Year: 2025
Type: article
Study design: Observational Study
Abstract: Background Delineation of Parkinson's disease (PD) from multiple system atrophy (MSA) can be challenging in early disease stages. Speech characteristics have been studied as digital biomarkers in PD and ataxias. Currently, data on speech in MSA is limited. Objectives To determine whether speech characteristics can serve as a digital biomarker to differentiate between MSA and PD. Methods Twenty‐one MSA patients and 23 PD patients underwent a battery of speech assessments: text reading, sustained phonation and diadochokinetic tasks. Speech characteristics were extracted using the software, Praat. Results MSA and PD speech can be described by three meaningful factors. MSA speech exhibited more reading pauses, higher pitch variability, prolonged syllables, and a more irregular speech rhythm, allowing differentiation from PD with a ROC‐AUC of 0.89. Speech characteristics were correlated with motor impairment and disease severity. Conclusion MSA can be differentiated from PD with good accuracy using speech analysis.
DOI: 10.1002/mdc3.70094
Authors: Tom Hähnel, Anna Nemitz, Katja Schön, Luise Berger, Annemarie Vogel, Doreen Gruber, Nils Schnalke, Stefan Bräuer, Björn H. Falkenburger, Florin Gandor
Language: English
Topic: Voice and Speech Disorders
Subfield: Speech and Hearing
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,400
Funder: Macquarie University
OpenAlex ID: W4410059632