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Journal Article

Citation

Zhao Q, Chen Z, Landis CD, Lytle A, Rao AK, Zanotto D, Guo Y. Wearable Technol. 2022; 3: e28.

Copyright

(Copyright © 2022, Cambridge University Press)

DOI

10.1017/wtc.2022.23

PMID

38486898

PMCID

PMC10936390

Abstract

An active lifestyle can mitigate physical decline and cognitive impairment in older adults. Regular walking exercises for older individuals result in enhanced balance and reduced risk of falling. In this article, we present a study on gait monitoring for older adults during walking using an integrated system encompassing an assistive robot and wearable sensors. The system fuses data from the robot onboard Red Green Blue plus Depth (RGB-D) sensor with inertial and pressure sensors embedded in shoe insoles, and estimates spatiotemporal gait parameters and dynamic margin of stability in real-time. Data collected with 24 participants at a community center reveal associations between gait parameters, physical performance (evaluated with the Short Physical Performance Battery), and cognitive ability (measured with the Montreal Cognitive Assessment). The results validate the feasibility of using such a portable system in out-of-the-lab conditions and will be helpful for designing future technology-enhanced exercise interventions to improve balance, mobility, and strength and potentially reduce falls in older adults.


Language: en

Keywords

assistive robot; cognitive assessment; dynamic margin of stability; gait analysis; instrumented footwear

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