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MUCHA, J.
Original Title
IDENTIFICATION OF PARKINSON’S DISEASE USING ACOUSTIC ANALYSIS OF POEM RECITATION
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
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.
English abstract
Keywords
poem recitation, acoustic analysis, binary classification, Parkinson’s disease, hypokinetic dysarthria
Key words in English
Authors
RIV year
2018
Released
27.04.2017
Location
Brno
ISBN
978-80-214-5496-5
Book
Proceedings of the 23nd Conference STUDENT EEICT 2017
Pages from
619
Pages to
623
Pages count
5
BibTex
@inproceedings{BUT135620, author="Ján {Mucha}", title="IDENTIFICATION OF PARKINSON’S DISEASE USING ACOUSTIC ANALYSIS OF POEM RECITATION", booktitle="Proceedings of the 23nd Conference STUDENT EEICT 2017", year="2017", pages="619--623", address="Brno", isbn="978-80-214-5496-5" }