This article presents an optimization formulation and experimental validation of a dynamic-joint-strength-based two-dimensional symmetric maximum weight-lifting simulation. Dynamic joint strength (the net moment capacity as a function of joint angle and angular velocity), as presented in the literature, is adopted in the optimization formulation to predict the symmetric maximum lifting weight and corresponding motion. Nineteen participants were recruited to perform a maximum-weight-box-lifting task in the laboratory, and kinetic and kinematic data including motion and ground reaction forces were collected using a motion capture system and force plates, respectively. For each individual, the predicted spine, shoulder, elbow, hip, knee, and ankle joint angles, as well as vertical and horizontal ground reaction force and box weight, were compared with the experimental data. Both root-mean-square error and Pearson’s correlation coefficient (r) were used for the validation. The results show that the proposed two-dimensional optimization-based motion prediction formulation is able to accurately predict all joint angles, box weights, and vertical ground reaction forces, but not horizontal ground reaction forces.

本文提出了基于动态关节强度的二维对称最大举重仿真的优化公式和实验验证。在优化公式中采用了动态关节强度（净力矩能力与关节角和角速度的函数关系）来预测对称的最大起重重量和相应的运动。招募了19名参与者在实验室中执行最大举重动作，分别使用运动捕捉系统和测力板收集了包括运动和地面反作用力在内的动力学和运动学数据。对于每个人，预测的脊柱，肩膀，肘部，臀部，膝盖和脚踝关节角度，以及地面和地面的垂直反作用力和箱子重量，与实验数据进行了比较。均方根误差和Pearson相关系数（r）用于验证。结果表明，提出的基于二维优化的运动预测公式能够准确预测所有关节角度，箱体重量和垂直地面反作用力，但不能准确预测水平地面反作用力。