A Gait Analysis Method Based on a Depth Camera for Fall Prevention
Identifieur interne : 000982 ( Main/Exploration ); précédent : 000981; suivant : 000983A Gait Analysis Method Based on a Depth Camera for Fall Prevention
Auteurs : Amandine Dubois [France] ; François Charpillet [France]Source :
Abstract
This paper proposes a markerless system whose purpose is to help preventing falls of elderly people at home. To track human movements, the Microsoft Kinect camera is used which allows to acquire at the same time a RGB image and a depth image. Several articles show that the analysis of some gait parameters could allow fall risk assessment. We developed a system which extracts three gait parameters (the length and the duration of steps and the speed of the gait) by tracking the center of mass of the person. To check the validity of our system, the accuracy of the gait parameters obtained with the camera is evaluated. In an experiment, eleven subjects walked on an actimetric carpet, perpendicularly to the camera which filmed the scene. The three gait parameters obtained by the carpet are compared with those of the camera. In this study, four situations were tested to evaluate the robustness of our model. The subjects walked normally, making small steps, wearing a skirt and in front of the camera. The results showed that the system is accurate when there is one camera fixed perpendicularly. Thus we believe that the presented method is accurate enough to be used in real fall prevention applications.
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CS 25233 - 54052 Nancy cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-lorraine.fr/</ref></desc></org></tutelle><tutelle name="UMR7503" active="#struct-441569" type="indirect"><org type="institution" xml:id="struct-441569" status="VALID"><idno type="ISNI">0000000122597504</idno><idno type="IdRef">02636817X</idno><orgName>Centre National de la Recherche Scientifique</orgName><orgName type="acronym">CNRS</orgName><date type="start">1939-10-19</date><desc><address><country key="FR"></country></address><ref type="url">http://www.cnrs.fr/</ref></desc></org></tutelle></tutelles></hal:affiliation><country>France</country><placeName><settlement type="city">Nancy</settlement><settlement type="city">Metz</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Université de Lorraine</orgName></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">This paper proposes a markerless system whose purpose is to help preventing falls of elderly people at home. To track human movements, the Microsoft Kinect camera is used which allows to acquire at the same time a RGB image and a depth image. Several articles show that the analysis of some gait parameters could allow fall risk assessment. We developed a system which extracts three gait parameters (the length and the duration of steps and the speed of the gait) by tracking the center of mass of the person. To check the validity of our system, the accuracy of the gait parameters obtained with the camera is evaluated. In an experiment, eleven subjects walked on an actimetric carpet, perpendicularly to the camera which filmed the scene. The three gait parameters obtained by the carpet are compared with those of the camera. In this study, four situations were tested to evaluate the robustness of our model. The subjects walked normally, making small steps, wearing a skirt and in front of the camera. The results showed that the system is accurate when there is one camera fixed perpendicularly. Thus we believe that the presented method is accurate enough to be used in real fall prevention applications.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Metz</li><li>Nancy</li></settlement><orgName><li>Université de Lorraine</li></orgName></list><tree><country name="France"><region name="Grand Est"><name sortKey="Dubois, Amandine" sort="Dubois, Amandine" uniqKey="Dubois A" first="Amandine" last="Dubois">Amandine Dubois</name></region><name sortKey="Charpillet, Francois" sort="Charpillet, Francois" uniqKey="Charpillet F" first="François" last="Charpillet">François Charpillet</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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