Speech Acoustic Markers Can Detect Mild Cognitive Impairment in Parkinson's Disease
- 1Department of Neurology, Boston Medical Center, Boston, MA 02118 USA.
- 2Massachusetts Institute of Technology Lincoln Laboratories, Lexington, MA 02421 USA.
- 3Massachusetts Institute of Technology Lincoln Laboratories, Lexington, MA 02421 USA, and also with the Speech and Hearing Bioscience and Technology Program, Harvard Medical School, Cambridge, MA 02115 USA.
- 0Department of Neurology, Boston Medical Center, Boston, MA 02118 USA.
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View abstract on PubMed
Summary
This summary is machine-generated.Researchers identified distinct speech acoustic features linked to mild cognitive impairment in Parkinson's disease (PD-MCI). These biomarkers, particularly from picture descriptions, show promise for developing new tools to detect and monitor PD-MCI.
Area Of Science
- Neurology
- Speech Science
- Biomarker Discovery
Background
- Speech biomarkers are established for Parkinson's disease (PD) motor symptoms.
- Biomarkers for mild cognitive impairment in PD (PD-MCI) remain understudied.
Purpose Of The Study
- Identify speech acoustic features associated with PD-MCI.
- Develop and evaluate a model to differentiate PD-MCI from cognitively normal PD (PD-NC) individuals.
Main Methods
- Analyzed speech samples from 42 PD participants classified as PD-MCI or PD-NC.
- Extracted acoustic features from reading and picture description tasks.
- Utilized Gaussian mixture models (GMMs) for classification.
Main Results
- Picture description tasks yielded more PD-MCI-associated acoustic features than reading tasks.
- A fused GMM model achieved an AUC of 0.82 for discriminating PD-MCI from PD-NC.
- Associated acoustic features involved multiple speech subsystems.
Conclusions
- PD-MCI exhibits a unique speech acoustic signature.
- These findings support the development of novel tools for PD-MCI detection and monitoring.
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