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Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough

The COVID-19 pandemic created significant interest and demand for infection detection and monitoring solutions. In this paper, we propose a machine learning method to quickly detect COVID-19 using audio recordings made on consumer devices. The approach combines signal processing and noise removal me...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IEEE 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9088778/
https://www.ncbi.nlm.nih.gov/pubmed/35582703
http://dx.doi.org/10.1109/JSTSP.2022.3142514
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collection PubMed
description The COVID-19 pandemic created significant interest and demand for infection detection and monitoring solutions. In this paper, we propose a machine learning method to quickly detect COVID-19 using audio recordings made on consumer devices. The approach combines signal processing and noise removal methods with an ensemble of fine-tuned deep learning networks and enables COVID detection on coughs. We have also developed and deployed a mobile application that uses a symptoms checker together with voice, breath, and cough signals to detect COVID-19 infection. The application showed robust performance on both openly sourced datasets and the noisy data collected during beta testing by the end users.
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spelling pubmed-90887782022-05-13 Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough IEEE J Sel Top Signal Process Article The COVID-19 pandemic created significant interest and demand for infection detection and monitoring solutions. In this paper, we propose a machine learning method to quickly detect COVID-19 using audio recordings made on consumer devices. The approach combines signal processing and noise removal methods with an ensemble of fine-tuned deep learning networks and enables COVID detection on coughs. We have also developed and deployed a mobile application that uses a symptoms checker together with voice, breath, and cough signals to detect COVID-19 infection. The application showed robust performance on both openly sourced datasets and the noisy data collected during beta testing by the end users. IEEE 2022-01-13 /pmc/articles/PMC9088778/ /pubmed/35582703 http://dx.doi.org/10.1109/JSTSP.2022.3142514 Text en This article is free to access and download, along with rights for full text and data mining, re-use and analysis.
spellingShingle Article
Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough
title Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough
title_full Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough
title_fullStr Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough
title_full_unstemmed Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough
title_short Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough
title_sort project achoo: a practical model and application for covid-19 detection from recordings of breath, voice, and cough
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9088778/
https://www.ncbi.nlm.nih.gov/pubmed/35582703
http://dx.doi.org/10.1109/JSTSP.2022.3142514
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