Publication detail

Potential of Prosodic Features to Estimate Degree of Parkinson's disease severity

GALÁŽ, Z.

Original Title

Potential of Prosodic Features to Estimate Degree of Parkinson's disease severity

English Title

Potential of Prosodic Features to Estimate Degree of Parkinson's disease severity

Type

conference paper

Language

en

Original Abstract

This paper deals with non-invasive and objective Parkinson's disease (PD) severity estimation. For this purpose, prosodic speech features expressing monopitch, monoloudness, and speech rate abnormalities were extracted from recordings of stress-modified reading task acquired from 72 patients with idiopathic PD. Using a single feature regression (esimating values of subjective clinical rating scales) with classification and regression algorithm, following performance in terms of root mean squared error was achieved: 10.72 (UPDRS III), 2.16 (UPDRS IV), 4.76 (FOG-Q), 17.89 (NMSS), 2.13 (RBDSQ), 6.43 (ACE-R), 1.41 (MMSE), and 4.82 (BDI). These results show a promising potential of prosodic speech features in the field of objective assessment of PD severity.

English abstract

This paper deals with non-invasive and objective Parkinson's disease (PD) severity estimation. For this purpose, prosodic speech features expressing monopitch, monoloudness, and speech rate abnormalities were extracted from recordings of stress-modified reading task acquired from 72 patients with idiopathic PD. Using a single feature regression (esimating values of subjective clinical rating scales) with classification and regression algorithm, following performance in terms of root mean squared error was achieved: 10.72 (UPDRS III), 2.16 (UPDRS IV), 4.76 (FOG-Q), 17.89 (NMSS), 2.13 (RBDSQ), 6.43 (ACE-R), 1.41 (MMSE), and 4.82 (BDI). These results show a promising potential of prosodic speech features in the field of objective assessment of PD severity.

Keywords

Parkinson's disease, hypokinetic dysarthria, dysprosody, objective assessment

Released

21.04.2016

Location

Brno

ISBN

978-80-214-5350-0

Book

Proceedings of the 22nd Conference STUDENT EEICT 2016

Pages from

533

Pages to

537

Pages count

5

BibTex


@inproceedings{BUT124429,
  author="Zoltán {Galáž}",
  title="Potential of Prosodic Features to Estimate Degree of Parkinson's disease severity",
  annote="This paper deals with non-invasive and objective Parkinson's disease (PD) severity estimation. For this purpose, prosodic speech features expressing monopitch, monoloudness, and speech rate abnormalities were extracted from recordings of stress-modified reading task acquired from 72 patients with idiopathic PD. Using a single feature regression (esimating values of subjective clinical rating scales) with classification and regression algorithm, following performance in terms of root mean squared error was achieved: 10.72 (UPDRS III), 2.16 (UPDRS IV), 4.76 (FOG-Q), 17.89 (NMSS), 2.13 (RBDSQ), 6.43 (ACE-R), 1.41 (MMSE), and 4.82 (BDI). These results show a promising potential of prosodic speech features in the field of objective assessment of PD severity.",
  booktitle="Proceedings of the 22nd Conference STUDENT EEICT 2016",
  chapter="124429",
  howpublished="electronic, physical medium",
  year="2016",
  month="april",
  pages="533--537",
  type="conference paper"
}