The MS Kinect Image and Depth Sensors Use for Gait Features Detection
The result's identifiers
Result code in 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>
Alternative codes found
RIV/00216208:11150/14:10321892
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
The MS Kinect Image and Depth Sensors Use for Gait Features Detection
Original language 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 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.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
—
Result continuities
Project
—
Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the IEEE 2014 International Conference on Image Processing
ISBN
978-1-4799-5751-4
ISSN
—
e-ISSN
—
Number of pages
4
Pages from-to
2271-2274
Publisher name
IEEE Institute of Electrical and Electronics Engineers
Place of publication
Piscataway, New Jersey
Event location
Paris
Event date
Oct 27, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—