基于传感器的日常行走特征分析：衰弱前期/衰弱评估的新范例。
Sensor-based characterization of daily walking: a new paradigm in pre-frailty/frailty assessment.
机构信息
Department of Biomedical Engineering, University of Arizona, Tucson, AZ, USA.
Arizona Center on Aging, Department of Medicine, University of Arizona, Tucson, AZ, USA.
出版信息
BMC Geriatr. 2020 May 6;20(1):164. doi: 10.1186/s12877-020-01572-1.
BACKGROUND
Frailty is a highly recognized geriatric syndrome resulting in decline in reserve across multiple physiological systems. Impaired physical function is one of the major indicators of frailty. The goal of this study was to evaluate an algorithm that discriminates between frailty groups (non-frail and pre-frail/frail) based on gait performance parameters derived from unsupervised daily physical activity (DPA).
METHODS
DPA was acquired for 48 h from older adults (≥65 years) using a tri-axial accelerometer motion-sensor. Continuous bouts of walking for 20s, 30s, 40s, 50s and 60s without pauses were identified from acceleration data. These were then used to extract qualitative measures (gait variability, gait asymmetry, and gait irregularity) and quantitative measures (total continuous walking duration and maximum number of continuous steps) to characterize gait performance. Association between frailty and gait performance parameters was assessed using multinomial logistic models with frailty as the dependent variable, and gait performance parameters along with demographic parameters as independent variables.
RESULTS
One hundred twenty-six older adults (44 non-frail, 60 pre-frail, and 22 frail, based on the Fried index) were recruited. Step- and stride-times, frequency domain gait variability, and continuous walking quantitative measures were significantly different between non-frail and pre-frail/frail groups (p < 0.05). Among the five different durations (20s, 30s, 40s, 50s and 60s), gait performance parameters extracted from 60s continuous walks provided the best frailty assessment results. Using the 60s gait performance parameters in the logistic model, pre-frail/frail group (vs. non-frail) was identified with 76.8% sensitivity and 80% specificity.
DISCUSSION
Everyday walking characteristics were found to be associated with frailty. Along with quantitative measures of physical activity, qualitative measures are critical elements representing the early stages of frailty. In-home gait assessment offers an opportunity to screen for and monitor frailty.
TRIAL REGISTRATION
The clinical trial was retrospectively registered on June 18th, 2013 with ClinicalTrials.gov, identifier NCT01880229.
背景
衰弱是一种高度公认的老年综合征，导致多个生理系统储备能力下降。身体功能受损是衰弱的主要指标之一。本研究的目的是评估一种基于无监督日常身体活动（DPA）中获取的步态表现参数来区分衰弱组（非衰弱和衰弱前期/衰弱）的算法。
方法
使用三轴加速度计运动传感器从老年人（≥65 岁）中采集 48 小时的 DPA。从加速数据中识别出连续 20s、30s、40s、50s 和 60s 无停顿的步行小段。然后，这些小段被用于提取定性测量（步态变异性、步态不对称和步态不规则）和定量测量（总连续步行时间和最大连续步数），以表征步态表现。使用衰弱作为因变量，步态表现参数和人口统计学参数作为自变量的多项逻辑模型评估衰弱与步态表现参数之间的关联。
结果
共招募了 126 名老年人（根据 Fried 指数，44 名非衰弱，60 名衰弱前期，22 名衰弱）。步幅和步频、频域步态变异性以及连续行走的定量测量在非衰弱和衰弱前期/衰弱组之间存在显著差异（p<0.05）。在五个不同的时间段（20s、30s、40s、50s 和 60s）中，从 60s 连续行走中提取的步态表现参数提供了最佳的衰弱评估结果。使用逻辑模型中的 60s 步态表现参数，将衰弱前期/衰弱组（与非衰弱组相比）识别的灵敏度为 76.8%，特异性为 80%。
讨论
发现日常行走特征与衰弱有关。除了身体活动的定量测量外，定性测量也是代表衰弱早期阶段的关键因素。家庭步态评估为筛查和监测衰弱提供了机会。
试验注册
该临床试验于 2013 年 6 月 18 日在 ClinicalTrials.gov 上进行了回顾性注册，标识符为 NCT01880229。
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