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使用惯性测量单元评估神经人群的时空步态参数。

Assessment of spatio-temporal gait parameters using inertial measurement units in neurological populations.

机构信息

Movement Science Group, School of Life Sciences, Oxford Brookes University, Oxford, UK.

出版信息

Gait Posture. 2011 Oct;34(4):558-60. doi: 10.1016/j.gaitpost.2011.06.018. Epub 2011 Jul 20.

Abstract

Laboratory based gait analysis techniques are expensive, time consuming and require technical expertise. Inertial measurement units can directly measure temporal parameters and in combination with gait models may provide a solution to obtain spatial gait measurements within daily clinical assessments. However it is not known if a model and standard correction factor determined by Zijlstra and Hof [8] to estimate step and stride length parameters in typically developed adults (TDA) can be accurately used in neurologically impaired gaits. This research estimated the stride length over two 10 m walks at self selected walking speed in people with neurological conditions, using a previously established model and correction factor for TDA. The relation of the correction factor to walking speed was explored. We recruited TDA (n=10) and participants with Parkinson's disease (PD; n=24), muscular dystrophy (MD; n=13), motor neuron disease (MND; n=7) and stroke survivors (n=18) for the study who twice walked 10 m at a self-selected pace. Stride length correction factors, for TDA (1.25±0.01), PD (1.25±0.03), and MD (1.21±0.08) (p=0.833 and p=0.242) were the same as previously reported in TDA (Zijlstra and Hof [8]). Correction factors for stroke (1.17±0.42) and MND (1.10±0.08) were different (p<0.01 and p=0.028 respectively). However there was a high level of variability for correction factors within groups, which did not relate to walking speed. Our findings support that correction factors should be determined for each individual to estimate average step/stride length in patients suffering from a neurological condition.

摘要

基于实验室的步态分析技术昂贵、耗时且需要技术专业知识。惯性测量单元可以直接测量时间参数,并结合步态模型,可能为在日常临床评估中获得空间步态测量提供解决方案。然而,尚不清楚 Zijlstra 和 Hof [8] 确定的模型和标准校正因子是否可以准确用于神经损伤步态,以估计典型发育成人(TDA)的步长和跨步参数。本研究使用先前为 TDA 建立的模型和校正因子,估计了神经功能障碍患者在自我选择的步行速度下两次进行的 10m 步行的跨步长度。研究人员还探讨了校正因子与步行速度的关系。我们招募了 TDA(n=10)和帕金森病(PD;n=24)、肌肉营养不良(MD;n=13)、运动神经元病(MND;n=7)和中风幸存者(n=18)的参与者进行研究,这些参与者两次以自我选择的速度走 10m。TDA(1.25±0.01)、PD(1.25±0.03)和 MD(1.21±0.08)的跨步长度校正因子(p=0.833 和 p=0.242)与之前在 TDA 中报道的结果相同(Zijlstra 和 Hof [8])。中风(1.17±0.42)和 MND(1.10±0.08)的校正因子则不同(p<0.01 和 p=0.028)。然而,各组内的校正因子存在高度的变异性,且与步行速度无关。我们的研究结果支持,应针对每个个体确定校正因子,以估计患有神经疾病的患者的平均步长/跨步长度。

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