Speech characteristics as markers of COPD and exacerbations

A short overview: In an EFRO project (see below) we collected speech recordings of persons with COPD (Chronic Obstructive Pulmonary Disease), in 2 conditions: stable and exacerbation (lung attack). After the EFRO project, these speech recordings were further used for subsequent research (see the publications below).
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Brief summary of the results: In our research we observed that speech characteristics can be used as biomarkers for COPD, and for exacerbations (lung attacks). In other words, there are differences in the speech characteristics of persons with and without COPD, and exacerbations (lung attacks) lead to changes in the speech characteristics.
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EFRO project (PROJ-00187): Spraakverandering als vroege marker longaanval.
(In English: Speech change as an early marker of lung attack.)
Partners:
o Hanneke van Helvoort, Yvonne Heijdra; Dept. of Pulmonary Diseases, Radboudumc
o Bas Dirkson; Apps4Air
o Marieke Snijder-van As; Relitech
o Helmer Strik; CLST, CLS, Radboud Univ.

Publications
o Helmer Strik, Julia Merkus (2019) Voorkomen van longaanvallen bij COPD met ‘een digitale luistervink’. In: December 2019 issue of DIXIT Magazine on ‘TST en Gezondheidszorg’.
o Julia Merkus (2019) Digital Eavesdropper – Acoustic speech characteristics as markers of exacerbations in COPD patients. MA Thesis, Radboud University, Nijmegen, 2019.
o Julia Merkus, Ferdy Hubers, Catia Cucchiarini and Helmer Strik (2020) Digital Eavesdropper – Acoustic Speech Characteristics as Markers of Exacerbations in COPD Patients. In: Proc. of the LREC-2020 workshop RaPID-3: Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data (RaPID).
o Loes van Bemmel, Wieke Harmsen, Catia Cucchiarini, Helmer Strik (2021) Automatic Selection of the Most Characterizing Features for Detecting COPD in Speech. In: Proc. of the 23rd International Conference on Speech and Computer, SPECOM 2021, St. Petersburg, Russia, September 27–30, 2021, pp. 737-748.
https://hdl.handle.net/2066/240818
https://repository.ubn.ru.nl/bitstream/handle/2066/240818/1/240818.pdf
o Loes van Bemmel (2021) Automatic selection of the most characterizing features for different types of atypical speech. Master’s Thesis, Data Science, Radboud University, Nijmegen.
o Venkata Srikanth Nallanthighal, Aki Härmä, and Helmer Strik (2022) Detection of COPD exacerbation from speech: comparison of acoustic features and deep learning based speech breathing models. In ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 9097–9101.
https://hdl.handle.net/2066/288187
https://repository.ubn.ru.nl/bitstream/handle/2066/288187/1/288187.pdf
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For all my publications see:
https://scholar.google.nl/citations?user=PuvTkHAAAAAJ&hl=en
https://www.researchgate.net/profile/Helmer_Strik/publications
https://repository.ubn.ru.nl/browse?authority=556e351686ea02bb77390237218ab252&type=author
There you can e.g. search for COPD or ‘pathological speech’.
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