The MS Kinect Image and Depth Sensors Use for Gait Features Detection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F14%3A43897329" target="_blank" >RIV/60461373:22340/14:43897329 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216208:11150/14:10321892

Výsledek na webu

<a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7025460&queryText%3DThe+MS+Kinect+Image+and+Depth+Sensors+Use+for+Gait+Features+Detection" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7025460&queryText%3DThe+MS+Kinect+Image+and+Depth+Sensors+Use+for+Gait+Features+Detection</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICIP.2014.7025460" target="_blank" >10.1109/ICIP.2014.7025460</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The MS Kinect Image and Depth Sensors Use for Gait Features Detection

Popis výsledku v původním jazyce

Movement disorders, problems with motion and gait stability related to aging form a very intensively studied research area. The paper presents a contribution to these topics through the use of data acquired by motion sensors and namely image and depth sensors of the MS Kinect. While video sequences obtained by complex camera systems can be used for the precise gait features evaluation, it is possible to use much cheaper devices for diagnostic purposes accurate enough in many cases. The experimental partof the study presents video sequences and depth sensors data acquisition for 18 individuals with the Parkinson's disease and 18 healthy age-matched controls using the proposed graphical user interface in the clinical environment. Results presented include the estimation of gait features to distinguish gait disorders and to classify individuals in the early stage of possible serious diseases. The accuracy achieved was higher then 90 % for given sets of individuals.

Název v anglickém jazyce

The MS Kinect Image and Depth Sensors Use for Gait Features Detection

Popis výsledku anglicky

Movement disorders, problems with motion and gait stability related to aging form a very intensively studied research area. The paper presents a contribution to these topics through the use of data acquired by motion sensors and namely image and depth sensors of the MS Kinect. While video sequences obtained by complex camera systems can be used for the precise gait features evaluation, it is possible to use much cheaper devices for diagnostic purposes accurate enough in many cases. The experimental partof the study presents video sequences and depth sensors data acquisition for 18 individuals with the Parkinson's disease and 18 healthy age-matched controls using the proposed graphical user interface in the clinical environment. Results presented include the estimation of gait features to distinguish gait disorders and to classify individuals in the early stage of possible serious diseases. The accuracy achieved was higher then 90 % for given sets of individuals.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the IEEE 2014 International Conference on Image Processing

ISBN

978-1-4799-5751-4

ISSN

—

e-ISSN

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Počet stran výsledku

4

Strana od-do

2271-2274

Název nakladatele

IEEE Institute of Electrical and Electronics Engineers

Místo vydání

Piscataway, New Jersey

Místo konání akce

Paris

Datum konání akce

27. 10. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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