Inoue Jun, Kawamura Kazuya, Fujie Masakatsu G
Graduate School of Science and Engineering, Waseda University, Japan.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:6446-50. doi: 10.1109/EMBC.2012.6347470.
In the present paper, we examine the appropriateness of a new model to examine the activity of the foot in gait. We developed an estimation model for foot-ankle muscular activity in the design of an ankle-foot orthosis by means of a statistical method. We chose three muscles for measuring muscular activity and built a Bayesian network model to confirm the appropriateness of the estimation model. We experimentally examined the normal gait of a non-disabled subject. We measured the muscular activity of the lower foot muscles using electromyography, the joint angles, and the pressure on each part of the sole. From these data, we obtained the causal relationship at every 10% level for these factors and built models for the stance phase, control term, and propulsive term. Our model has three advantages. First, it can express the influences that change during gait because we use 10% level nodes for each factor. Second, it can express the influences of factors that differ for low and high muscular-activity levels. Third, we created divided models that are able to reflect the actual features of gait. In evaluating the new model, we confirmed it is able to estimate all muscular activity level with an accuracy of over 90%.
在本文中，我们研究了一种用于检查步态中足部活动的新模型的适用性。我们通过统计方法在踝足矫形器设计中开发了一种用于估计足踝肌肉活动的模型。我们选择了三块肌肉来测量肌肉活动，并构建了一个贝叶斯网络模型以确认估计模型的适用性。我们通过实验研究了一名非残疾受试者的正常步态。我们使用肌电图、关节角度和鞋底各部位的压力来测量足部下部肌肉的活动。从这些数据中，我们获得了这些因素在每10%水平上的因果关系，并为站立期、控制项和推进期建立了模型。我们的模型有三个优点。首先，它可以表达步态过程中变化的影响，因为我们对每个因素使用10%水平的节点。其次，它可以表达低肌肉活动水平和高肌肉活动水平下不同因素的影响。第三，我们创建了能够反映步态实际特征的划分模型。在评估新模型时，我们确认它能够以超过90%的准确率估计所有肌肉活动水平。
