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使用 G-STRIDE 足部安装惯性传感器评估老年人跌倒情况。

Assessing falls in the elderly population using G-STRIDE foot-mounted inertial sensor.

机构信息

Department of Geriatrics, Foundation for Research and Biomedical Innovation of the Infanta Sofía Hospital (HUIS), Madrid, 28702, Spain.

Spanish National Research Council, Centre for Automation and Robotics (CAR), CSIC-UPM, Arganda del Rey, 28500, Spain.

出版信息

Sci Rep. 2023 Jun 6;13(1):9208. doi: 10.1038/s41598-023-36241-x.

Abstract

Falls are one of the main concerns in the elderly population due to their high prevalence and associated consequences. Guidelines for the management of the elder with falls are comprised of multidimensional assessments, especially gait and balance. Daily clinical practice needs for timely, effortless, and precise tools to assess gait. This work presents the clinical validation of the G-STRIDE system, a 6-axis inertial measurement unit (IMU) with onboard processing algorithms, that allows the calculation of walking-related metrics correlated with clinical markers of fall risk. A cross-sectional case-control study was conducted with 163 participants (falls and non-falls groups). All volunteers were assessed with clinical scales and conducted a 15-min walking test at a self-selected pace while wearing the G-STRIDE. G-STRIDE is a low-cost solution to facilitate the transfer to society and clinical evaluations. It is open hardware and flexible and, thus, has the advantage of providing runtime data processing. Walking descriptors were derived from the device, and a correlation analysis was conducted between walking and clinical variables. G-STRIDE allowed measuring walking parameters in non-restricted walking conditions (e.g. hallway). Walking parameters statistically discriminate between falls and non-falls groups. We found good/excellent estimation accuracy (ICC = 0.885; [Formula: see text]) for walking speed, showing good/excellent correlation between gait speed and several clinical variables. G-STRIDE can calculate walking-related metrics that allow for discrimination between falls and non-falls groups, which correlates with clinical indicators of fall risk. A preliminary fall-risk assessment based on the walking parameters was found to improve the Timed Up and Go test in the identification of fallers.

摘要

跌倒在老年人中是一个主要关注点,因为其发病率高且相关后果严重。老年人跌倒管理指南包括多维评估,尤其是步态和平衡。日常临床实践需要及时、轻松且精准的工具来评估步态。本研究介绍了 G-STRIDE 系统的临床验证,该系统是一种带有板载处理算法的 6 轴惯性测量单元 (IMU),可计算与跌倒风险的临床标志物相关的行走相关指标。一项横断面病例对照研究纳入了 163 名参与者(跌倒组和非跌倒组)。所有志愿者都接受了临床量表评估,并在佩戴 G-STRIDE 时以自我选择的速度进行了 15 分钟的步行测试。G-STRIDE 是一种低成本解决方案,可促进向社会和临床评估的转移。它是开源硬件,灵活且具有实时数据处理的优势。从设备中提取了行走描述符,并对行走和临床变量进行了相关分析。G-STRIDE 允许在不受限制的行走条件下(例如走廊)测量行走参数。行走参数可在跌倒组和非跌倒组之间进行统计学区分。我们发现行走速度的估计精度较好/非常好(ICC = 0.885;[公式:见正文]),表明步态速度与多个临床变量之间具有良好/非常好的相关性。G-STRIDE 可以计算行走相关指标,以区分跌倒组和非跌倒组,这些指标与跌倒风险的临床指标相关。基于行走参数的初步跌倒风险评估被发现可提高计时起立行走测试对跌倒者的识别能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b08/10244449/6a6646d3e4a4/41598_2023_36241_Fig1_HTML.jpg

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