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Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients
BACKGROUND: A laboratory-free test for assessing recovery from pulmonary tuberculosis (TB) would be extremely beneficial in regions of the world where laboratory facilities are lacking. Our hypothesis is that analysis of cough sound recordings may provide such a test. In the current paper, we presen...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3468608/ https://www.ncbi.nlm.nih.gov/pubmed/23071550 http://dx.doi.org/10.1371/journal.pone.0046229 |
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author | Larson, Sandra Comina, Germán Gilman, Robert H. Tracey, Brian H. Bravard, Marjory López, José W. |
author_facet | Larson, Sandra Comina, Germán Gilman, Robert H. Tracey, Brian H. Bravard, Marjory López, José W. |
author_sort | Larson, Sandra |
collection | PubMed |
description | BACKGROUND: A laboratory-free test for assessing recovery from pulmonary tuberculosis (TB) would be extremely beneficial in regions of the world where laboratory facilities are lacking. Our hypothesis is that analysis of cough sound recordings may provide such a test. In the current paper, we present validation of a cough analysis tool. METHODOLOGY/PRINCIPAL FINDINGS: Cough data was collected from a cohort of TB patients in Lima, Peru and 25.5 hours of recordings were manually annotated by clinical staff. Analysis software was developed and validated by comparison to manual scoring. Because many patients cough in bursts, coughing was characterized in terms of cough epochs. Our software correctly detects 75.5% of cough episodes with a specificity of 99.6% (comparable to past results using the same definition) and a median false positive rate of 4 false positives/hour, due to the noisy, real-world nature of our dataset. We then manually review detected coughs to eliminate false positives, in effect using the algorithm as a pre-screening tool that reduces reviewing time to roughly 5% of the recording length. This cough analysis approach provides a foundation to support larger-scale studies of coughing rates over time for TB patients undergoing treatment. |
format | Online Article Text |
id | pubmed-3468608 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34686082012-10-15 Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients Larson, Sandra Comina, Germán Gilman, Robert H. Tracey, Brian H. Bravard, Marjory López, José W. PLoS One Research Article BACKGROUND: A laboratory-free test for assessing recovery from pulmonary tuberculosis (TB) would be extremely beneficial in regions of the world where laboratory facilities are lacking. Our hypothesis is that analysis of cough sound recordings may provide such a test. In the current paper, we present validation of a cough analysis tool. METHODOLOGY/PRINCIPAL FINDINGS: Cough data was collected from a cohort of TB patients in Lima, Peru and 25.5 hours of recordings were manually annotated by clinical staff. Analysis software was developed and validated by comparison to manual scoring. Because many patients cough in bursts, coughing was characterized in terms of cough epochs. Our software correctly detects 75.5% of cough episodes with a specificity of 99.6% (comparable to past results using the same definition) and a median false positive rate of 4 false positives/hour, due to the noisy, real-world nature of our dataset. We then manually review detected coughs to eliminate false positives, in effect using the algorithm as a pre-screening tool that reduces reviewing time to roughly 5% of the recording length. This cough analysis approach provides a foundation to support larger-scale studies of coughing rates over time for TB patients undergoing treatment. Public Library of Science 2012-10-10 /pmc/articles/PMC3468608/ /pubmed/23071550 http://dx.doi.org/10.1371/journal.pone.0046229 Text en © 2012 Larson et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Larson, Sandra Comina, Germán Gilman, Robert H. Tracey, Brian H. Bravard, Marjory López, José W. Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients |
title | Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients |
title_full | Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients |
title_fullStr | Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients |
title_full_unstemmed | Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients |
title_short | Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients |
title_sort | validation of an automated cough detection algorithm for tracking recovery of pulmonary tuberculosis patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3468608/ https://www.ncbi.nlm.nih.gov/pubmed/23071550 http://dx.doi.org/10.1371/journal.pone.0046229 |
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