# Assessing Progress of Parkinson s Disease Using Acoustic Analysis of Phonation

arXiv: https://arxiv.org/abs/2203.09295 · HTML: https://mlsanity.com/paper/2203.09295/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Mar 2022.

## Built on by (most cited first, 1 of 1)

- [Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation](https://mlsanity.com/paper/2203.09880/) (2022)

## Abstract (arXiv)

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.