Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status

Applied Sciences

Josep Vilaseca¹  Noemí Garcia¹  Mireia Sans¹  Joan Codina-Filbಠ Mireia Farrús²  Erik Andrés³  Elisenda Reixach³ 

[1] CAP Comte Borrell, Consorci d’Atenció Primària de Salut de Barcelona Esquerra (CAPSBE), 08029 Barcelona, Spain;Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, Spain;Fundació TIC Salut Social, Departament de Salut, Generalitat de Catalunya, 08005 Barcelona, Spain;

关键词: chronic obstructive pulmonary disease;    COPD;    machine learning;    prosody;    speech analysis;   

DOI  :  10.3390/app11177999

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown