Universität zu Köln

Thies, Tabea ORCID: 0000-0001-9149-3143, Mallick, Elisa, Tröger, Johannes, Baykara, Ebru, Mücke, Doris ORCID: 0000-0002-6217-3121 and Barbe, Michael T. ORCID: 0000-0003-1149-8054 (2025). Automatic speech analysis combined with machine learning reliably predicts the motor state in people with Parkinson’s disease. npj Parkinson's Disease, 11. pp. 1-7. Springer Nature. ISSN 2373-8057

PDF s41531-025-00959-4.pdf Bereitstellung unter der CC-Lizenz: Creative Commons Attribution. Download (818kB)

Abstract

[Artikel-Nr.: 105] It is still under debate whether levodopa treatment improves speech functions in Parkinson’s disease (PD). Therefore, speech functions of people with PD were compared in medication-OFF condition (withdrawal of PD medication for at least 12 h) and medication-ON condition (after receiving 200 mg of soluble levodopa). A total of 78 participants, including 51 males and 27 females, performed predefined standard speech tasks. Acoustic speech features were automatically extracted with the algorithm given by the Dysarthria Analyzer. Results suggest that acute levodopa intake improves phonatory- respiratory speech functions and speech planning abilities, while the articulatory system remains unaffected. Furthermore, the study provided preliminary evidence that speech function is able to predict the medication status in individuals with PD as the constructed speech-based biomarker score did not only correlate with established measures of (speech) motor impairment but could also differentiate between the medication OFF and ON status. A post-hoc machine learning model yielded similar results.

Item Type:	Article
Creators:	Creators Email ORCID ORCID Put Code Thies, Tabea UNSPECIFIED https://orcid.org/0000-0001-9149-3143 UNSPECIFIED Mallick, Elisa UNSPECIFIED UNSPECIFIED UNSPECIFIED Tröger, Johannes UNSPECIFIED UNSPECIFIED UNSPECIFIED Baykara, Ebru UNSPECIFIED UNSPECIFIED UNSPECIFIED Mücke, Doris doris.muecke@uni-koeln.de https://orcid.org/0000-0002-6217-3121 UNSPECIFIED Barbe, Michael T. UNSPECIFIED https://orcid.org/0000-0003-1149-8054 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-788405
Identification Number:	10.1038/s41531-025-00959-4
Journal or Publication Title:	npj Parkinson's Disease
Volume:	11
Page Range:	pp. 1-7
Number of Pages:	7
Date:	2025
Publisher:	Springer Nature
ISSN:	2373-8057
Language:	English
Faculty:	Collaborative Research Centers Faculty of Arts and Humanities Faculty of Medicine
Divisions:	Faculty of Medicine > Neurologie > Klinik und Poliklinik für Neurologie Faculty of Arts and Humanities > Fächergruppe 1: Kunstgeschichte, Musikwissenschaft, Medienkultur und Theater, Linguistik, Digital Humanities > Institut für Linguistik (IfL) > Abteilung für Phonetik (PHO) Collaborative Research Centers > CRC 1252: Prominence in Language
Subjects:	Social sciences Language, Linguistics Medical sciences Medicine
['eprint_fieldname_oa_funders' not defined]:	Publikationsfonds UzK
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/78840