Identification Of Patients At The Risk Of Lewy Body Diseases Based On Acoustic Analysis Of Speech
but.event.date | 25.04.2019 | cs |
but.event.title | Student EEICT 2019 | cs |
dc.contributor.author | FernándezMartínez, Andrea | |
dc.date.accessioned | 2020-04-16T07:19:26Z | |
dc.date.available | 2020-04-16T07:19:26Z | |
dc.date.issued | 2019 | cs |
dc.description.abstract | Lewy body diseases (LBDs) is a group of neurodegenerative diseases that consists of Parkinson’s disease and dementia with Lewy bodies, that are generally very crucial to be diagnosed in their prodromal state. In the frame of this study we proposed a multivariate logistic regression model that identifies people in a high risk of LBDs based on their articulatory and prosodic characteristics. More specifically, the model has 80 % specificity and 85 % sensitivity based on quantification of rigidity of tongue/jaw, monoloudness, and inappropriate pausing. | en |
dc.format | text | cs |
dc.format.extent | 50-53 | cs |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Proceedings of the 25st Conference STUDENT EEICT 2019. s. 50-53. ISBN 978-80-214-5735-5 | cs |
dc.identifier.isbn | 978-80-214-5735-5 | |
dc.identifier.uri | http://hdl.handle.net/11012/186615 | |
dc.language.iso | en | cs |
dc.publisher | Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
dc.relation.ispartof | Proceedings of the 25st Conference STUDENT EEICT 2019 | 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 | Lewy body diseases | en |
dc.subject | Parkinson’s disease | en |
dc.subject | dementia with Lewy bodies | en |
dc.subject | speech | en |
dc.subject | voice | en |
dc.subject | acoustic analysis | en |
dc.subject | prodromal diagnosis | en |
dc.title | Identification Of Patients At The Risk Of Lewy Body Diseases Based On Acoustic Analysis Of Speech | 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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