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Digital Biomarkers for Assessing Respiratory Disorders in 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%3APU148594" target="_blank" >RIV/00216305:26220/23:PU148594 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdf" target="_blank" >https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_2_v2.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.13164/eeict.2023.232" target="_blank" >10.13164/eeict.2023.232</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Digital Biomarkers for Assessing Respiratory Disorders in Parkinson’s Disease

  • Original language description

    Respiratory disorders are a significant part of hypokinetic dysarthria (HD) that affects patients with Parkinson’s disease (PD). Still, their potential role in the objective assessment of HD has not yet been fully explored, which is the primary goal of this study. Several respiratory features were designed and extracted from acoustic signals recorded during text reading. Based on these features, the XGBoost model was able to predict clinical test scores of phonorespiration with an estimated error rate of 12.54%. Statistical analysis revealed that measuring respiration rate and quantifying signal fluctuations during inspiration have great potential in the objective assessment of respiratory disorders in patients with PD.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

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 II of the 29st Conference STUDENT EEICT 2023: Selected papers

  • ISBN

    978-80-214-6154-3

  • ISSN

    2788-1334

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    232-236

  • Publisher name

    Brno University of Technology, Faculty of Elektronic Engineering and Communication

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    Apr 25, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article