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Real-time gait speed evaluation at home in a multi residents context

Chapron Kévin, Bouchard Kévin et Gaboury Sébastien. (2020). Real-time gait speed evaluation at home in a multi residents context. Multimedia Tools and Applications,

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In recent years, the aging of the population has attracted considerable attention in the scientific community. An important fact is an increasing number of senior people will suffer from cognitive decline and there is almost no existing way to detect it early without the intervention of a clinician. Indeed, the sooner the cognitive decline is detected, the professional can elaborate a more adequate strategy to slow it down. In fact, Mild Cognitive Impairments (MCI) have been strongly correlated to a decreasing gait speed over the time. However, it would take a lot of human resources to carry out a standardized walking speed test every year to follow the evolution of this one. In fact, it is unthinkable in the current context of healthcare economics scarcity, thus finding a way of measuring it automatically at home could be a promising solution. This ambient sensor should be able to measure the gait speed of an inhabitant and automatically associate it to the right resident in a multi-resident context. In this paper, we present a new prototype to monitor gait speed continuously at home non intrusively. When coupled with a wristband capable of communicating through BLE, the gait speed can then be associated with the right person in a multi-resident context. The proposed prototype was tested in a realistic smart home context and results obtained are very encouraging.

Type de document:Article publié dans une revue avec comité d'évaluation
Version évaluée par les pairs:Oui
Identifiant unique:10.1007/s11042-020-08962-y
Sujets:Sciences naturelles et génie > Sciences mathématiques > Informatique
Département, module, service et unité de recherche:Départements et modules > Département d'informatique et de mathématique
Mots-clés:gait speed evaluation, smart home, speed sensor, multi resident identification, wearable sensors
Déposé le:10 févr. 2021 19:37
Dernière modification:10 févr. 2021 19:37
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