Remote and non-invasive monitoring of patients with COVID-19 by smartphone

Detalhes bibliográficos
Autor(a) principal: Mazzu-Nascimento, Thiago
Data de Publicação: 2021
Outros Autores: Nogueira Evangelista, Danilo, Abubakar, Obeedu, Geraldo Alves Souto, Bernardino, Domingues, Lucas Vinicius, Furtado Silva, Diego, Nogueira-de-Almeida , Carlos Alberto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Medica (Porto Alegre. Online)
Texto Completo: https://revistaseletronicas.pucrs.br/scientiamedica/article/view/39340
Resumo: The pandemic caused by the new coronavirus (SARS-COV-2) has led to more than two million deaths in the world by March 2021. The worldwide call to reduce transmission is enormous. Recently, there has been a rapid growth of telemedicine and the use of mobile health (mHealth) in the context of the COVID-19 pandemic. Smartphone accessories such as a flashlight, camera, microphone, and microprocessor can measure different clinical parameters such as oxygen saturation, blood pressure, heart rate, breathing rate, fever, pulmonary auscultation, and even voice analysis. All these parameters are of great clinical importance when evaluating suspected patients of COVID-19 or monitoring infected patients admitted in various hospitals or in-home isolation. In remote medical care, the results of these parameters can be sent to a call center or a health unit for interpretation by a qualified health professional. Thus, the patient can receive orientations or be immediately referred for in-patient care. The application of machine learning and other artificial intelligence strategies assume a central role in signal processing and are gaining much space in the medical field. In this work, we present different approaches for evaluating clinical parameters that are valuable in the case of COVID-19 and we hope that soon all these parameters can be measured by a single smartphone application, facilitating remote clinical assessments.
id PUC_RS-25_0e7f540fc07e41785c6dd11fd28c7b4a
oai_identifier_str oai:ojs.revistaseletronicas.pucrs.br:article/39340
network_acronym_str PUC_RS-25
network_name_str Scientia Medica (Porto Alegre. Online)
repository_id_str
spelling Remote and non-invasive monitoring of patients with COVID-19 by smartphoneMonitoramento remoto e não invasivo de pacientes com COVID-19 pelo smartphonecoronavirus infectionsmobile healthpandemicssmartphonetelemedicineinfecções por Coronavirussaúde móvelpandemia,smartphonetelemedicinaThe pandemic caused by the new coronavirus (SARS-COV-2) has led to more than two million deaths in the world by March 2021. The worldwide call to reduce transmission is enormous. Recently, there has been a rapid growth of telemedicine and the use of mobile health (mHealth) in the context of the COVID-19 pandemic. Smartphone accessories such as a flashlight, camera, microphone, and microprocessor can measure different clinical parameters such as oxygen saturation, blood pressure, heart rate, breathing rate, fever, pulmonary auscultation, and even voice analysis. All these parameters are of great clinical importance when evaluating suspected patients of COVID-19 or monitoring infected patients admitted in various hospitals or in-home isolation. In remote medical care, the results of these parameters can be sent to a call center or a health unit for interpretation by a qualified health professional. Thus, the patient can receive orientations or be immediately referred for in-patient care. The application of machine learning and other artificial intelligence strategies assume a central role in signal processing and are gaining much space in the medical field. In this work, we present different approaches for evaluating clinical parameters that are valuable in the case of COVID-19 and we hope that soon all these parameters can be measured by a single smartphone application, facilitating remote clinical assessments.A pandemia causada pelo novo coronavírus (SARS-COV-2) foi a responsável por mais de dois milhões de mortes no mundo até março de 2021. O apelo mundial para reduzir a transmissão é enorme. Recentemente, houve um rápido crescimento do uso de telemedicina e saúde móvel (mHealth) no contexto da pandemia causada pela doença COVID-19. Os acessórios dos smartphones, como lanterna, câmera, microfone, bem como o microprocessador podem analisar diferentes parâmetros clínicos, tais como, a saturação de oxigênio, pressão arterial, frequência cardíaca, frequência respiratória, febre, ausculta pulmonar e até mesmo análise da voz. Todos esses parâmetros são de grande importância clínica na avaliação de pacientes suspeitos de COVID-19 ou no monitoramento de pacientes infectados que estão no hospital ou em isolamento domiciliar. No atendimento médico remoto, os resultados desses parâmetros podem ser enviados a uma central de atendimento ou à unidade de saúde para que o resultado seja interpretado por profissional de saúde qualificado. Assim, o paciente pode receber orientações ou ser encaminhado imediatamente para internação. A aplicação de aprendizado de máquina e outras estratégias de inteligência artificial assumem um papel central no processamento de sinais e vêm ganhando muito espaço na área médica. Neste trabalho, apresentamos diferentes abordagens para avaliação de parâmetros clínicos valiosos no caso do COVID-19 e esperamos que em breve todos esses parâmetros possam ser mensurados em um único aplicativo para smartphone, facilitando avaliações clínicas à distância.Editora da PUCRS - ediPUCRS2021-04-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistaseletronicas.pucrs.br/scientiamedica/article/view/3934010.15448/1980-6108.2021.1.39340Scientia Medica; Vol. 31 No. 1 (2021): Single Volume; e39340Scientia Medica; v. 31 n. 1 (2021): Volume