Potential of Prosodic Features to Estimate Degree of Parkinson's Disease Severity
| but.event.date | 28.04.2016 | cs |
| but.event.title | Student EEICT 2016 | cs |
| dc.contributor.author | Galáž, Zoltán | |
| dc.date.accessioned | 2018-07-10T12:48:19Z | |
| dc.date.available | 2018-07-10T12:48:19Z | |
| dc.date.issued | 2016 | cs |
| dc.description.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. | en |
| dc.format | text | cs |
| dc.format.extent | 533-537 | cs |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Proceedings of the 22nd Conference STUDENT EEICT 2016. s. 533-537. ISBN 978-80-214-5350-0 | cs |
| dc.identifier.isbn | 978-80-214-5350-0 | |
| dc.identifier.uri | http://hdl.handle.net/11012/83990 | |
| dc.language.iso | en | cs |
| dc.publisher | Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
| dc.relation.ispartof | Proceedings of the 22nd Conference STUDENT EEICT 2016 | en |
| dc.relation.uri | http://www.feec.vutbr.cz/EEICT/ | cs |
| dc.rights | © Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
| dc.rights.access | openAccess | en |
| dc.subject | Parkinson’s disease | en |
| dc.subject | hypokinetic dysarthria | en |
| dc.subject | dysprosody | en |
| dc.subject | objective assessment | en |
| dc.title | Potential of Prosodic Features to Estimate Degree of Parkinson's Disease Severity | en |
| dc.type.driver | conferenceObject | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
| eprints.affiliatedInstitution.department | Fakulta elektrotechniky a komunikačních technologií | cs |
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