Ultrasensitive laser spectroscopy for breath analysis View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-03

AUTHORS

J. Wojtas, Z. Bielecki, T. Stacewicz, J. Mikołajczyk, M. Nowakowski

ABSTRACT

At present there are many reasons for seeking new methods and technologies that aim to develop new and more perfect sensors for different chemical compounds. However, the main reasons are safety ensuring and health care. In the paper, recent advances in the human breath analysis by the use of different techniques are presented. We have selected non-invasive ones ensuring detection of pathogenic changes at a molecular level. The presence of certain molecules in the human breath is used as an indicator of a specific disease. Thus, the analysis of the human breath is very useful for health monitoring. We have shown some examples of diseases’ biomarkers and various methods capable of detecting them. Described methods have been divided into non-optical and optical methods. The former ones are the following: gas chromatography, flame ionization detection, mass spectrometry, ion mobility spectrometry, proton transfer reaction mass spectrometry, selected ion flow tube mass spectrometry. In recent twenty years, the optical methods have become more popular, especially the laser techniques. They have a great potential for detection and monitoring of the components in the gas phase. These methods are characterized by high sensitivity and good selectivity. The spectroscopic sensors provide the opportunity to detect specific gases and to measure their concentration either in a sampling place or a remote one. Multipass spectroscopy, cavity ring-down spectroscopy, and photo-acoustic spectroscopy were characterised in the paper as well. More... »

PAGES

26-39

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.2478/s11772-012-0011-4

    DOI

    http://dx.doi.org/10.2478/s11772-012-0011-4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1043996688


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