Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients

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This work was funded in part by National Institutes of Health through awards 5D43TW006581 "Infectious Diseases Training Program in Peru'' and R21 AI094143 "Cough-A Rapid Indication of Response to Therapy in Pulmonary Tuberculosis''. JL and MB were supported by NIH Fogar...

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Detalles Bibliográficos
Autores: Larson, S, Comina, G, Gilman, RH, Tracey, BH, Bravard, M, Lopez, JW
Formato: artículo
Fecha de Publicación:2012
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/1132
Enlace del recurso:https://hdl.handle.net/20.500.12390/1132
https://doi.org/10.1371/journal.pone.0046229
Nivel de acceso:acceso abierto
Materia:Leicester
Cough
Bronchitis
https://purl.org/pe-repo/ocde/ford#2.06.02
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oai_identifier_str oai:repositorio.concytec.gob.pe:20.500.12390/1132
network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv 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
spellingShingle Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients
Larson, S
Leicester
Cough
Bronchitis
https://purl.org/pe-repo/ocde/ford#2.06.02
title_short 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_sort Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients
author Larson, S
author_facet Larson, S
Comina, G
Gilman, RH
Tracey, BH
Bravard, M
Lopez, JW
author_role author
author2 Comina, G
Gilman, RH
Tracey, BH
Bravard, M
Lopez, JW
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Larson, S
Comina, G
Gilman, RH
Tracey, BH
Bravard, M
Lopez, JW
dc.subject.none.fl_str_mv Leicester
topic Leicester
Cough
Bronchitis
https://purl.org/pe-repo/ocde/ford#2.06.02
dc.subject.es_PE.fl_str_mv Cough
Bronchitis
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.06.02
description This work was funded in part by National Institutes of Health through awards 5D43TW006581 "Infectious Diseases Training Program in Peru'' and R21 AI094143 "Cough-A Rapid Indication of Response to Therapy in Pulmonary Tuberculosis''. JL and MB were supported by NIH Fogarty Foundation fellowships. G. Comina wants to thank the Consejo Nacional de Ciencia, Tecnologia e Innovacion Tecnologica of Peru (CONCYTEC) for their support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
publishDate 2012
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2012
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/1132
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1371/journal.pone.0046229
dc.identifier.isi.none.fl_str_mv 312385200017
url https://hdl.handle.net/20.500.12390/1132
https://doi.org/10.1371/journal.pone.0046229
identifier_str_mv 312385200017
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv PLOS ONE
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.none.fl_str_mv https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0/
dc.publisher.none.fl_str_mv Public Library of Science
publisher.none.fl_str_mv Public Library of Science
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
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spelling Publicationrp03155500rp00605500rp00604500rp03194600rp03193600rp03192600Larson, SComina, GGilman, RHTracey, BHBravard, MLopez, JW2024-05-30T23:13:38Z2024-05-30T23:13:38Z2012https://hdl.handle.net/20.500.12390/1132https://doi.org/10.1371/journal.pone.0046229312385200017This work was funded in part by National Institutes of Health through awards 5D43TW006581 "Infectious Diseases Training Program in Peru'' and R21 AI094143 "Cough-A Rapid Indication of Response to Therapy in Pulmonary Tuberculosis''. JL and MB were supported by NIH Fogarty Foundation fellowships. G. Comina wants to thank the Consejo Nacional de Ciencia, Tecnologia e Innovacion Tecnologica of Peru (CONCYTEC) for their support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.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.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengPublic Library of SciencePLOS ONEinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/LeicesterCough-1Bronchitis-1https://purl.org/pe-repo/ocde/ford#2.06.02-1Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patientsinfo:eu-repo/semantics/articlereponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#20.500.12390/1132oai:repositorio.concytec.gob.pe:20.500.12390/11322024-05-30 15:23:43.369https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="e3bdde12-2f4e-42ee-809c-a5db17d73fb7"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients</Title> <PublishedIn> <Publication> <Title>PLOS ONE</Title> </Publication> </PublishedIn> <PublicationDate>2012</PublicationDate> <DOI>https://doi.org/10.1371/journal.pone.0046229</DOI> <ISI-Number>312385200017</ISI-Number> <Authors> <Author> <DisplayName>Larson, S</DisplayName> <Person id="rp03155" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Comina, G</DisplayName> <Person id="rp00605" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Gilman, RH</DisplayName> <Person id="rp00604" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Tracey, BH</DisplayName> <Person id="rp03194" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Bravard, M</DisplayName> <Person id="rp03193" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Lopez, JW</DisplayName> <Person id="rp03192" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Public Library of Science</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by/4.0/</License> <Keyword>Leicester</Keyword> <Keyword>Cough</Keyword> <Keyword>Bronchitis</Keyword> <Abstract>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.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
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Validation of an Automated Cough Detection Algorithm for Tracking Recovery of Pulmonary Tuberculosis Patients
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