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Knee angle prediction during stair ascending gait of trans-femoral amputee Neural networks application

机译:跨股骨截肢神经网络应用阶梯上升步态期间的膝关节角预测

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For the Trans-femoral (TF) amputee, the biomechanics of stair gait can be analyzed in only the stair descending. The information of stair ascending gait can be evaluated for only the normal side. The study with TF amputee mostly referred to the stair ascending by leading with the normal side rather than the prosthetic side as there was none of prosthesis can be the leading side to climb up the stair so none of TF amputee can make the step over step climbing up the stair. Since there was none of prosthesis can be the leading side to climb up the stair, none of TF amputee can make the step over step climbing up the stair and hence none of the stair ascending gait prediction model has been studied in transfemoral amputee, this study is aiming to figure out the stair gait ascending pattern in transfemoral amputee which imitated by the healthy person. Then, the neural network model is constructed to predict the knee angle during stair ascending, in which purpose to integrate into the controller of the prosthetic knee component to assist the stair ascending gait
机译:对于跨股(TF)截肢者,楼梯步态的生物力学只能在楼梯下降中分析。阶梯上升步态的信息只能为正常方面进行评估。与TF截肢者的研究主要由正常一侧而不是假肢的正常方面提升阶段,因为没有假肢可以是爬上楼梯的领先侧,所以没有TF截肢者可以使阶梯爬上一步楼梯。由于假肢没有一个假肢可以是爬上楼梯的领先方面,没有一个截肢者可以使阶梯爬上楼梯,因此没有阶梯上升的步态预测模型已经在经弗雷莫尔截肢者中研究过这项研究旨在弄清楚由健康人模仿的经罚款截肢者的楼梯步态上升模式。然后,构造神经网络模型以预测阶梯上升期间的膝膝斜角,其中目的是集成到假体膝部部件的控制器中以帮助阶梯上升步态

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