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Mesure de la fragilité et détection de chutes pour le maintien à domicile des personnes âgées

Abstract : Population ageing is a major issue for society in the next years, especially because of the increase of dependent people. The limits in specialized institutes capacity and the wish of the elderly to stay at home as long as possible explain a growing need for new specific at home services. Technologies can help securing the person at home by detecting falls. They can also help in the evaluation of the frailty for preventing future accidents. This work concerns the development of low cost ambient systems for helping the stay at home of elderly. Depth cameras allow analysing in real time the displacement of the person. We show that it is possible to recognize the activity of the person and to measure gait parameters from the analysis of simple feature extracted from depth images. Activity recognition is based on Hidden Markov Models and allows detecting at risk behaviours and falls. When the person is walking, the analysis of the trajectory of her centre of mass allows measuring gait parameters that can be used for frailty evaluation. This work is based on laboratory experimentations for the acquisition of data used for models training and for the evaluation of the results. We show that some of the developed Hidden Markov Models are robust enough for classifying the activities. We also evaluate de precision of the gait parameters measurement in comparison to the measures provided by an actimetric carpet. We believe that such a system could be installed in the home of the elderly because it relies on a local processing of the depth images. It would be able to provide daily information on the person activity and on the evolution of her gait parameters that are useful for securing her and evaluating her frailty
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Submitted on : Thursday, March 29, 2018 - 12:56:07 PM
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  • HAL Id : tel-01750835, version 1



Amandine Dubois. Mesure de la fragilité et détection de chutes pour le maintien à domicile des personnes âgées. Autre [cs.OH]. Université de Lorraine, 2014. Français. ⟨NNT : 2014LORR0095⟩. ⟨tel-01750835⟩



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