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

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7025460&queryText%3DThe+MS+Kinect+Image+and+Depth+Sensors+Use+for+Gait+Features+Detection
Description	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 part of 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. 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 part of 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. (en)
Title	The MS Kinect Image and Depth Sensors Use for Gait Features Detection The MS Kinect Image and Depth Sensors Use for Gait Features Detection (en)
skos:prefLabel	The MS Kinect Image and Depth Sensors Use for Gait Features Detection The MS Kinect Image and Depth Sensors Use for Gait Features Detection (en)
skos:notation	RIV/60461373:22340/14:43897329!RIV15-MSM-22340___
http://linked.open...avai/riv/aktivita	V
http://linked.open...avai/riv/aktivity	V
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Schätz, Martin Procházka, Aleš Ťupa, Ondřej Yadollahi, Mohammadreza
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoká škola chemicko-technologická v Praze / Fakulta chemicko-inženýrská
http://linked.open...dnocenehoVysledku	30895
http://linked.open...ai/riv/idVysledku	RIV/60461373:22340/14:43897329
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Parkinson's disease; biomedical signal processing; classification; MS Kinect; gait recognition; threedimensional modeling; motion, image and depth sensors (en)
http://linked.open.../riv/klicoveSlovo	image and depth sensors threedimensional modeling MS Kinect Parkinson's disease classification motion biomedical signal processing gait recognition
http://linked.open...ontrolniKodProRIV	[75422BAC6795]
http://linked.open...v/mistoKonaniAkce	Paris
http://linked.open...i/riv/mistoVydani	Piscataway, New Jersey
http://linked.open...i/riv/nazevZdroje	Proceedings of the IEEE 2014 International Conference on Image Processing
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	4 (xsd:int)
http://linked.open...cetTvurcuVysledku	6 (xsd:int)
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Procházka, Aleš Vališ, Martin Vyšata, Oldřich Yadollahi, Mohammadreza Ťupa, Ondřej Schätz, Martin
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2014-10-27 (xsd:date)
number of pages	4 (xsd:int)
http://bibframe.org/vocab/doi	10.1109/ICIP.2014.7025460
http://purl.org/ne...btex#hasPublisher	IEEE Institute of Electrical and Electronics Engineers
https://schema.org/isbn	978-1-4799-5751-4
http://localhost/t...ganizacniJednotka	22340

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