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@inproceedings{1323791,
author = {Mekyska, J. and Galaz, Z. and Mzourek, Z. and Smékal, Z. and Rektorová, Irena and Eliášová, Ilona and Košťálová, Milena and Mračková, Martina and Beránková, Dagmar and FaundezandZanuy, M. and Lópezanddeand Ipina, K. and AlonsoandHernandez, Jesus B.},
address = {neuveden},
booktitle = {4th International Work Conference on Bio-Inspired Intelligence, IWOBI 2015},
doi = {http://dx.doi.org/10.1109/IWOBI.2015.7160153},
editor = {Alonso-Hernandez J.B.; Travieso-Gonzalez C.M.; Lopez de Ipina K.},
keywords = {Biodiversity; Conservation; Decision trees; Intelligent systems; Neurodegenerative diseases; Patient rehabilitation; Speech Acoustic analysis;},
howpublished = {tištěná verze "print"},
language = {eng},
location = {neuveden},
isbn = {978-1-4799-6174-0},
pages = {111-118},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
title = {Assessing progress of Parkinson's disease using acoustic analysis of phonation},
url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7160153},
year = {2015}
}
TY - JOUR
ID - 1323791
AU - Mekyska, J. - Galaz, Z. - Mzourek, Z. - Smékal, Z. - Rektorová, Irena - Eliášová, Ilona - Košťálová, Milena - Mračková, Martina - Beránková, Dagmar - Faundez-Zanuy, M. - López-de- Ipina, K. - Alonso-Hernandez, Jesus B.
PY - 2015
TI - Assessing progress of Parkinson's disease using acoustic analysis of phonation
PB - Institute of Electrical and Electronics Engineers Inc.
CY - neuveden
SN - 9781479961740
KW - Biodiversity
KW - Conservation
KW - Decision trees
KW - Intelligent systems
KW - Neurodegenerative diseases
KW - Patient rehabilitation
KW - Speech Acoustic analysis;
UR - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7160153
L2 - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7160153
N2 - This paper deals with a complex acoustic analysis of phonation in patients with Parkinson's disease (PD) with a special focus on estimation of disease progress that is described by 7 different clinical scales (e. g. Unified Parkinson's disease rating scale or Beck depression inventory). The analysis is based on parametrization of 5 Czech vowels pronounced by 84 PD patients. Using classification and regression trees we estimated all clinical scores with maximal error lower or equal to 13 %. Best estimation was observed in the case of Mini-mental state examination (MAE = 0.77, estimation error 5.50 %). Finally, we proposed a binary classification based on random forests that is able to identify Parkinson's disease with sensitivity SEN = 92.86% (SPE = 85.71 %). The parametrization process was based on extraction of 107 speech features quantifying different clinical signs of hypokinetic dysarthria present in PD
ER -
MEKYSKA, J., Z. GALAZ, Z. MZOUREK, Z. SMÉKAL, Irena REKTOROVÁ, Ilona ELIÁŠOVÁ, Milena KOŠŤÁLOVÁ, Martina MRAČKOVÁ, Dagmar BERÁNKOVÁ, M. FAUNDEZ-ZANUY, K. LÓPEZ-DE- IPINA and Jesus B. ALONSO-HERNANDEZ. Assessing progress of Parkinson's disease using acoustic analysis of phonation. In Alonso-Hernandez J.B.; Travieso-Gonzalez C.M.; Lopez de Ipina K. \textit{4th International Work Conference on Bio-Inspired Intelligence, IWOBI 2015}. neuveden: Institute of Electrical and Electronics Engineers Inc., 2015, p.~111-118. ISBN~978-1-4799-6174-0. Available from: https://dx.doi.org/10.1109/IWOBI.2015.7160153.
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