大数据下花样跳绳运动动作安全性预测仿真
发布时间：2019-06-08 16:02
【摘要】：对花样跳神运动动作的安全性进行预测,能够有效降低跳绳运动对人体各部位的损伤概率。对花样跳绳动作安全性的预测,需要先评价跳绳动作对关节损伤,以踝关节为例,获得惯性载荷作用下其关节面形变量。传统方法对关节表面的力学特征进行分析,设定关节面的应力峰值,但忽略了关节面的形变量,导致对关节预测精度偏低。提出大数据下基于逆向动力学的花样跳绳运动关节预测模型。计算得出动态平衡状态下关节位置的主动活动度,获得动作在惯性载荷作用下其各个关节面的形变量,进一步得到了关节位置力矩变化量及角度变化量递推计算式,并分析了关节位置觉的影响因素,建立花样跳绳运动对动作安全性的预测模型。实验结果表明,所提方法预测精度高,能够预防和减少关节损伤。
[Abstract]:Predicting the safety of figure skipping can effectively reduce the damage probability of rope skipping to all parts of the human body. To predict the safety of pattern rope skipping, it is necessary to evaluate the joint injury caused by rope skipping. Taking the ankle joint as an example, the joint shape variable under inertial load is obtained. The mechanical characteristics of the joint surface are analyzed by the traditional method, and the stress peak value of the joint surface is set, but the shape variable of the joint surface is ignored, which leads to the low accuracy of joint prediction. A prediction model of pattern rope skipping joint based on reverse dynamics under big data is proposed. The active motion of the joint position under the dynamic equilibrium state is calculated, and the shape variables of each joint surface of the action under the action of inertia load are obtained, and the recurrence formulas of the torque variation and the angle change of the joint position are further obtained. The influencing factors of joint position perception are analyzed, and the prediction model of movement safety caused by pattern rope skipping is established. The experimental results show that the proposed method has high prediction accuracy and can prevent and reduce joint injury.
【作者单位】： 江西中医药大学体育教学部;南昌大学体育与教育学院;
【分类号】：G898.1
，
本文编号：2495416
[Abstract]:Predicting the safety of figure skipping can effectively reduce the damage probability of rope skipping to all parts of the human body. To predict the safety of pattern rope skipping, it is necessary to evaluate the joint injury caused by rope skipping. Taking the ankle joint as an example, the joint shape variable under inertial load is obtained. The mechanical characteristics of the joint surface are analyzed by the traditional method, and the stress peak value of the joint surface is set, but the shape variable of the joint surface is ignored, which leads to the low accuracy of joint prediction. A prediction model of pattern rope skipping joint based on reverse dynamics under big data is proposed. The active motion of the joint position under the dynamic equilibrium state is calculated, and the shape variables of each joint surface of the action under the action of inertia load are obtained, and the recurrence formulas of the torque variation and the angle change of the joint position are further obtained. The influencing factors of joint position perception are analyzed, and the prediction model of movement safety caused by pattern rope skipping is established. The experimental results show that the proposed method has high prediction accuracy and can prevent and reduce joint injury.
【作者单位】： 江西中医药大学体育教学部;南昌大学体育与教育学院;
【分类号】：G898.1
，
本文编号：2495416
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