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This summary is machine-generated.

Vocal biomarkers show promise for tracking Parkinson's disease progression. While many speech features change, long-term temporal data is limited, highlighting the need for further research in this area.

Keywords:
Parkinson’s diseasemonitoringprogressionvocal features

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Area of Science:

  • Neurology
  • Speech-Language Pathology
  • Biomedical Engineering

Background:

  • Parkinson's disease (PD) significantly alters vocal characteristics, presenting potential biomarkers for disease monitoring.
  • Understanding the temporal evolution of these vocal biomarkers is crucial for effective disease progression tracking.

Purpose of the Study:

  • To identify commonly used vocal features for Parkinson's disease monitoring.
  • To analyze the temporal changes of these vocal features throughout disease progression.

Main Methods:

  • Systematic online database search for studies on voice and speech changes in Parkinson's disease.
  • Analysis of identified vocal features and their temporal variations to establish trends.

Main Results:

  • Eighteen vocal features were identified, categorized into articulation, phonation, and prosody.
  • Twelve features showed significant variations in Parkinsonian voices compared to controls.
  • Limited insights into long-term temporal changes were observed.

Conclusions:

  • Vocal features effectively differentiate Parkinsonian voices and can potentially monitor disease progression.
  • Long-term temporal changes in vocal biomarkers for Parkinson's disease are underexplored.
  • Further long-term studies are needed to provide clinical insights and improve automated voice-based monitoring.