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dc.contributorDepartament de Salut
dc.contributor.authorFarrús, Mireia
dc.contributor.authorCodina-Filba, Joan
dc.contributor.authorReixach-Espaulella, Elisenda
dc.contributor.authorAndrés, Erik
dc.contributor.authorSans Corrales, Mireia
dc.contributor.authorGarcia Planas, Noemí
dc.contributor.authorVilaseca, Josep
dc.date.accessioned2022-03-21T12:17:07Z
dc.date.available2022-03-21T12:17:07Z
dc.date.issued2021-08-29
dc.identifier.citationFarrús M, Codina-Filbà J, Reixach E, Andrés E, Sans M, Garcia N, et al. Speech-based support system to supervise chronic obstructive pulmonary disease patient status. Appl Sci. 2021;11(7999).
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/11351/7225
dc.descriptionChronic obstructive pulmonary disease; Prosody; Speech analysis
dc.description.abstractPatients with chronic obstructive pulmonary disease (COPD) suffer from voice changes with respect to the healthy population. However, two issues remain to be studied: how long-term speech elements such as prosody are affected; and whether physical effort and medication also affect the speech of patients with COPD, and if so, how an automatic speech-based detection system of COPD measurements can be influenced by these changes. The aim of the current study is to address both issues. To this end, long read speech from COPD and control groups was recorded, and the following experiments were performed: (a) a statistical analysis over the study and control groups to analyse the effects of physical effort and medication on speech; and (b) an automatic classification experiment to analyse how different recording conditions can affect the performance of a COPD detection system. The results obtained show that speech—especially prosodic features—is affected by physical effort and inhaled medication in both groups, though in opposite ways; and that the recording condition has a relevant role when designing an automatic COPD detection system. The current work takes a step forward in the understanding of speech in patients with COPD, and in turn, in the research on its automatic detection to help professionals supervising patient status.
dc.language.isoeng
dc.publisherMDPI
dc.relation.ispartofseriesApplied sciences;11
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceScientia
dc.subjectAnàlisi prosòdica
dc.subjectPulmons - Malalties obstructives
dc.subject.meshArticulation Disorders
dc.subject.meshLung Diseases, Obstructive
dc.titleSpeech-based support system to supervise chronic obstructive pulmonary disease patient status
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.3390/app11177999
dc.subject.decstrastornos de la articulación del habla
dc.subject.decsenfermedades pulmonares obstructivas
dc.relation.publishversionhttps://doi.org/10.3390/app11177999
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.audienceProfessionals
dc.contributor.authoraffiliation[Farrús M] Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain. Language and Computation Centre, Universitat de Barcelona, Barcelona, Spain. [Codina-Filbà J] Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain. [Reixach E, Andrés E] Fundació TIC Salut Social, Departament de Salut, Generalitat de Catalunya, Barcelona, Spain. [Sans M, Garcia N] CAP Comte Borrell, Consorci d’Atenció Primària de Salut de Barcelona Esquerra (CAPSBE), Departament de Salut, Generalitat de Catalunya, Barcelona, Spain. [Vilaseca J] CAP Comte Borrell, Consorci d’Atenció Primària de Salut de Barcelona Esquerra (CAPSBE), Departament de Salut, Generalitat de Catalunya, Barcelona, Spain. Grup de Recerca Transversal en Atenció Primària, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain. Universitat de Vic, Universitat Central de Catalunya, Vic, Spain. Department of Medicine, Universitat de Barcelona, Barcelona, Spain
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess


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