Towards Identification of Hypomimia in Parkinson's Disease Based on Face Recognition Methods

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F18%3A00070351" target="_blank" >RIV/00159816:_____/18:00070351 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/65269705:_____/18:00070351 RIV/00216224:14110/18:00113819

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Towards Identification of Hypomimia in Parkinson's Disease Based on Face Recognition Methods

Popis výsledku v původním jazyce

Hypomimia manifested as an expressionless face with little or no sense of animation is a typical symptom of Parkinson&apos;s disease (PD). Although some researchers tried to quantify and diagnose the hypomimia based on the analysis of video-recordings, a study dealing with a possibility of its identification using the simple static face analysis is missing. The goal of this work is therefore to verify whether PD hypomimia can be detected even from static face images. For this purpose we enrolled 50 PD patients and 50 age-and gender-matched healthy controls. Parameterization based on face recognition methods in combination with conventional classifiers (random forests, XG-Boost, etc.) were used to automatically identify PD hypomimia. Among the classifiers, the decision tree algorithm achieved the best accuracy (67.33 %). The results suggest that automatic static face analysis can support PD hypomimia diagnosis, nevertheless is not accurate enough to outperform the approaches based on video-recordings processing.

Název v anglickém jazyce

Towards Identification of Hypomimia in Parkinson's Disease Based on Face Recognition Methods

Popis výsledku anglicky

Hypomimia manifested as an expressionless face with little or no sense of animation is a typical symptom of Parkinson&apos;s disease (PD). Although some researchers tried to quantify and diagnose the hypomimia based on the analysis of video-recordings, a study dealing with a possibility of its identification using the simple static face analysis is missing. The goal of this work is therefore to verify whether PD hypomimia can be detected even from static face images. For this purpose we enrolled 50 PD patients and 50 age-and gender-matched healthy controls. Parameterization based on face recognition methods in combination with conventional classifiers (random forests, XG-Boost, etc.) were used to automatically identify PD hypomimia. Among the classifiers, the decision tree algorithm achieved the best accuracy (67.33 %). The results suggest that automatic static face analysis can support PD hypomimia diagnosis, nevertheless is not accurate enough to outperform the approaches based on video-recordings processing.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

30502 - Other medical science

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

2018 10TH INTERNATIONAL CONGRESS ON ULTRA MODERN TELECOMMUNICATIONS AND CONTROL SYSTEMS AND WORKSHOPS (ICUMT 2018): EMERGING TECHNOLOGIES FOR CONNECTED SOCIETY

ISBN

978-1-5386-9360-5

ISSN

2157-0221

e-ISSN

neuvedeno

Počet stran výsledku

4

Strana od-do

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Název nakladatele

IEEE

Místo vydání

NEW YORK

Místo konání akce

Moscow

Datum konání akce

5. 11. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000459238500052