Contribution of different handwriting modalities to differential diagnosis of Parkinson's Disease

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F15%3APU114697" target="_blank" >RIV/00216305:26220/15:PU114697 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/MeMeA.2015.7145225" target="_blank" >http://dx.doi.org/10.1109/MeMeA.2015.7145225</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/MeMeA.2015.7145225" target="_blank" >10.1109/MeMeA.2015.7145225</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Contribution of different handwriting modalities to differential diagnosis of Parkinson's Disease

Popis výsledku v původním jazyce

In this paper, we evaluate the contribution of different handwriting modalities to the diagnosis of Parkinson's disease. We analyse on-surface movement, in-air movement and pressure exerted on the tablet surface. Especially in-air movement and pressure-based features have been rarely taken into account in previous studies. We show that pressure and in-air movement also possess information that is relevant for the diagnosis of Parkinson's Disease (PD) from handwriting. In addition to the conventional kinematic and spatio-temporal features, we present a group of the novel features based on entropy and empirical mode decomposition of the handwriting signal. The presented results indicate that handwriting can be used as biomarker for PD providing classification performance around 89% area under the ROC curve (AUC) for PD classification.

Název v anglickém jazyce

Contribution of different handwriting modalities to differential diagnosis of Parkinson's Disease

Popis výsledku anglicky

In this paper, we evaluate the contribution of different handwriting modalities to the diagnosis of Parkinson's disease. We analyse on-surface movement, in-air movement and pressure exerted on the tablet surface. Especially in-air movement and pressure-based features have been rarely taken into account in previous studies. We show that pressure and in-air movement also possess information that is relevant for the diagnosis of Parkinson's Disease (PD) from handwriting. In addition to the conventional kinematic and spatio-temporal features, we present a group of the novel features based on entropy and empirical mode decomposition of the handwriting signal. The presented results indicate that handwriting can be used as biomarker for PD providing classification performance around 89% area under the ROC curve (AUC) for PD classification.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

Medical Measurements and Applications (MeMeA), 2015 IEEE International Symposium on

ISBN

978-1-4799-6476-5

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

344-348

Název nakladatele

Neuveden

Místo vydání

Neuveden

Místo konání akce

Turín

Datum konání akce

7. 5. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000380610600064