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

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU118975" target="_blank" >RIV/00216305:26220/16:PU118975 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Potential of Prosodic Features to Estimate Degree of Parkinson's disease severity
Original language description
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.
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 22nd Conference STUDENT EEICT 2016
ISBN
978-80-214-5350-0
ISSN
—
e-ISSN
—
Number of pages
5
Pages from-to
533-537
Publisher name
Neuveden
Place of publication
Brno
Event location
Brno
Event date
Apr 28, 2016
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
—

Similar results(10)