Affordable, portable and self-administrable electrical impedance tomography enables global and regional lung function assessment.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
30 11 2022
Historique:
received: 13 05 2022
accepted: 14 11 2022
entrez: 30 11 2022
pubmed: 1 12 2022
medline: 3 12 2022
Statut: epublish

Résumé

Accessibility of diagnostic screening and treatment monitoring devices for respiratory diseases is critical in promoting healthcare and reducing sudden complications and mortality. Spirometry is the standard for diagnosing and monitoring several lung diseases. However, it lacks regional assessment capabilities necessary for detecting subtle regional changes in certain diseases. It also requires challenging breathing maneuvers difficult for elderlies, children, and diseased patients. Here, we actualized an affordable, portable, and self-administrable electrical impedance tomography (EIT) system for home-based lung function assessment and telemedicine. Through simultaneous EIT-spirometry trials on healthy subjects, we demonstrated that our device can predict spirometry indicators over a wide range and can provide regional mapping of these indicators. We further developed a close-to-effortless breathing paradigm and tested it by longitudinally monitoring a COVID-19 discharged subject and two healthy controls with results suggesting the paradigm can detect initial deterioration followed by recovery. Overall, the EIT system can be widely applicable for lung function screening and monitoring both at homes and clinics.

Identifiants

pubmed: 36450830
doi: 10.1038/s41598-022-24330-2
pii: 10.1038/s41598-022-24330-2
pmc: PMC9712422
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

20613

Informations de copyright

© 2022. The Author(s).

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Auteurs

Fedi Zouari (F)

Gense Technologies Ltd., Hong Kong, China.

Wei Yi Oon (WY)

Gense Technologies Ltd., Hong Kong, China.
Department of Electrical and Electronic Engineering, Faculty of Engineering, The University of Hong Kong, Hong Kong, China.

Dipyaman Modak (D)

Gense Technologies Ltd., Hong Kong, China.

Wing Hang Lee (WH)

Gense Technologies Ltd., Hong Kong, China.

Wang Chun Kwok (WC)

Department of Medicine, Queen Mary Hospital, Hong Kong, China.
Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.

Peng Cao (P)

Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.

Wei-Ning Lee (WN)

Department of Electrical and Electronic Engineering, Faculty of Engineering, The University of Hong Kong, Hong Kong, China.

Terence Chi Chun Tam (TCC)

Department of Medicine, Queen Mary Hospital, Hong Kong, China.
Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.

Eddie C Wong (EC)

Gense Technologies Ltd., Hong Kong, China.

Russell W Chan (RW)

Gense Technologies Ltd., Hong Kong, China. russell@gense.tech.

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