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Volatile Organic Compounds (VOCs) are organic molecules that have low boiling points and therefore easily evaporate into the air. They pose significant risks to human health, making their accurate detection the crux of efforts to monitor…

Volatile organic compounds (VOCs) represent a novel but underexplored modality for emotion recognition. This paper presents a systematic evidence synthesis and exploratory investigation of VOC-based affective computing using low-cost…

Human-Computer Interaction · Computer Science 2025-12-25 Nicolai Plintz , Marcus Vetter , Dirk Ifenthaler

Detection of Volatile Organic Compounds (VOCs) from the breath is becoming a viable route for the early detection of diseases non-invasively. This paper presents a sensor array with three metal oxide electrodes that can use machine learning…

Volatile organic compounds (VOCs) are valuable health indicators, with synthetic breath biomarkers offering rapid and disease specific diagnostics. However, their <100 ppb level exhalation requires mass spectrometry, limiting clinical…

Human exposure to Volatile Organic Compounds (VOCs) and their presence in indoor and working environments is recognized as a serious health risk, causing impairment of varying severity. Different detecting systems able to monitor VOCs are…

Diabetes is a global health burden, and early detection is critical for timely intervention. This study explores a non-invasive, data-driven framework to identify individuals at risk of diabetes using Volatile Organic Compounds (VOCs) and…

Machine Learning · Computer Science 2026-05-22 Varsha Sharma , Prasanta K. Guha , Avik Ghose

To date, researchers have identified over 1000 different compounds contained in human breath. These molecules have both endogenous and exogenous origins and provide information about physiological processes occurring in the body as well as…

Breath analysis enables rapid, non-invasive diagnostics, as well as long-term monitoring, of human health through the identification and quantification of exhaled biomarkers. Here, for the first time, we demonstrate the remarkable…

Chemical Physics · Physics 2022-06-07 Qizhong Liang , Ya-Chu Chan , P. Bryan Changala , David J. Nesbitt , Jun Ye , Jutta Toscano

This paper presents the results of an automated volatile organic compound (VOC) classification process implemented by embedding a machine learning algorithm into an Arduino Uno board. An electronic nose prototype is constructed to detect…

Volatile organic compounds emitted by a human body form a chemical signature capable of providing invaluable information on the physiological status of an individual and, thereby, could serve as signs-of-life for detecting victims after…

Other Quantitative Biology · Quantitative Biology 2015-04-24 Pawel Mochalski , Karl Unterkofler , Gerald Teschl , Anton Amann

A gas cell for in-situ measurements of Volatile Organic Compounds (VOCs) and their adsorption behavior on different surfaces by means of X-Ray Fluorescence (XRF) and X-ray Absorption Fine-Structure (XAFS) spectroscopy has been developed.…

Methods for reduction of Volatile Organic Compounds (VOCs) content in air depend on the 10 application considered. For low concentration and low flux, non-thermal plasma methods are often considered as efficient. However, the complex…

Background: Classification of volatile organic compounds (VOCs) is of interest in many fields. Examples include but are not limited to medicine, detection of explosives, and food quality control. Measurements collected with electronic noses…

Using machine learning algorithms for the rapid diagnosis and detection of the COVID-19 pandemic and isolating the patients from crowded environments are very important to controlling the epidemic. This study aims to develop a point-of-care…

In this paper we develop a simple two compartment model which extends the Farhi equation to the case when the inhaled concentration of a volatile organic compound (VOC) is not zero. The model connects the exhaled breath concentration of…

Quantitative Methods · Quantitative Biology 2015-06-26 Karl Unterkofler , Julian King , Pawel Mochalski , Martin Jandacka , Helin Koc , Susanne Teschl , Anton Amann , Gerald Teschl

This paper proposes a weakly-supervised machine learning-based approach aiming at a tool to alert patients about possible respiratory diseases. Various types of pathologies may affect the respiratory system, potentially leading to severe…

Sound · Computer Science 2023-12-05 Michele Cozzatti , Federico Simonetta , Stavros Ntalampiras

Breath analysis has emerged as a critical tool in health monitoring, offering insights into respiratory function, disease detection, and continuous health assessment. While traditional contact-based methods are reliable, they often pose…

Machine Learning · Computer Science 2025-08-14 Almustapha A. Wakili , Babajide J. Asaju , Woosub Jung

Respiratory ailments are increasing globally at an alarming rate and are currently one of the leading factors of death and infirmity worldwide. Among respiratory diseases, those linked to poor air quality and pollutants are increasing at a…

Quantitative Methods · Quantitative Biology 2025-12-03 Shelby Lacouture , Mitchell Kelley , Noah Plues , Laszlo Hunyadi , Emily Sundman , Annette Sobel , Robert V. Duncan

Biogenic Volatile Organic Compounds (BVOCs) play a critical role in biosphere-atmosphere interactions, being a key factor in the physical and chemical properties of the atmosphere and climate. Acquiring large and fine-grained BVOC emission…

Image and Video Processing · Electrical Eng. & Systems 2023-07-04 Antonio Giganti , Sara Mandelli , Paolo Bestagini , Marco Marcon , Stefano Tubaro

Real-time gas classification is an essential issue and challenge in applications such as food and beverage quality control, accident prevention in industrial environments, for instance. In recent years, the Deep Learning (DL) models have…

Signal Processing · Electrical Eng. & Systems 2020-10-05 Juan C. Rodriguez Gamboa , Adenilton J. da Silva , Ismael C. S. Araujo , Eva Susana Albarracin E. , Cristhian M. Duran A
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