Michalski Radosław, Wit Andrzej, Gajewski Jan
Institute of Sport, Warsaw, Poland.
Acta Bioeng Biomech. 2011;13(4):65-70.
The study attempts to assess gait symmetry based on measurement of vertical component of ground reaction force (GRF) in lower limbs. The aim of the study was to compare the results of gait classification obtained by means of artificial neural networks (ANN) and authors' own quantitative index method. Twenty male and twenty female physiotherapy students participated in the study. Measurements were carried out by means of the Kistler force plate. The profiles of GRF were analysed using ANN which classifies the cases under one of four groups of asymmetry based on suitably prepared training set. Author's own index method was employed for quantitative assessment of the degree of gait asymmetry. The analysis of our symmetry index revealed that the difference between the cases classified by the network as symmetrical and other asymmetrical profiles was significant (p<0.001), which suggests the conformity of both methods.
该研究试图基于下肢地面反作用力（GRF）垂直分量的测量来评估步态对称性。本研究的目的是比较通过人工神经网络（ANN）获得的步态分类结果与作者自己的定量指标方法的结果。20名男性和20名女性物理治疗专业学生参与了该研究。测量通过奇石乐测力板进行。使用ANN分析GRF曲线，该网络根据适当准备的训练集将病例分类为四组不对称中的一组。作者自己的指标方法用于步态不对称程度的定量评估。对我们的对称性指数的分析表明，网络分类为对称的病例与其他不对称曲线之间的差异具有显著性（p<0.001），这表明两种方法具有一致性。
