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首页> 外文期刊>Journal of Biomechanics >A new model to predict in vivo human knee kinematics under physiological-like muscle activation
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A new model to predict in vivo human knee kinematics under physiological-like muscle activation

机译：在生理样肌肉激活下预测体内人膝运动学的新模型

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Although a number of approaches have attempted to model knee kinematics, rarely have they been validated against in vivo data in a larger subject cohort. Here, we assess the feasibility of four-bar linkage mechanisms in addressing knee kinematics and propose a new approach that is capable of accounting for lengthening characteristics of the ligaments, including possible laxity, as well as the internal/external rotation of the joint. MR scans of the knee joints of 12 healthy volunteers were taken at flexion angles of 0 degrees, 30 degrees and 90 degrees under both passive and active muscle conditions. By reconstructing the surfaces at each position, the accuracy of the four-bar linkage mechanism was assessed for every possible combination of points within each cruciate ligament attachment area. The specific set of parameters that minimized the deviation between the predictions and the in vivo pose was derived, producing a mean error of 1.8 and 2.5 on the medial and 1.7 and 2.4mrn on the lateral side at 30 degrees and 90 degrees flexion, respectively, for passive motion, significantly improving oil the models that did not consider internal/external rotation. For active flexion, mean medial errors were 3.3 and 4.7 mm and lateral errors 3.4 and 4.8 mm. Using this best parameter set, a generic predictive model was created and assessed against the known in vivo positions, producing a maximum average error of 4.9mm at 90 degrees flexion. The accuracy achieved shows that kinematics may be accurately reconstructed for subject specific musculoskeletal models to allow a better understanding of the load distribution within the knee. (c) 2007 Elsevier Ltd. All rights reserved.
机译：尽管已经尝试了许多方法来模拟膝盖运动学，但很少有人针对较大的受试者队列对它们进行体内数据验证。在这里，我们评估了四连杆机构在解决膝关节运动学方面的可行性，并提出了一种新的方法，该方法能够解决韧带的延长特征，包括可能的松弛以及关节的内部/外部旋转。在被动和主动肌肉条件下，以0度，30度和90度屈曲角度对12名健康志愿者的膝关节进行MR扫描。通过在每个位置重建表面，对每个十字韧带连接区域内的点的每种可能组合，评估四连杆机构的精度。得出了将预测值与体内姿势之间的偏差最小化的一组特定参数，分别在屈曲30度和90度时，在内侧产生的平均误差分别为1.8和2.5，在外侧产生的平均误差为1.7和2.4m，对于被动运动，可以显着改善不考虑内部/外部旋转的模型。对于主动屈曲，平均内侧误差为3.3和4.7 mm，外侧误差为3.4和4.8 mm。使用该最佳参数集，创建了通用的预测模型，并针对已知的体内位置进行了评估，从而在90度屈曲时产生了4.9mm的最大平均误差。所获得的精度表明，可以针对受试者特定的肌肉骨骼模型准确地重建运动学，以更好地了解膝盖内的负荷分布。 （c）2007 Elsevier Ltd.保留所有权利。

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