Único; e393401980-61081806-556210.15448/1980-6108.2021.1reponame:Scientia Medica (Porto Alegre. Online)instname:Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)instacron:PUC_RSenghttps://revistaseletronicas.pucrs.br/scientiamedica/article/view/39340/26723Copyright (c) 2021 Scientia Medicahttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessMazzu-Nascimento, ThiagoNogueira Evangelista, DaniloAbubakar, ObeeduGeraldo Alves Souto, Bernardino Domingues, Lucas ViniciusFurtado Silva, Diego Nogueira-de-Almeida , Carlos Alberto2022-01-25T17:01:59Zoai:ojs.revistaseletronicas.pucrs.br:article/39340Revistahttps://revistaseletronicas.pucrs.br/scientiamedica/PUBhttps://revistaseletronicas.pucrs.br/scientiamedica/oaiscientiamedica@pucrs.br || editora.periodicos@pucrs.br1980-61081806-5562opendoar:2022-01-25T17:01:59Scientia Medica (Porto Alegre. Online) - Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)false
dc.title.none.fl_str_mv Remote and non-invasive monitoring of patients with COVID-19 by smartphone
Monitoramento remoto e não invasivo de pacientes com COVID-19 pelo smartphone
title Remote and non-invasive monitoring of patients with COVID-19 by smartphone
spellingShingle Remote and non-invasive monitoring of patients with COVID-19 by smartphone
Mazzu-Nascimento, Thiago
coronavirus infections
mobile health
pandemics
smartphone
telemedicine
infecções por Coronavirus
saúde móvel
pandemia,
smartphone
telemedicina
title_short Remote and non-invasive monitoring of patients with COVID-19 by smartphone
title_full Remote and non-invasive monitoring of patients with COVID-19 by smartphone
title_fullStr Remote and non-invasive monitoring of patients with COVID-19 by smartphone
title_full_unstemmed Remote and non-invasive monitoring of patients with COVID-19 by smartphone
title_sort Remote and non-invasive monitoring of patients with COVID-19 by smartphone
author Mazzu-Nascimento, Thiago
author_facet Mazzu-Nascimento, Thiago
Nogueira Evangelista, Danilo
Abubakar, Obeedu
Geraldo Alves Souto, Bernardino
Domingues, Lucas Vinicius
Furtado Silva, Diego
Nogueira-de-Almeida , Carlos Alberto
author_role author
author2 Nogueira Evangelista, Danilo
Abubakar, Obeedu
Geraldo Alves Souto, Bernardino
Domingues, Lucas Vinicius
Furtado Silva, Diego
Nogueira-de-Almeida , Carlos Alberto
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Mazzu-Nascimento, Thiago
Nogueira Evangelista, Danilo
Abubakar, Obeedu
Geraldo Alves Souto, Bernardino
Domingues, Lucas Vinicius
Furtado Silva, Diego
Nogueira-de-Almeida , Carlos Alberto
dc.subject.por.fl_str_mv coronavirus infections
mobile health
pandemics
smartphone
telemedicine
infecções por Coronavirus
saúde móvel
pandemia,
smartphone
telemedicina
topic coronavirus infections
mobile health
pandemics
smartphone
telemedicine
infecções por Coronavirus
saúde móvel
pandemia,
smartphone
telemedicina
description The pandemic caused by the new coronavirus (SARS-COV-2) has led to more than two million deaths in the world by March 2021. The worldwide call to reduce transmission is enormous. Recently, there has been a rapid growth of telemedicine and the use of mobile health (mHealth) in the context of the COVID-19 pandemic. Smartphone accessories such as a flashlight, camera, microphone, and microprocessor can measure different clinical parameters such as oxygen saturation, blood pressure, heart rate, breathing rate, fever, pulmonary auscultation, and even voice analysis. All these parameters are of great clinical importance when evaluating suspected patients of COVID-19 or monitoring infected patients admitted in various hospitals or in-home isolation. In remote medical care, the results of these parameters can be sent to a call center or a health unit for interpretation by a qualified health professional. Thus, the patient can receive orientations or be immediately referred for in-patient care. The application of machine learning and other artificial intelligence strategies assume a central role in signal processing and are gaining much space in the medical field. In this work, we present different approaches for evaluating clinical parameters that are valuable in the case of COVID-19 and we hope that soon all these parameters can be measured by a single smartphone application, facilitating remote clinical assessments.
publishDate 2021
dc.date.none.fl_str_mv 2021-04-05
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revistaseletronicas.pucrs.br/scientiamedica/article/view/39340
10.15448/1980-6108.2021.1.39340
url https://revistaseletronicas.pucrs.br/scientiamedica/article/view/39340
identifier_str_mv 10.15448/1980-6108.2021.1.39340
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistaseletronicas.pucrs.br/scientiamedica/article/view/39340/26723
dc.rights.driver.fl_str_mv Copyright (c) 2021 Scientia Medica
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Scientia Medica
http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Editora da PUCRS - ediPUCRS
publisher.none.fl_str_mv Editora da PUCRS - ediPUCRS
dc.source.none.fl_str_mv Scientia Medica; Vol. 31 No. 1 (2021): Single Volume; e39340
Scientia Medica; v. 31 n. 1 (2021): Volume Único; e39340
1980-6108
1806-5562
10.15448/1980-6108.2021.1
reponame:Scientia Medica (Porto Alegre. Online)
instname:Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)
instacron:PUC_RS
instname_str Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)
instacron_str PUC_RS
institution PUC_RS
reponame_str Scientia Medica (Porto Alegre. Online)
collection Scientia Medica (Porto Alegre. Online)
repository.name.fl_str_mv Scientia Medica (Porto Alegre. Online) - Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)
repository.mail.fl_str_mv scientiamedica@pucrs.br || editora.periodicos@pucrs.br
_version_ 1809101752438358016