Assessing progress of Parkinson's disease using acoustic analysis of phonation

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Authors

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.

Year of publication 2015
Type Article in Proceedings
Conference 4th International Work Conference on Bio-Inspired Intelligence, IWOBI 2015
MU Faculty or unit

Central European Institute of Technology

Citation
Web http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7160153
Doi http://dx.doi.org/10.1109/IWOBI.2015.7160153
Field Neurology, neurosurgery, neurosciences
Keywords Biodiversity; Conservation; Decision trees; Intelligent systems; Neurodegenerative diseases; Patient rehabilitation; Speech Acoustic analysis;
Description 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
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