Chaussure

Résumé

Le terme chaussure désigne les vêtements destinés aux pieds, les protégeant du froid, de l'humidité, des aspérités du sol, etc. Il s'agit également d'un accessoire de mode qui vêt les femmes comme les hommes. Le terme chaussure dérive du verbe chausser, issu du latin calceare « mettre des souliers ». La plus vieille chaussure du monde, en écorce et découverte aux États-Unis, aurait plus de . La plus ancienne chaussure en cuir, un moccassin, a et a été découverte dans une grotte en Arménie. La forme des chaussures peut varier à l'infini, notamment en fonction de la mode et du statut social. La matière la plus couramment utilisée pour fabriquer les chaussures est le cuir. L'artisan spécialiste de la réparation des chaussures est le cordonnier, métier qui a fortement décliné dans les pays occidentaux. Description Semelle (chaussure)Semelle vignette|gauche|Diagramme des parties d'une chaussure masculine. Une chaussure se compose principalement du semelage, partie inférie

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https://fr.wikipedia.org/wiki/Chaussure

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Instrumented shoes for activity classification in the elderly

Kamiar Aminian, Anisoara Ionescu, Christopher Moufawad El Achkar

Quantifying daily physical activity in older adults can provide relevant monitoring and diagnostic information about risk of fall and frailty. In this study, we introduce instrumented shoes capable of recording movement and foot loading data unobtrusively throughout the day. Recorded data were used to devise an activity classification algorithm. Ten elderly persons wore the instrumented shoe system consisting of insoles inside the shoes and inertial measurement units on the shoes, and performed a series of activities of daily life as part of a semi-structured protocol. We hypothesized that foot loading, orientation, and elevation can be used to classify postural transitions, locomotion, and walking type. Additional sensors worn at the right thigh and the trunk were used as reference, along with an event marker. An activity classification algorithm was built based on a decision tree that incorporates rules inspired from movement biomechanics. The algorithm revealed excellent performance with respect to the reference system with an overall accuracy of 97% across all activities. The algorithm was also capable of recognizing all postural transitions and locomotion periods with elevation changes. Furthermore, the algorithm proved to be robust against small changes of tuning parameters. This instrumented shoe system is suitable for daily activity monitoring in elderly persons and can additionally provide gait parameters, which, combined with activity parameters, can supply useful clinical information regarding the mobility of elderly persons. (C) 2015 Elsevier B.V. All rights reserved.

Elsevier2016

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Activity level and gait parameters during daily life are important indicators for clinicians because they can provide critical insights into modifications of mobility and function over time. Wearable activity monitoring has been gaining momentum in daily life health assessment. Consequently, this study seeks to validate an algorithm for the classification of daily life activities and to provide a detailed gait analysis in older adults. A system consisting of an inertial sensor combined with a pressure sensing insole has been developed. Using an algorithm that we previously validated during a semi structured protocol, activities in 10 healthy elderly participants were recorded and compared to a wearable reference system over a 4 h recording period at home. Detailed gait parameters were calculated from inertial sensors. Dynamics of physical behavior were characterized using barcodes that express the measure of behavioral complexity. Activity classification based on the algorithm led to a 93% accuracy in classifying basic activities of daily life, i.e., sitting, standing, and walking. Gait analysis emphasizes the importance of metrics such as foot clearance in daily life assessment. Results also underline that measures of physical behavior and gait performance are complementary, especially since gait parameters were not correlated to complexity. Participants gave positive feedback regarding the use of the instrumented shoes. These results extend previous observations in showing the concurrent validity of the instrumented shoes compared to a body-worn reference system for daily-life physical behavior monitoring in older adults.

Mdpi Ag2016

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, ,

Activity monitoring in daily life is gaining momentum as a health assessment tool, especially in older adults and at-risk populations. Several research-based and commercial systems have been proposed with varying performances in classification accuracy. Configurations with many sensors are generally accurate but cumbersome, whereas single sensors tend to have lower accuracies. To this end, we propose an instrumented shoes system capable of accurate activity classification and gait analysis that contains sensors located entirely at the level of the shoes. One challenge in daily activity monitoring is providing punctual and subject-tailored feedback to improve mobility. Therefore, the instrumented shoe system was equipped with a Bluetooth (R) module to transmit data to a smartphone and perform detailed activity profiling of the monitored subjects. The potential applications of such a system are numerous in mobility and fall risk-assessment as well as in fall prevention.

Ios Press2016

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