Morris Rosie, Hickey Aodhán, Del Din Silvia, Godfrey Alan, Lord Sue, Rochester Lynn
Institute of Neuroscience/Newcastle University Institute of Ageing, Clinical Ageing Research Unit, Campus for Ageing and Vitality Newcastle University, Newcastle upon Tyne, United Kingdom.
Institute of Neuroscience/Newcastle University Institute of Ageing, Clinical Ageing Research Unit, Campus for Ageing and Vitality Newcastle University, Newcastle upon Tyne, United Kingdom.
Gait Posture. 2017 Feb;52:68-71. doi: 10.1016/j.gaitpost.2016.11.024. Epub 2016 Nov 16.
Gait is a marker of global health, cognition and falls risk. Gait is complex, comprised of multiple characteristics sensitive to survival, age and pathology. Due to covariance amongst characteristics, conceptual gait models have been established to reduce redundancy and aid interpretation. Previous models have been derived from laboratory gait assessments which are costly in equipment and time. Body-worn monitors (BWM) allow for free-living, low-cost and continuous gait measurement and produce similar covariant gait characteristics. A BWM gait model from both controlled and free-living measurement has not yet been established, limiting utility.
103 control and 67 PD participants completed a controlled laboratory assessment; walking for two minutes around a circuit wearing a BWM. 89 control and 58 PD participants were assessed in free-living, completing normal activities for 7 days wearing a BWM. Fourteen gait characteristics were derived from the BWM, selected according to a previous model. Principle component analysis derived factor loadings of gait characteristics.
Four gait domains were derived for both groups and conditions; pace, rhythm, variability and asymmetry. Domains totalled 84.84% and 88.43% of variance for controlled and 90.00% and 93.03% of variance in free-living environments for control and PD participants respectively. Gait characteristic loading was unambiguous for all characteristics apart from gait variability which demonstrated cross-loading for both groups and environments. The model was highly congruent with the original model.
The conceptual gait models remained stable using a BWM in controlled and free-living environments. The model became more discrete supporting utility of the gait model for free-living gait.
步态是整体健康、认知和跌倒风险的一个指标。步态很复杂,由多个对生存、年龄和病理状况敏感的特征组成。由于这些特征之间存在协方差,因此已经建立了概念性步态模型以减少冗余并有助于解释。先前的模型是从实验室步态评估中推导出来的,这在设备和时间方面成本很高。穿戴式身体监测器(BWM)可实现自由活动状态下的低成本连续步态测量,并产生类似的协变步态特征。尚未建立来自受控和自由活动测量的BWM步态模型,这限制了其效用。
103名对照参与者和67名帕金森病(PD)参与者完成了一次受控实验室评估;佩戴BWM在一个环形路线上行走两分钟。89名对照参与者和58名PD参与者在自由活动状态下接受评估,佩戴BWM进行7天的正常活动。根据先前的模型从BWM中提取了14个步态特征。主成分分析得出步态特征的因子载荷。
两组在两种情况下都得出了四个步态域;步速、节奏、变异性和不对称性。对于对照参与者和PD参与者,在受控环境中,这些域分别占方差的84.84%和88.43%,在自由活动环境中分别占方差的90.00%和93.03%。除了步态变异性外,所有特征的步态特征载荷都是明确的,步态变异性在两组和两种环境中都表现出交叉载荷。该模型与原始模型高度一致。
在受控和自由活动环境中使用BWM时,概念性步态模型保持稳定。该模型变得更加离散,支持了步态模型在自由活动步态中的效用。