Department of Industrial Engineering, Tsinghua University, Beijing, China.
Geriatr Gerontol Int. 2018 Sep;18(9):1366-1371. doi: 10.1111/ggi.13492. Epub 2018 Aug 14.
Smart bracelets are popular today. Based on their built-in motion sensors, they can serve as a cost-effective method of gait assessment in home-based care. Few studies have applied smart bracelets in the gait assessment of older Chinese adults. The present study aimed to: (i) establish reference gait parameters of older Chinese adults using smart bracelets under single and dual task; and (ii) explore the differences in gait parameters among non-frail and pre-frail Chinese older adults.
A total of 50 community-dwelling older Chinese adults aged ≥50 years wore a smart bracelet sensor in the L3 region of the back and underwent a 10-m walking test under single- and dual-task conditions. Participants were preliminarily classified into non-frail and pre-frail groups based on the Fatigue, Resistance, Ambulation, Illnesses and Loss of Weight scale. Gait parameters including average walking speed, step frequency, root mean square (RMS), acceleration amplitude variability, step variability, step regularity and step symmetry were calculated based on the data exported from the bracelet.
Multivariate analysis of covariance (mancova) analysis showed that older adults had significantly decreased speed and step frequency (P < 0.05) under the dual cognitive task condition. Pre-frail older adults showed significantly decreased speed, mediolateral RMS, vertical RMS, anteroposterior RMS, vertical amplitude variability and vertical step regularity compared with non-frail older adults (P < 0.05).
The present study suggested that the decline in gait parameters as a result of frailty could be detected by the smart bracelet sensor. Geriatr Gerontol Int 2018; 18: 1366-1371.
智能手环如今很流行。基于其内置的运动传感器，它们可以成为家庭护理中评估步态的一种具有成本效益的方法。很少有研究将智能手环应用于中国老年人的步态评估中。本研究旨在：（i）使用智能手环在单任务和双任务条件下建立中国老年人的参考步态参数；（ii）探索无虚弱和衰弱前期中国老年人之间步态参数的差异。
共有 50 名年龄≥50 岁、居住在社区的中国老年人在背部 L3 区佩戴智能手环传感器，并在单任务和双任务条件下进行 10m 步行测试。根据疲劳、抵抗力、活动能力、疾病和体重减轻量表，初步将参与者分为无虚弱和衰弱前期组。基于从手环导出的数据，计算平均步行速度、步频、均方根（RMS）、加速度幅度变异性、步变异性、步规则性和步对称性等步态参数。
协方差多元分析（manova）分析显示，老年人在双认知任务条件下速度和步频显著降低（P<0.05）。与无虚弱老年人相比，衰弱前期老年人的速度、横向 RMS、垂直 RMS、前后 RMS、垂直振幅变异性和垂直步规则性明显降低（P<0.05）。
本研究表明，智能手环传感器可以检测到因虚弱而导致的步态参数下降。老年医学与老年病学国际 2018；18:1366-1371.
