A New Modality for Quantitative Evaluation of Parkinson's Disease: In-Air Movement

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F13%3APU109976" target="_blank" >RIV/00216305:26220/13:PU109976 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/BIBE.2013.6701692" target="_blank" >http://dx.doi.org/10.1109/BIBE.2013.6701692</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/BIBE.2013.6701692" target="_blank" >10.1109/BIBE.2013.6701692</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A New Modality for Quantitative Evaluation of Parkinson's Disease: In-Air Movement

Popis výsledku v původním jazyce

Parkinsons disease (PD) is neurodegenerative disorder with very high prevalence rate occurring mainly among elderly. One of the most typical symptoms of PD is deterioration of handwriting that is usually the first manifestation of Parkinsons disease. Inthis study, a new modality - in-air trajectory during handwriting - is proposed to efficiently diagnose PD. Experimental results showed that analysis of in-air trajectories is capable of assessing subtle motor abnormalities that are connected with PD. Moreover, conjunction of in-air trajectories with conventional on-surface handwriting allows us to build predictive model with PD classification accuracy over 80%. In total, we compute over 600 handwriting features. Then, we select smaller subset of thesefeatures using two feature selection algorithms: Mann-Whitney U-test filter and relief algorithm, and map these feature subsets to binary classification response using support vector machines.

Název v anglickém jazyce

A New Modality for Quantitative Evaluation of Parkinson's Disease: In-Air Movement

Popis výsledku anglicky

Parkinsons disease (PD) is neurodegenerative disorder with very high prevalence rate occurring mainly among elderly. One of the most typical symptoms of PD is deterioration of handwriting that is usually the first manifestation of Parkinsons disease. Inthis study, a new modality - in-air trajectory during handwriting - is proposed to efficiently diagnose PD. Experimental results showed that analysis of in-air trajectories is capable of assessing subtle motor abnormalities that are connected with PD. Moreover, conjunction of in-air trajectories with conventional on-surface handwriting allows us to build predictive model with PD classification accuracy over 80%. In total, we compute over 600 handwriting features. Then, we select smaller subset of thesefeatures using two feature selection algorithms: Mann-Whitney U-test filter and relief algorithm, and map these feature subsets to binary classification response using support vector machines.

Druh

D - Stať ve sborníku

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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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)

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

2013 IEEE 13TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE)

ISBN

978-1-4799-3163-7

ISSN

—

e-ISSN

—

Počet stran výsledku

4

Strana od-do

1-4

Název nakladatele

IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA

Místo vydání

NEW YORK, NY 10017 USA

Místo konání akce

Chania

Datum konání akce

10. 11. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000335217700166