Research progress of electronic nose technology in exhaled breath disease analysis.

Electrical and electronic engineering Sensors

Journal

Microsystems & nanoengineering
ISSN: 2055-7434
Titre abrégé: Microsyst Nanoeng
Pays: England
ID NLM: 101695458

Informations de publication

Date de publication:
2023
Historique:
received: 11 07 2023
revised: 16 08 2023
accepted: 17 08 2023
medline: 13 10 2023
pubmed: 13 10 2023
entrez: 13 10 2023
Statut: epublish

Résumé

Exhaled breath analysis has attracted considerable attention as a noninvasive and portable health diagnosis method due to numerous advantages, such as convenience, safety, simplicity, and avoidance of discomfort. Based on many studies, exhaled breath analysis is a promising medical detection technology capable of diagnosing different diseases by analyzing the concentration, type and other characteristics of specific gases. In the existing gas analysis technology, the electronic nose (eNose) analysis method has great advantages of high sensitivity, rapid response, real-time monitoring, ease of use and portability. Herein, this review is intended to provide an overview of the application of human exhaled breath components in disease diagnosis, existing breath testing technologies and the development and research status of electronic nose technology. In the electronic nose technology section, the three aspects of sensors, algorithms and existing systems are summarized in detail. Moreover, the related challenges and limitations involved in the abovementioned technologies are also discussed. Finally, the conclusion and perspective of eNose technology are presented.

Identifiants

pubmed: 37829158
doi: 10.1038/s41378-023-00594-0
pii: 594
pmc: PMC10564766
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

129

Informations de copyright

© Aerospace Information Research Institute, Chinese Academy of Sciences 2023.

Déclaration de conflit d'intérêts

Conflict of interestThe authors declare no competing interests.

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Auteurs

Ying Li (Y)

School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, 100192 China.
Laboratory of Intelligent Microsystems, Beijing Information Science and Technology University, Beijing, 100192 China.

Xiangyang Wei (X)

School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, 100192 China.
Laboratory of Intelligent Microsystems, Beijing Information Science and Technology University, Beijing, 100192 China.

Yumeng Zhou (Y)

School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, 100192 China.

Jing Wang (J)

School of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun, 130022 China.

Rui You (R)

School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing, 100192 China.
Laboratory of Intelligent Microsystems, Beijing Information Science and Technology University, Beijing, 100192 China.

Classifications MeSH