Remote and non-invasive monitoring of patients with COVID-19 by smartphone
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
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. |
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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 |
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1809101752438358016 |