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Contribution à la caractérisation de la locomotion des personnes hémiparétiques en situation écologique

Abstract : Clinical evaluation of stroke patients before and also after treatments is an essential step in gait rehabilitation. A 3D gait analysis system allows quantification of several parameters at each instant of walking. Nowadays, the 3D gait analysis system is used in clinical conditions which are different from daily life conditions. Indeed, the 3D gait analysis system, considered as a reference, can only be used at hospital. The absence of device usable in daily life situation constitutes a lack pointed out by clinical practitioners and was at the origin of this research. The objective of this thesis was to develop a wearable system that can measure the gait parameters of stroke patient in daily life situations. To do this, this thesis was devoted to the implementation of algorithms for joints angles estimation, to the design the electronics of the wearable movement sensors and the sensors’ firmware. In order to make the system optimized for stroke patients,a new algorithm for automatic partitioning data into gait cycles has been developed. Radio frequency rangefinders have been specially developed for this new algorithm. The wireless sensor system that we proposed is based on a distributed architecture. Its easy installation, compactness and light weight reduce their possible influence on patients’ gait. Different experiments had been carried out to evaluate with accuracy the joint angles, the precision of the sensor synchronization, the precision of the gait events detection and the robustness in the case of pathological walk. The gait parameters quantified by this new system are similar to those obtained with the 3D motion analysis system. The system shows good robustness when used in the case of pathological walking and the differences of results obtained with respectively the 3D motion analysis system and the proposed multi-sensor wireless system are limited. Once industrialized, it will be quite possible to use it to assess patients’ gait in daily life conditions.
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Submitted on : Wednesday, February 21, 2018 - 12:19:23 PM
Last modification on : Friday, October 9, 2020 - 9:51:37 AM
Long-term archiving on: : Tuesday, May 22, 2018 - 1:37:12 PM


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  • HAL Id : tel-01714176, version 1



Tong Li. Contribution à la caractérisation de la locomotion des personnes hémiparétiques en situation écologique. Médecine humaine et pathologie. Université Paris-Saclay, 2017. Français. ⟨NNT : 2017SACLV058⟩. ⟨tel-01714176⟩



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