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Assessing Movement of Articulatory Organs in Patients with Parkinson’s Disease

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU148893" target="_blank" >RIV/00216305:26220/23:PU148893 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1_v2.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1_v2.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Assessing Movement of Articulatory Organs in Patients with Parkinson’s Disease

  • Original language description

    Hypokinetic dysarthria is a motor speech disorder often present during Parkinson’s disease. It affects the speech system, including articulatory abilities. There are several speech parameters describing this domain, so it is suggested to deal with their mutual comparison. This work aims to design and describe an algorithm for calculating the parameters of articulation, adapted for the Czech language, and then compare their discriminative power. The acoustic analysis of speech included in it is done via the Praat program and basic machine learning algorithms such as Expectation-Maximization, K-means and linear regression are used for the subsequent data processing. The Mann-Whitney U test, descriptive statistics and Random Forest machine learning model using cross-validation and balanced accuracy is used for evaluation. The results are scripts for automatic assessment of vowel space area, for calculating articulation parameters and for their evaluation. The outputs of the analysis of speech recording database prove that differences in articulation can indeed be observed between normal and dysarthric speech. Based on the mutual comparison of results, it is therefore proposed in the work which parameters are being appropriate for further dealing with this issue.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

    <a href="/en/project/NU20-04-00294" target="_blank" >NU20-04-00294: Diagnostics of Lewy body diseases in prodromal stage based on multimodal data analysis</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings I of the 28th Conference STUDENT EEICT 2022 General papers

  • ISBN

    978-80-214-6029-4

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    243-246

  • Publisher name

    Brno University of Technology, Faculty of Electrical Engineering and Communication

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    Apr 26, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article