Digital Biomarkers for Assessing Respiratory Disorders in Parkinson’s Disease
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Date
2023
Authors
Kováč, Daniel
Cvetler, Dominik
ORCID
Advisor
Referee
Mark
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Volume Title
Publisher
Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
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Abstract
Respiratory disorders are a significant part of hypokineticdysarthria (HD) that affects patients with Parkinson’sdisease (PD). Still, their potential role in the objective assessmentof HD has not yet been fully explored, which is the primary goalof this study. Several respiratory features were designed andextracted from acoustic signals recorded during text reading.Based on these features, the XGBoost model was able to predictclinical test scores of phonorespiration with an estimated errorrate of 12.54%. Statistical analysis revealed that measuring respirationrate and quantifying signal fluctuations during inspirationhave great potential in the objective assessment of respiratorydisorders in patients with PD.
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Citation
Proceedings II of the 29st Conference STUDENT EEICT 2023: Selected papers. s. 232-236. ISBN 978-80-214-6154-3
https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdf
https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdf
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Peer-reviewed
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en
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© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií