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

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Abstract

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.

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Notes

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Acknowledgements

The authors would like to acknowledge the financial contribution of the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canadian Foundation for Innovation (CFI). Also, the authors would like to thank all participants, without them, this work would not have been possible.

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Authors and Affiliations

  1. Laboratoire d’Intelligence Ambiante pour la Reconnaissance d’Activités, Université du Québec à Chicoutimi, Québec, Canada

    Kévin Chapron, Kévin Bouchard & Sébastien Gaboury

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  1. Kévin Chapron
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  2. Kévin Bouchard
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  3. Sébastien Gaboury
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Correspondence to Kévin Chapron.

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Chapron, K., Bouchard, K. & Gaboury, S. Real-time gait speed evaluation at home in a multi residents context. Multimed Tools Appl 80, 12931–12949 (2021). https://doi.org/10.1007/s11042-020-08962-y

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