■步态是检测轻度认知障碍(MCI)和阿尔茨海默病(AD)的潜在诊断工具。然而,很少注意步行过程中的手臂运动,目前在步态不对称问题上还没有达成共识。因此,在这项研究中,我们的目的是确定是否可以利用手臂运动和步态不对称来识别MCI和AD.
■总共,102名中老年人被纳入最终分析,并被分配到以下三组:AD(n=27),MCI(n=35),和正常对照组(n=40)。对所有参与者进行步态和认知评估。步态检测包括具有自由速度行走的单任务步态和双任务步态,并在行走中添加连续负7的认知任务。使用具有MATRIX系统2.0的可穿戴设备收集原始步态参数。通过使用带有varimax旋转的主成分提取的因子分析,将步态参数缩短为几个主要的步态域。随后,提取的步态域用于区分三组,并计算受试者工作特性曲线下的面积。
■单任务步态的因子分析确定了五个独立的步态域:节律对称性,节奏,步调不对称,手臂运动,和可变性。双任务步态的因素分析确定了四个步态域:节律,可变性,对称性,和手臂运动。在单任务行走中,步速不对称性与MoCA评分呈负相关,可以区分AD组与其他两组。手臂运动与MoCA评分无关,并且在任何一项任务中都没有表现出足够的歧视。
■目前,没有可靠的证据表明手臂运动可用于识别AD或MCI.步态不对称性可作为辅助诊断AD而非MCI的潜在步态标志物。
UNASSIGNED: Gait is a potential diagnostic tool for detecting mild cognitive impairment (MCI) and Alzheimer\'s disease (AD). Nevertheless, little attention has been paid to arm movements during walking, and there is currently no consensus on gait
asymmetry. Therefore, in this
study, we aimed to determine whether arm motion and gait
asymmetry could be utilized for identifying MCI and AD.
UNASSIGNED: In total, 102 middle-aged and elderly individuals were included in the final analysis and were assigned to the following three groups: AD (n = 27), MCI (n = 35), and a normal control group (n = 40). Gait and cognitive assessments were conducted for all participants. Gait detection included a single-task gait with free-speed walking and a dual-task gait with adding a cognitive task of successive minus seven to walking. Original gait parameters were collected using a wearable device featuring the MATRIX system 2.0. Gait parameters were shortened to several main gait domains through factor analysis using principal component extraction with varimax rotation. Subsequently, the extracted gait domains were used to differentiate the three groups, and the area under the receiver operating characteristic curve was calculated.
UNASSIGNED: Factor analysis of single-task gait identified five independent gait domains: rhythm symmetry, rhythm, pace
asymmetry, arm motion, and variability. Factor analysis of the dual-task gait identified four gait domains: rhythm, variability, symmetry, and arm motion. During single-task walking, pace
asymmetry was negatively correlated with MoCA scores and could distinguish between the AD group and the other two groups. Arm motion was not associated with MoCA scores, and did not exhibit adequate discrimination in either task.
UNASSIGNED: Currently, there is no reliable evidence suggesting that arm motion can be used to recognize AD or MCI. Gait
asymmetry can serve as a potential gait marker for the auxiliary diagnosis of AD but not for MCI.