The interpretation of joint kinematics data in terms of displacements is a product of the type of movement, the measurement technique and the underlying model of the joint implemented in optimization procedures. Kinematic constraints reducing the number of degrees of freedom (DOFs) are expected to compensate for measurement errors and noise, thus, increasing the reproducibility of joint angles. One approach already successfully applied by several groups approximates the healthy human knee joint as a compound hinge joint with minimal varus/valgus rotation. Most of these optimizations involve an orthogonality constraint. This contribution compares the effect of a model with and without orthogonality constraint on the obtained joint rotation angles. For this purpose, knee joint motion is simulated to generate kinematic data without noise and with normally distributed noise of varying size. For small noise the unconstrained model provides more accurate results, whereas for larger noise this is the case for the constrained model. This can be attributed to the shape of the objective function of the unconstrained model near its minimum.

中文翻译：

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从运动学数据重建膝关节机构

根据位移对关节运动学数据的解释是运动类型、测量技术和优化程序中实施的关节基础模型的产物。减少自由度 (DOF) 数量的运动学约束有望补偿测量误差和噪声，从而提高关节角度的再现性。已经被多个小组成功应用的一种方法将健康的人类膝关节近似为具有最小内翻/外翻旋转的复合铰链关节。大多数这些优化涉及正交性约束。该贡献比较了具有和不具有正交性约束的模型对获得的关节旋转角度的影响。以此目的，模拟膝关节运动以生成没有噪声和具有不同大小的正态分布噪声的运动学数据。对于小噪声，无约束模型提供更准确的结果，而对于较大噪声，约束模型就是这种情况。这可以归因于接近其最小值的无约束模型的目标函数的形状。