Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status
Patients 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 pati...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-08-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/17/7999 |
| _version_ | 1797521677825867776 |
|---|---|
| author | Mireia Farrús Joan Codina-Filbà Elisenda Reixach Erik Andrés Mireia Sans Noemí Garcia Josep Vilaseca |
| author_facet | Mireia Farrús Joan Codina-Filbà Elisenda Reixach Erik Andrés Mireia Sans Noemí Garcia Josep Vilaseca |
| author_sort | Mireia Farrús |
| collection | DOAJ |
| description | Patients 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. |
| first_indexed | 2024-03-10T08:15:56Z |
| format | Article |
| id | doaj.art-b66dc76232de4404b7ff2981be0924f0 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T08:15:56Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-b66dc76232de4404b7ff2981be0924f02023-11-22T10:19:51ZengMDPI AGApplied Sciences2076-34172021-08-011117799910.3390/app11177999Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient StatusMireia Farrús0Joan Codina-Filbà1Elisenda Reixach2Erik Andrés3Mireia Sans4Noemí Garcia5Josep Vilaseca6Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, SpainDepartment of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, SpainFundació TIC Salut Social, Departament de Salut, Generalitat de Catalunya, 08005 Barcelona, SpainFundació TIC Salut Social, Departament de Salut, Generalitat de Catalunya, 08005 Barcelona, SpainCAP Comte Borrell, Consorci d’Atenció Primària de Salut de Barcelona Esquerra (CAPSBE), 08029 Barcelona, SpainCAP Comte Borrell, Consorci d’Atenció Primària de Salut de Barcelona Esquerra (CAPSBE), 08029 Barcelona, SpainCAP Comte Borrell, Consorci d’Atenció Primària de Salut de Barcelona Esquerra (CAPSBE), 08029 Barcelona, SpainPatients 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.https://www.mdpi.com/2076-3417/11/17/7999chronic obstructive pulmonary diseaseCOPDmachine learningprosodyspeech analysis |
| spellingShingle | Mireia Farrús Joan Codina-Filbà Elisenda Reixach Erik Andrés Mireia Sans Noemí Garcia Josep Vilaseca Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status Applied Sciences chronic obstructive pulmonary disease COPD machine learning prosody speech analysis |
| title | Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status |
| title_full | Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status |
| title_fullStr | Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status |
| title_full_unstemmed | Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status |
| title_short | Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status |
| title_sort | speech based support system to supervise chronic obstructive pulmonary disease patient status |
| topic | chronic obstructive pulmonary disease COPD machine learning prosody speech analysis |
| url | https://www.mdpi.com/2076-3417/11/17/7999 |
| work_keys_str_mv | AT mireiafarrus speechbasedsupportsystemtosupervisechronicobstructivepulmonarydiseasepatientstatus AT joancodinafilba speechbasedsupportsystemtosupervisechronicobstructivepulmonarydiseasepatientstatus AT elisendareixach speechbasedsupportsystemtosupervisechronicobstructivepulmonarydiseasepatientstatus AT erikandres speechbasedsupportsystemtosupervisechronicobstructivepulmonarydiseasepatientstatus AT mireiasans speechbasedsupportsystemtosupervisechronicobstructivepulmonarydiseasepatientstatus AT noemigarcia speechbasedsupportsystemtosupervisechronicobstructivepulmonarydiseasepatientstatus AT josepvilaseca speechbasedsupportsystemtosupervisechronicobstructivepulmonarydiseasepatientstatus |