Towards an affordable mobile analysis platform for pathological walking assessment

Vincent Bonnet 1 Christine Azevedo Coste 2 Lionel Lapierre 3 Jennifer Cadic 4 Philippe Fraisse 5 René Zapata 3 Gentiane Venture 1 Christian Geny 6
2 DEMAR - Artificial movement and gait restoration
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
3 EXPLORE - Robotique mobile pour l'exploration de l'environnement
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
5 IDH - Interactive Digital Humans
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : This paper proposes an affordable mobile platform for pathological gait analysis. Gait spatio-temporal parameters are of great importance in clinical evaluation but often require expensive equipment and are limited to a small and controlled environment. The proposed system uses state-of-the art robotic tools, in contrast to their original use, for the development of a robust low-cost diagnostic decision-making tool. The mobile system, which is driven by a Kinect sensor, is able to (1) follow a patient at a constant distance on his own defined path, and (2) to estimate the gait spatio-temporal parameters. The Robust Tracking-Learning-Detection algorithm estimates the positions of the targets attached to the trunk and heels of the patient. Real-condition experimental validation including the corridor, occlusion cases, and illumination changes was performed. A gold standard stereophotogrammetric system was also used and showed good tracking of the patient and an accuracy in the stride length estimate of 2%. Finally, preliminary results showed an RMS error that was below 10°in the 3D lower-limb joint angle estimates during walking on a treadmill.
Type de document :
Article dans une revue
Robotics and Autonomous Systems, Elsevier, 2015, 66, pp.116-128. 〈10.1016/j.robot.2014.12.002〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01348662
Contributeur : Isabelle Gouat <>
Soumis le : lundi 25 juillet 2016 - 14:09:30
Dernière modification le : jeudi 24 mai 2018 - 15:59:24

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Vincent Bonnet, Christine Azevedo Coste, Lionel Lapierre, Jennifer Cadic, Philippe Fraisse, et al.. Towards an affordable mobile analysis platform for pathological walking assessment. Robotics and Autonomous Systems, Elsevier, 2015, 66, pp.116-128. 〈10.1016/j.robot.2014.12.002〉. 〈lirmm-01348662〉

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