Cargando…

A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19

The novel coronavirus, renamed SARS-CoV-2 and most commonly referred to as COVID-19, has infected nearly 44.83 million people in 224 countries and has been designated SARS-CoV-2. In this study, we used ‘web of Science’, ‘Scopus’ and ‘goggle scholar’ with the keywords of “SARS-CoV-2 detection” or “co...

Descripción completa

Detalles Bibliográficos
Autores principales: Anand, Satyajit, Sharma, Vikrant, Pourush, Rajeev, Jaiswal, Sandeep
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8975609/
https://www.ncbi.nlm.nih.gov/pubmed/35401978
http://dx.doi.org/10.1016/j.amsu.2022.103519
_version_ 1784680401490411520
author Anand, Satyajit
Sharma, Vikrant
Pourush, Rajeev
Jaiswal, Sandeep
author_facet Anand, Satyajit
Sharma, Vikrant
Pourush, Rajeev
Jaiswal, Sandeep
author_sort Anand, Satyajit
collection PubMed
description The novel coronavirus, renamed SARS-CoV-2 and most commonly referred to as COVID-19, has infected nearly 44.83 million people in 224 countries and has been designated SARS-CoV-2. In this study, we used ‘web of Science’, ‘Scopus’ and ‘goggle scholar’ with the keywords of “SARS-CoV-2 detection” or “coronavirus 2019 detection” or “COVID 2019 detection” or “COVID 19 detection” “corona virus techniques for detection of COVID-19”, “audio techniques for detection of COVID-19”, “speech techniques for detection of COVID-19”, for period of 2019–2021. Some COVID-19 instances have an impact on speech production, which suggests that researchers should look for signs of disease detection in speech utilising audio and speech recognition signals from humans to better understand the condition. It is presented in this review that an overview of human audio signals is presented using an AI (Artificial Intelligence) model to diagnose, spread awareness, and monitor COVID-19, employing bio and non-obtrusive signals that communicated human speech and non-speech audio information is presented. Development of accurate and rapid screening techniques that permit testing at a reasonable cost is critical in the current COVID-19 pandemic crisis, according to the World Health Organization. In this context, certain existing investigations have shown potential in the detection of COVID 19 diagnostic signals from relevant auditory noises, which is a promising development. According to authors, it is not a single “perfect” COVID-19 test that is required, but rather a combination of rapid and affordable tests, non-clinic pre-screening tools, and tools from a variety of supply chains and technologies that will allow us to safely return to our normal lives while we await the completion of the hassle free COVID-19 vaccination process for all ages. This review was able to gather information on biomedical signal processing in the detection of speech, coughing sounds, and breathing signals for the purpose of diagnosing and screening the COVID-19 virus.
format Online
Article
Text
id pubmed-8975609
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-89756092022-04-04 A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19 Anand, Satyajit Sharma, Vikrant Pourush, Rajeev Jaiswal, Sandeep Ann Med Surg (Lond) Review The novel coronavirus, renamed SARS-CoV-2 and most commonly referred to as COVID-19, has infected nearly 44.83 million people in 224 countries and has been designated SARS-CoV-2. In this study, we used ‘web of Science’, ‘Scopus’ and ‘goggle scholar’ with the keywords of “SARS-CoV-2 detection” or “coronavirus 2019 detection” or “COVID 2019 detection” or “COVID 19 detection” “corona virus techniques for detection of COVID-19”, “audio techniques for detection of COVID-19”, “speech techniques for detection of COVID-19”, for period of 2019–2021. Some COVID-19 instances have an impact on speech production, which suggests that researchers should look for signs of disease detection in speech utilising audio and speech recognition signals from humans to better understand the condition. It is presented in this review that an overview of human audio signals is presented using an AI (Artificial Intelligence) model to diagnose, spread awareness, and monitor COVID-19, employing bio and non-obtrusive signals that communicated human speech and non-speech audio information is presented. Development of accurate and rapid screening techniques that permit testing at a reasonable cost is critical in the current COVID-19 pandemic crisis, according to the World Health Organization. In this context, certain existing investigations have shown potential in the detection of COVID 19 diagnostic signals from relevant auditory noises, which is a promising development. According to authors, it is not a single “perfect” COVID-19 test that is required, but rather a combination of rapid and affordable tests, non-clinic pre-screening tools, and tools from a variety of supply chains and technologies that will allow us to safely return to our normal lives while we await the completion of the hassle free COVID-19 vaccination process for all ages. This review was able to gather information on biomedical signal processing in the detection of speech, coughing sounds, and breathing signals for the purpose of diagnosing and screening the COVID-19 virus. Elsevier 2022-04-01 /pmc/articles/PMC8975609/ /pubmed/35401978 http://dx.doi.org/10.1016/j.amsu.2022.103519 Text en © 2022 Published by Elsevier Ltd on behalf of IJS Publishing Group Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Anand, Satyajit
Sharma, Vikrant
Pourush, Rajeev
Jaiswal, Sandeep
A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19
title A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19
title_full A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19
title_fullStr A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19
title_full_unstemmed A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19
title_short A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19
title_sort comprehensive survey on the biomedical signal processing methods for the detection of covid-19
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8975609/
https://www.ncbi.nlm.nih.gov/pubmed/35401978
http://dx.doi.org/10.1016/j.amsu.2022.103519
work_keys_str_mv AT anandsatyajit acomprehensivesurveyonthebiomedicalsignalprocessingmethodsforthedetectionofcovid19
AT sharmavikrant acomprehensivesurveyonthebiomedicalsignalprocessingmethodsforthedetectionofcovid19
AT pourushrajeev acomprehensivesurveyonthebiomedicalsignalprocessingmethodsforthedetectionofcovid19
AT jaiswalsandeep acomprehensivesurveyonthebiomedicalsignalprocessingmethodsforthedetectionofcovid19
AT anandsatyajit comprehensivesurveyonthebiomedicalsignalprocessingmethodsforthedetectionofcovid19
AT sharmavikrant comprehensivesurveyonthebiomedicalsignalprocessingmethodsforthedetectionofcovid19
AT pourushrajeev comprehensivesurveyonthebiomedicalsignalprocessingmethodsforthedetectionofcovid19
AT jaiswalsandeep comprehensivesurveyonthebiomedicalsignalprocessingmethodsforthedetectionofcovid19