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多特征步态评分:一种评估步态质量的准确方法。

The Multifeature Gait Score: An accurate way to assess gait quality.

作者信息

Ben Mansour Khaireddine, Gorce Philippe, Rezzoug Nasser

机构信息

Handibio-EA4322-Université de Toulon, Toulon-Var, La Garde cedex, France.

出版信息

PLoS One. 2017 Oct 19;12(10):e0185741. doi: 10.1371/journal.pone.0185741. eCollection 2017.

Abstract

PURPOSE

This study introduces a novel way to accurately assess gait quality. This new method called Multifeature Gait Score (MGS) is based on the computation of multiple parameters characterizing six aspects of gait (temporal, amplitude, variability, regularity, symmetry and complexity) quantified with one inertial sensor. According to the aspects described, parameters were aggregated into partial scores to indicate the altered aspect in the case of abnormal patterns. In order to evaluate the overall gait quality, partial scores were averaged to a global score.

METHODS

The MGS was computed for 3 groups namely: healthy adult (10 subjects), sedentary elderly (11 subjects) and active elderly (20 subjects). Data were gathered from an inertial sensor located at the lumbar region during two sessions of 12m walking.

RESULTS

The results based on ANOVA and Tukey tests showed that the partial scores with the exception of those which describe the symmetry aspect were able to discriminate between groups (p<0.05). This significant difference was also confirmed by the global score which shows a significantly lower value for the sedentary elderly group (3.58 ±1.15) compared to the healthy adults (5.19 ±0.84) and active elderly (4.82 ±1.26). In addition, the intersession repeatability of the elaborated global score was excellent (ICC = 0.93, % SEM = 10.81).

CONCLUSION

The results obtained support the reliability and the relevance of the MGS as a novel method to characterize gait quality.

摘要

目的

本研究介绍一种准确评估步态质量的新方法。这种名为多特征步态评分(MGS)的新方法基于对多个参数的计算,这些参数表征了用一个惯性传感器量化的步态六个方面(时间、幅度、变异性、规律性、对称性和复杂性)。根据所描述的方面,将参数汇总为部分评分,以指示异常模式下改变的方面。为了评估整体步态质量,将部分评分平均为一个全局评分。

方法

计算了3组的MGS,即:健康成年人(10名受试者)、久坐不动的老年人(11名受试者)和活跃的老年人(20名受试者)。在两次12米步行过程中,从位于腰椎区域的惯性传感器收集数据。

结果

基于方差分析和Tukey检验的结果表明,除了描述对称性方面的评分外,其他部分评分能够区分不同组(p<0.05)。全局评分也证实了这一显著差异,该评分显示久坐不动的老年人组(3.58±1.15)的值明显低于健康成年人(5.19±0.84)和活跃的老年人(4.82±1.26)。此外,所制定的全局评分的组内重复性极佳(ICC = 0.93,% SEM = 10.81)。

结论

所获得的结果支持MGS作为一种表征步态质量的新方法的可靠性和相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70d4/5648116/c9cfe9ab5189/pone.0185741.g001.jpg

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