IDENTIFICATION OF PARKINSON’S DISEASE USING ACOUSTIC ANALYSIS OF POEM RECITATION

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F17%3APU123584" target="_blank" >RIV/00216305:26220/17:PU123584 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
IDENTIFICATION OF PARKINSON’S DISEASE USING ACOUSTIC ANALYSIS OF POEM RECITATION
Original language description
Parkinson’s disease (PD) is the second most frequent neurodegenerative disorder. It is estimated that 60–90% of PD patients suffer from speech disorder called hypokinetic dysarthria (HD). The goal of this work is to reveal influence of poem recitation on acoustic analysis of speech and propose concept of Parkinson’s disease identification based on this analysis. Classification methods used in this work are Random Forests and Support Vector Machine. The best achieved accuracy of disease identification is 70.66% with 59.25% sensitivity for Random Forests classifier fed mainly with articulation features. These results demonstrate a high potential of research in this area.
Czech name
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Czech description
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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
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 23nd Conference STUDENT EEICT 2017
ISBN
978-80-214-5496-5
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
619-623
Publisher name
Neuveden
Place of publication
Brno
Event location
Brno
Event date
Apr 27, 2017
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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