Comprehensive Biotechnical System for Screening Risk-based Diagnosis of COVID-19 and Post-COVID Syndrome.

Bioimpedance COVID-19 E-health health care personnel pathophysiology post-COVID syndrome rheography

Journal

Journal of electrical bioimpedance
ISSN: 1891-5469
Titre abrégé: J Electr Bioimpedance
Pays: Poland
ID NLM: 101769140

Informations de publication

Date de publication:
Jan 2022
Historique:
received: 16 06 2022
accepted: 26 08 2022
entrez: 5 10 2022
pubmed: 6 10 2022
medline: 6 10 2022
Statut: epublish

Résumé

At present, there are no hardware or biochemical systems that allow to assess the severity of post-COVID syndrome in vivo. The hardware of the proposed biotechnical system is based on routine transthoracic electrical impedance rheography, which makes it possible to register the frequency characteristics of the patient's bioimpedance response to controlled stress stimulation, thereby simultaneously fixing the characteristics of his productive heart, the state of the hemomicrocirculatory bed, the efficiency of the gas transport function of his blood, and also reliably assess personal reactivity and adaptive potential. Subsequent mathematical approximation of the obtained biometric data by an original neural network makes it possible to rank the results obtained and automatically generate a program of medical rehabilitation for a particular patient, depending on the severity of his post-COVID syndrome. The study results proved two reliable physiological signs confirming the presence of latent post-COVID complications: a decrease in the base impedance value for light exercise and an increase in the length of the systolic arc of the rheocardiogram.

Identifiants

pubmed: 36196240
doi: 10.2478/joeb-2022-0008
pii: joeb-2022-0008
pmc: PMC9487909
doi:

Types de publication

Journal Article

Langues

eng

Pagination

45-53

Informations de copyright

© 2022 Vladimir Savostyanov, Alexander Kobelev, Ivan Kudashov, published by Sciendo.

Déclaration de conflit d'intérêts

Conflict of interest Authors state no conflict of interest.

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Auteurs

Vladimir Savostyanov (V)

Faculty of Biomedical Engineering, Bauman Moscow State Technical University, Moscow, Russia.

Alexander Kobelev (A)

Faculty of Biomedical Engineering, Bauman Moscow State Technical University, Moscow, Russia.

Ivan Kudashov (I)

Faculty of Biomedical Engineering, Bauman Moscow State Technical University, Moscow, Russia.

Classifications MeSH