老年人在引导步行过程中的步态监测:一种集成的辅助机器人和可穿戴传感器方法

IF 3.4 Q2 ENGINEERING, BIOMEDICAL
Wearable technologies Pub Date : 2022-10-25 eCollection Date: 2022-01-01 DOI:10.1017/wtc.2022.23
Qingya Zhao, Zhuo Chen, Corey D Landis, Ashley Lytle, Ashwini K Rao, Damiano Zanotto, Yi Guo
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引用次数: 0

摘要

摘要积极的生活方式可以减轻老年人的身体衰退和认知障碍。老年人定期进行步行锻炼可以增强平衡,降低跌倒风险。在这篇文章中,我们提出了一项关于老年人在行走过程中步态监测的研究,该研究使用了一个包含辅助机器人和可穿戴传感器的集成系统。该系统将机器人板载红-绿-蓝+深度(RGB-D)传感器的数据与鞋垫中嵌入的惯性和压力传感器融合,并实时估计时空步态参数和动态稳定裕度。在社区中心收集的24名参与者的数据揭示了步态参数、身体表现(用短期身体表现电池评估)和认知能力(用蒙特利尔认知评估测量)之间的关联。研究结果验证了在实验室外条件下使用这种便携式系统的可行性,并将有助于设计未来技术增强的运动干预措施,以改善平衡、灵活性和力量,并有可能减少老年人的跌倒。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gait monitoring for older adults during guided walking: An integrated assistive robot and wearable sensor approach.

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.

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来源期刊
CiteScore
5.80
自引率
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