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Parkinson’s disease glottal flow characterization: Phonation features vs amplitude distributions

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU136735" target="_blank" >RIV/00216305:26220/20:PU136735 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://www.scitepress.org/Link.aspx?doi=10.5220%2f0009189403590368" target="_blank" >https://www.scitepress.org/Link.aspx?doi=10.5220%2f0009189403590368</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.5220/0009189403590368" target="_blank" >10.5220/0009189403590368</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Parkinson’s disease glottal flow characterization: Phonation features vs amplitude distributions

  • Popis výsledku v původním jazyce

    The study of speech and voice in people diagnosed with a neurodegenerative disorder for the purposes of detection and monitoring has known a very relevant push forward in these last years, but it is far from being completed. One of the main concerns nowadays is that once the deterioration of speech and phonation quality has been informed by machine learning relying upon clinical expertise, there is insufficient evidence to resolve if quality deterioration may come from organic causes, neuromotor degeneration or simply from aging. The present work is part of a more ambitious plan to shed light on this problem by resorting to a theoretical modelling of glottal signals under the main known causes affecting phonation quality, which are closure deficits during the phonation cycle. These deficits may be due to anatomical, organic pathologic or neuromotor reasons. Simulation examples explaining them in the glottal excitation signals are given and contrasted with real examples. Finally, relevant scores from an experimental separation of Parkinson Disease phonation samples from 24 male and 24 female subjects against aging 24 male and 24 female controls on the same age taken from a male-female balanced dataset confronted to a normative subset of 24 male and 24 female speakers are presented to exemplify an analysis study deepening into this problem. Although classification accuracy scores as high as 99.69 and 99.59 were attained in 10-fold cross-validation using an SVM classifier, there is still the impression that co-morbidity and aging effects are not well taken into account, requiring a further semantic study on the features behind the discrimination scores obtained.

  • Název v anglickém jazyce

    Parkinson’s disease glottal flow characterization: Phonation features vs amplitude distributions

  • Popis výsledku anglicky

    The study of speech and voice in people diagnosed with a neurodegenerative disorder for the purposes of detection and monitoring has known a very relevant push forward in these last years, but it is far from being completed. One of the main concerns nowadays is that once the deterioration of speech and phonation quality has been informed by machine learning relying upon clinical expertise, there is insufficient evidence to resolve if quality deterioration may come from organic causes, neuromotor degeneration or simply from aging. The present work is part of a more ambitious plan to shed light on this problem by resorting to a theoretical modelling of glottal signals under the main known causes affecting phonation quality, which are closure deficits during the phonation cycle. These deficits may be due to anatomical, organic pathologic or neuromotor reasons. Simulation examples explaining them in the glottal excitation signals are given and contrasted with real examples. Finally, relevant scores from an experimental separation of Parkinson Disease phonation samples from 24 male and 24 female subjects against aging 24 male and 24 female controls on the same age taken from a male-female balanced dataset confronted to a normative subset of 24 male and 24 female speakers are presented to exemplify an analysis study deepening into this problem. Although classification accuracy scores as high as 99.69 and 99.59 were attained in 10-fold cross-validation using an SVM classifier, there is still the impression that co-morbidity and aging effects are not well taken into account, requiring a further semantic study on the features behind the discrimination scores obtained.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    20204 - Robotics and automatic control

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/NV16-30805A" target="_blank" >NV16-30805A: Efekt neinvazivní stimulace mozku na hypokinetickou dysartrii, mikrografii a mozkovou plasticitu u pacientů s Parkinsonovou nemocí</a><br>

  • Návaznosti

    S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2020

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: SERPICO

  • ISBN

    978-989-758-398-8

  • ISSN

  • e-ISSN

  • Počet stran výsledku

    10

  • Strana od-do

    359-368

  • Název nakladatele

    Neuveden

  • Místo vydání

    Neuveden

  • Místo konání akce

    Valletta, Malta

  • Datum konání akce

    24. 2. 2020

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku

    000571477000045