Integrated approach for automatic crackle detection based on fractal dimension and box filtering
Autor(a) principal: | |
---|---|
Data de Publicação: | 2016 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/22160 |
Resumo: | Crackles are adventitious respiratory sounds (RS) that provide valuable information on different respiratory conditions. Nevertheless, crackles automatic detection in RS is challenging, mainly when collected in clinical settings. This study aimed to develop an algorithm for automatic crackle detection/characterisation and to evaluate its performance and accuracy against a multi-annotator gold standard. The algorithm is based on 4 main procedures: i) recognition of a potential crackle; ii) verification of its validity; iii) characterisation of crackles parameters; and iv) optimisation of the algorithm parameters. Twenty-four RS files acquired in clinical settings were selected from 10 patients with pneumonia and cystic fibrosis. The algorithm performance was assessed by comparing its results with a multi-annotator gold standard agreement. High level of overall performance (F-score=92%) was achieved. The results highlight the potential of the algorithm for automatic crackle detection and characterisation of RS acquired in clinical settings. |
id |
RCAP_5c959367e69e413db87a99d180216102 |
---|---|
oai_identifier_str |
oai:ria.ua.pt:10773/22160 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Integrated approach for automatic crackle detection based on fractal dimension and box filteringAdventitious respiratory soundsCracklesDiscontinuous respiratory soundsAutomatic detectionClassification algorithmsFractal dimensionBox filteringMulti-annotator gold standard agreementCrackles are adventitious respiratory sounds (RS) that provide valuable information on different respiratory conditions. Nevertheless, crackles automatic detection in RS is challenging, mainly when collected in clinical settings. This study aimed to develop an algorithm for automatic crackle detection/characterisation and to evaluate its performance and accuracy against a multi-annotator gold standard. The algorithm is based on 4 main procedures: i) recognition of a potential crackle; ii) verification of its validity; iii) characterisation of crackles parameters; and iv) optimisation of the algorithm parameters. Twenty-four RS files acquired in clinical settings were selected from 10 patients with pneumonia and cystic fibrosis. The algorithm performance was assessed by comparing its results with a multi-annotator gold standard agreement. High level of overall performance (F-score=92%) was achieved. The results highlight the potential of the algorithm for automatic crackle detection and characterisation of RS acquired in clinical settings.IGI-Global2018-02-14T17:08:01Z2016-10-10T00:00:00Z2016-10-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/22160eng2160-955110.4018/IJRQEH.2016100103Pinho, CátiaOliveira, AnaJácome, CristinaRodrigues, JoãoMarques, Aldainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T11:43:21Zoai:ria.ua.pt:10773/22160Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:56:20.639504Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Integrated approach for automatic crackle detection based on fractal dimension and box filtering |
title |
Integrated approach for automatic crackle detection based on fractal dimension and box filtering |
spellingShingle |
Integrated approach for automatic crackle detection based on fractal dimension and box filtering Pinho, Cátia Adventitious respiratory sounds Crackles Discontinuous respiratory sounds Automatic detection Classification algorithms Fractal dimension Box filtering Multi-annotator gold standard agreement |
title_short |
Integrated approach for automatic crackle detection based on fractal dimension and box filtering |
title_full |
Integrated approach for automatic crackle detection based on fractal dimension and box filtering |
title_fullStr |
Integrated approach for automatic crackle detection based on fractal dimension and box filtering |
title_full_unstemmed |
Integrated approach for automatic crackle detection based on fractal dimension and box filtering |
title_sort |
Integrated approach for automatic crackle detection based on fractal dimension and box filtering |
author |
Pinho, Cátia |
author_facet |
Pinho, Cátia Oliveira, Ana Jácome, Cristina Rodrigues, João Marques, Alda |
author_role |
author |
author2 |
Oliveira, Ana Jácome, Cristina Rodrigues, João Marques, Alda |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Pinho, Cátia Oliveira, Ana Jácome, Cristina Rodrigues, João Marques, Alda |
dc.subject.por.fl_str_mv |
Adventitious respiratory sounds Crackles Discontinuous respiratory sounds Automatic detection Classification algorithms Fractal dimension Box filtering Multi-annotator gold standard agreement |
topic |
Adventitious respiratory sounds Crackles Discontinuous respiratory sounds Automatic detection Classification algorithms Fractal dimension Box filtering Multi-annotator gold standard agreement |
description |
Crackles are adventitious respiratory sounds (RS) that provide valuable information on different respiratory conditions. Nevertheless, crackles automatic detection in RS is challenging, mainly when collected in clinical settings. This study aimed to develop an algorithm for automatic crackle detection/characterisation and to evaluate its performance and accuracy against a multi-annotator gold standard. The algorithm is based on 4 main procedures: i) recognition of a potential crackle; ii) verification of its validity; iii) characterisation of crackles parameters; and iv) optimisation of the algorithm parameters. Twenty-four RS files acquired in clinical settings were selected from 10 patients with pneumonia and cystic fibrosis. The algorithm performance was assessed by comparing its results with a multi-annotator gold standard agreement. High level of overall performance (F-score=92%) was achieved. The results highlight the potential of the algorithm for automatic crackle detection and characterisation of RS acquired in clinical settings. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-10-10T00:00:00Z 2016-10-10 2018-02-14T17:08:01Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10773/22160 |
url |
http://hdl.handle.net/10773/22160 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2160-9551 10.4018/IJRQEH.2016100103 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
IGI-Global |
publisher.none.fl_str_mv |
IGI-Global |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799137617016520704 |