Assessing Progress of Parkinson s Disease Using Acoustic Analysis of Phonation
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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 of Mini-mental state examination (MAE = 0.77, estimation error 5.50 we proposed a binary classification based on random forests that is able to identify Parkinson's disease with sensitivity SEN = 92.86 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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