Acute respiratory viral infections in active-duty military personnel: Early diagnosis using biometric video analytics-Reference-Cited by-同舟云学术

Acute respiratory viral infections in active-duty military personnel: Early diagnosis using biometric video analytics

Published:2023-06-28 Issue:11 Volume: Page:44-49
ISSN:2949-2807
Container-title:Medical alphabet
language:
Short-container-title:Medicinskij alfavit

Author:

Kuzin A. A.¹^ORCID,Zobov A. E.¹^ORCID,Parfenov S. A.¹^ORCID,Semenov A. A.¹^ORCID,Glushakov R. I.¹,Smirnov A. N.²^ORCID

Affiliation:

1. Military Medical Academy n.a. S.M. Kirov

2. 321 Military Clinical Hospital

Abstract

Acute respiratory viral infections (ARVIs) are an important cause of morbidity in the military setting for many decades. It has high rates of seeking medical care and job loss. Due to the stressful living conditions and activities and other abundance of risk factors, the most effective anti-epidemic measures in military teams should be considered the early detection of infected persons and their timely isolation. We used a modern data present a review that focuses on technical level of current software and hardware systems for biometric video analytics and artiﬁcial intelligence algorithms, which make it possible to detect early symptoms of infectious diseases. A list of most common symptoms in ARVIs that can be recognized using video surveillance and video analytics was determined. These symptoms can be used as initial empirical data for a comprehensive automated assessment of the person’s individual state parameters. A scheme for the operation of a software and hardware complex for video data analytics for the early detection of infected persons is proposed. This scheme is necessary because some infected persons appear healthy for some time but keep infecting others when they interact with them. The use of independent machine learning based on the principle of a retrospective statistical analysis of locomotor data and other signs identiﬁed in infected persons in the prodromal period of the disease can establish reliable diagnostic correlations based on big data. The data accumulation of the features of the preclinical stages of ARVIs using the proposed approach will lead to the formation of a minimum informative set of video analytical signs (markers) that allow them to be reliably recognized in the prodromal period for the purpose of timely isolation and additional examination of the infected persons and to protect non-infected persons. The implementation of the developed direction will improve the effectiveness of anti-epidemic measures through early localization and liquidation of the epidemic.

Publisher

Alfmed LLC

Subject

Materials Chemistry,Economics and Econometrics,Media Technology,Forestry

Reference26 articles.

1. Alimov A.V. The incidence of respiratory viral infections in the military team. A.V. Alimov [et al.]. Military Medical Journal. 2019. No. 12. P. 45–49.

2. Velmozhko N.I. Analysis of changes in the parameters of the human body in the process of performing physical exercises using the Kinect video controller. N.I. Velmozhko. Polytechnic Youth Magazine. 2020. No. 3 (44). Pp. 6–15.

3. Dobrykh V.A. Relationship of subjective clinical symptoms at the onset of acute lower respiratory tract infections with the further course of the disease. V.A. Good [et al.]. Far Eastern Medical Journal. 2014. No. 3. P. 26–28.

4. Artebyakin S.V. The etiological structure of respiratory viral infections in the organized military collective of the Central Military District during the epidemic seasons of 2016– 2020. S.V. Artebyakin [et al.]. Bulletin of Ros. Military-Med. Acad. 2020. No. 4. P. 45–48.

5. Baumtrog V.E. To the question of the possibilities of modern intelligent video surveillance systems. V.E. Baumtrog, V.G. Pirogov. Bulletin of the Barnaul Law Institute of the Ministry of Internal Affairs of Russia. 2017. No. 1 (32). Pp. 212–215.