mortality rate and improves survival. Exhaled breath analysis could offer a tool to clinicians to improve the ability to detect lung cancer at an early stage, thus leading to a reduction in the associated survival rate. In this paper, we present an electronic nose for the automatic analysis of exhaled breath. A total of five a-specific gas sensors were embedded in the electronic nose, making it sensitive to different volatile organic compounds (VOCs) contained in exhaled breath. Nine features were extracted from each gas sensor response to exhaled breath, identifying the subject breathprint. We tested the electronic nose on a cohort of 80 subjects, equally split between lung cancer and at-risk control subjects. Including gas sensor features and clinical features in a classification model, recall, precision, and accuracy of 78%, 80%, and 77% were reached using a fourfold cross-validation approach. The addition of other a-specific gas sensors, or of sensors specific to certain compounds, could improve the classification accuracy, therefore allowing for the development of a clinical tool to be integrated in the clinical pipeline for exhaled breath analysis and lung cancer early diagnosis.

Optical Gas Sensors for Exhaled Breath Analysis

2017 ◽  
Author(s):  
Paula Regina Fortes ◽  
João Flávio da Silveira Petruci ◽  
Ivo Milton Raimundo
Keyword(s):  
Gas Sensors ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
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 Detection and quantification of exhaled volatile organic compounds in mechanically ventilated patients – comparison of two sampling methods

The Analyst ◽  
2021 ◽  
Vol 146 (1) ◽  
pp. 222-231
Author(s):  
Pouline M. P. van Oort ◽  
Iain R. White ◽  
Waqar Ahmed ◽  
Craig Johnson ◽  
Jonathan Bannard-Smith ◽  
...  
Keyword(s):  
Organic Compounds ◽  
Sampling Methods ◽  
Exhaled Breath ◽  
Mechanically Ventilated ◽  
Mechanically Ventilated Patients ◽  
Exhaled Breath Analysis ◽  
Volatile Organic ◽  
Potential Sources ◽  
Ventilated Patients ◽  
Detection And Quantification

Exhaled breath analysis is a promising new diagnostic tool, but currently no standardised method for sampling is available in mechanically ventilated patients. We identified potential sources of bias as illustrated in this figure.

Review of the algorithms used in exhaled breath analysis for the detection of diabetes

2022 ◽  
Author(s):  
Anna Paleczek ◽  
Artur Maciej Rydosz
Keyword(s):  
Gas Sensors ◽  
Support Vector ◽  
Exhaled Breath ◽  
Diagnostic Systems ◽  
Exhaled Breath Analysis ◽  
Potential Biomarker ◽  
Exhaled Air ◽  
Medical Diagnostic ◽  
Detection Of Biomarkers ◽  
Intensive Work

Abstract Currently, intensive work is underway on the development of truly noninvasive medical diagnostic systems, including respiratory analysers based on the detection of biomarkers of several diseases including diabetes. In terms of diabetes, acetone is considered as a one of the potential biomarker, although is not the single one. Therefore, the selective detection is crucial. Most often, the analysers of exhaled breath are based on the utilization of several commercially available gas sensors or on specially designed and manufactured gas sensors to obtain the highest selectivity and sensitivity to diabetes biomarkers present in the exhaled air. An important part of each system are the algorithms that are trained to detect diabetes based on data obtained from sensor matrices. The prepared review of the literature showed that there are many limitations in the development of the versatile breath analyser, such as high metabolic variability between patients, but the results obtained by researchers using the algorithms described in this paper are very promising and most of them achieve over 90% accuracy in the detection of diabetes in exhaled air. This paper summarizes the results using various measurement systems, feature extraction and feature selection methods as well as algorithms such as Support Vector Machines, k-Nearest Neighbours and various variations of Neural Networks for the detection of diabetes in patient samples and simulated artificial breath samples.

Metal oxide gas sensors for exhaled breath analysis: a review

2021 ◽  
Author(s):  
Daejeong Yang ◽  
Ramu Adam Gopal ◽  
Telmenbayar Lkhagvaa ◽  
Dongjin Choi
Keyword(s):  
Metal Oxide ◽  
Gas Sensors ◽  
Breath Analysis ◽  
Exhaled Breath ◽  
Exhaled Breath Analysis ◽  
Metal Oxide Gas Sensors

Exhaled Breath Analysis in Tuberculosis Case Detection: The New Horizon

2013 ◽  
Vol 3 (2) ◽  
pp. 243-244
Author(s):  
Ranabir Pal ◽  
S Dahal ◽  
A Gurung
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Gaseous Mixture ◽  
Nobel Prize Winner ◽  
Exhaled Breath ◽  
Tuberculosis Case ◽  
Exhaled Breath Analysis ◽  
Organ Systems ◽  
Volatile Organic ◽  
Health And Disease

Sixty years ago, Nobel Prize winner Linus Pauling proposed the concept that human breath is a complex and dynamic gaseous mixture of more than 200 different endogenous volatile organic compounds (VOCs) that are continually being released in different quantities within the internal environment during health and disease. The researchers estimate that more than a thousand chemicals produced in different organ-systems as metabolic end products come out every minute through the respiratory tract. Volatile organic compounds and other products of oxidative stress are a big chunk among these exhaled breath elements.DOI: http://doi.dx.org/10.3126/nje.v3i2.8509

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