A Gait Analysis Method Based on a Depth Camera for Fall Prevention

Amandine Dubois 1 François Charpillet 1
1 MAIA - Autonomous intelligent machine
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
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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Communication dans un congrès
The 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Aug 2014, Chicago, United States. 2014
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Dernière modification le : jeudi 11 janvier 2018 - 06:25:23
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Amandine Dubois, François Charpillet. A Gait Analysis Method Based on a Depth Camera for Fall Prevention. The 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Aug 2014, Chicago, United States. 2014. 〈hal-01069640〉

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