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步态受损的中风幸存者跌倒风险的生物力学关联

Biomechanical Correlates of Falls Risk in Gait Impaired Stroke Survivors.

作者信息

Nagano Hanatsu, Said Catherine M, James Lisa, Sparrow William A, Begg Rezaul

机构信息

Institute for Health and Sports (IHeS), Victoria University, Melbourne, VIC, Australia.

Department of Physiotherapy, Melbourne School of Health Sciences, University of Melbourne, Melbourne, VIC, Australia.

出版信息

Front Physiol. 2022 Mar 7;13:833417. doi: 10.3389/fphys.2022.833417. eCollection 2022.

Abstract

Increased falls risk is prevalent among stroke survivors with gait impairments. Tripping is the leading cause of falls and it is highly associated with mid-swing Minimum Foot Clearance (MFC), when the foot's vertical margin from the walking surface is minimal. The current study investigated MFC characteristics of post-stroke individuals ( = 40) and healthy senior controls ( = 21) during preferred speed treadmill walking, using an Optotrak 3D motion capture system to record foot-ground clearance. In addition to MFC, bi-lateral spatio-temporal gait parameters, including step length, step width and double support time, were obtained for the post-stroke group's Unaffected and Affected limb and the control group's Dominant and Non-dominant limbs. Statistical analysis of MFC included central tendency (mean, median), step-to-step variability (standard deviation and interquartile range) and distribution (skewness and kurtosis). In addition, the first percentile, that is the lowest 1% of MFC values (MFC 1%) were computed to identify very high-risk foot trajectory control. Spatio-temporal parameters were described using the mean and standard deviation with a 2 × 2 (Group × Limb) Multivariate Analysis of Variance applied to determine significant Group and Limb effects. Pearson's correlations were used to reveal any interdependence between gait variables and MFC control. The main finding of the current research was that post-stroke group's affected limb demonstrated lower MFC 1% with higher variability and lower kurtosis. Post-stroke gait was also characterised by shorter step length, larger step width and increased double support time. Gait retraining methods, such as using real-time biofeedback, would, therefore, be recommended for post-stroke individuals, allowing them to acquire optimum swing foot control and reduce their tripping risk by elevating the swing foot and improving step-to-step consistency in gait control.

摘要

步态受损的中风幸存者中,跌倒风险增加的情况很普遍。绊倒 是跌倒的主要原因,并且与摆动中期最小足间隙(MFC)高度相关,此时足部与行走表面的垂直距离最小。本研究使用Optotrak 3D运动捕捉系统记录足部与地面的间隙,调查了中风后个体(n = 40)和健康老年对照组(n = 21)在偏好速度的跑步机行走过程中的MFC特征。除了MFC,还获取了中风后组的健侧和患侧肢体以及对照组的优势侧和非优势侧肢体的双侧时空步态参数,包括步长、步宽和双支撑时间。MFC的统计分析包括集中趋势(均值、中位数)、步间变异性(标准差和四分位距)和分布(偏度和峰度)。此外,计算了第一百分位数,即MFC值最低的1%(MFC 1%),以识别极高风险的足部轨迹控制。时空参数用均值和标准差描述,并应用2×2(组×肢体)多变量方差分析来确定显著的组效应和肢体效应。使用Pearson相关性来揭示步态变量与MFC控制之间的任何相互依赖关系。本研究的主要发现是,中风后组的患侧肢体表现出较低的MFC 1%,变异性较高且峰度较低。中风后步态的特征还包括步长较短、步宽较大和双支撑时间增加。因此,建议对中风后个体采用步态再训练方法,如使用实时生物反馈,使他们能够获得最佳的摆动足控制,并通过抬高摆动足和提高步态控制中的步间一致性来降低绊倒风险。

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