ArticleFrontiers in psychology2023
Vowel production: a potential speech biomarker for early detection of dysarthria in Parkinson's disease.
Article in Frontiers in psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 13 citations in OpenAlex.
- A Machine Learning Approach to Voice-Based Parkinson Disease Screening Using Multiview Spectrogram and Speech Recognition Features: Diagnostic Study.JMIR medical informatics · 2026Article
- Aerodynamic and Acoustic Characteristics of Nasal Airflow in Parkinson's Disease.Journal of speech, language, and hearing research : JSLHR · 2026Article
- Longitudinal Evaluation of Dysarthria Progression in Patients with Parkinson's Disease.Diagnostics (Basel, Switzerland) · 2026Article
- Speech and Language Changes During Rapid Eye Movement (REM) Sleep with Potential Diagnostic Markers: A Systematic Review.Brain sciences · 2026Review
- Comparing token-based and trajectory-based vowel space metrics for assessing speech in Parkinson's disease.PloS one · 2026Article
- Speech Markers of Parkinson's Disease: Phonological Features and Acoustic Measures.Brain sciences · 2025Article
- Vocal Feature Changes for Monitoring Parkinson's Disease Progression-A Systematic Review.Brain sciences · 2025Review
- Variability in Vowel Space in Parkinson's Disease: Associations With Cognitive and Motor Impairment.Journal of speech, language, and hearing research : JSLHR · 2024Article
- Article
- Consensus-Based Definitions for Vocal Biomarkers: The International VOCAL Initiative.Digital biomarkersArticle
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: Our aim is to detect early, subclinical speech biomarkers of dysarthria in Parkinson's disease (PD), i.e., systematic atypicalities in speech that remain subtle, are not easily detectible by the clinician, so that the patient is labeled "non-dysarthric." Based on promising exploratory work, we examine here whether vowel articulation, as assessed by three acoustic metrics, can be used as early indicator of speech difficulties associated with Parkinson's disease. Study design: This is a prospective case-control study. Methods: Sixty-three individuals with PD and 35 without PD (healthy controls-HC) participated in this study. Out of 63 PD patients, 43 had been diagnosed with dysarthria (DPD) and 20 had not (NDPD). Sustained vowels were recorded for each speaker and formant frequencies were measured. The analyses focus on three acoustic metrics: individual vowel triangle areas (tVSA), vowel articulation index (VAI) and the Phi index. Results: tVSA were found to be significantly smaller for DPD speakers than for HC. The VAI showed significant differences between these two groups, indicating greater centralization and lower vowel contrasts in the DPD speakers with dysarhtria. In addition, DPD and NDPD speakers had lower Phi values, indicating a lower organization of their vowel system compared to the HC. Results also showed that the VAI index was the most efficient to distinguish between DPD and NDPD whereas the Phi index was the best acoustic metric to discriminate NDPD and HC. Conclusion: This acoustic study identified potential subclinical vowel-related speech biomarkers of dysarthria in speakers with Parkinson's disease who have not been diagnosed with dysarthria.
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