Computational modelling is an invaluable tool for investigating features of human locomotion and motor control which cannot be measured except through invasive techniques. Recent research has focussed on creating personalised musculoskeletal models using population-based morphing or directly from medical imaging. Although progress has been made, robust definition of two critical model parameters remains challenging: (1) complete tibiofemoral (TF) and patellofemoral (PF) joint motions, and (2) muscle tendon unit (MTU) pathways and kinematics (i.e. lengths and moment arms). The aim of this study was to develop an automated framework, using population-based morphing approaches to create personalised musculoskeletal models, consisting of personalised bone geometries, TF and PF joint mechanisms, and MTU pathways and kinematics. Informed from medical imaging, personalised rigid body TF and PF joint mechanisms were created. Using atlas- and optimisation-based methods, personalised MTU pathways and kinematics were created with the aim of preventing MTU penetration into bones and achieving smooth MTU kinematics that follow patterns from existing literature. This framework was integrated into the Musculoskeletal Atlas Project Client software package to create and optimise models for 6 participants with incrementally increasing levels of personalisation with the aim of improving MTU kinematics and pathways. Three comparisons were made: (1) non-optimised (Model 1) and optimised models (Model 3) with generic joint mechanisms; (2) non-optimised (Model 2) and optimised models (Model 4) with personalised joint mechanisms; and (3) both optimised models (Model 3 and 4). Following optimisation, improvements were consistently shown in pattern similarity to cadaveric data in comparison (1) and (2). For comparison (3), a number of comparisons showed no significant difference between the two compared models. Importantly, optimisation did not produce statistically significantly worse results in any case.

计算建模是研究人类运动和运动控制特征的宝贵工具，这些特征只能通过侵入性技术进行测量。最近的研究侧重于使用基于人群的变形或直接从医学成像创建个性化的肌肉骨骼模型。尽管取得了进展，但两个关键模型参数的稳健定义仍然具有挑战性：(1) 完整的胫股 (TF) 和髌股 (PF) 关节运动，以及 (2) 肌腱单元 (MTU) 通路和运动学（即长度和力矩武器）。本研究的目的是开发一个自动化框架，使用基于群体的变形方法来创建个性化的肌肉骨骼模型，包括个性化的骨骼几何形状、TF 和 PF 关节机制以及 MTU 通路和运动学。从医学成像中获取信息，创建了个性化的刚体 TF 和 PF 关节机制。使用基于图谱和优化的方法，创建了个性化的 MTU 通路和运动学，目的是防止 MTU 渗透到骨骼中并实现遵循现有文献模式的平滑 MTU 运动学。该框架已集成到 Musculoskeletal Atlas Project Client 软件包中，为 6 名参与者创建和优化模型，并逐步提高个性化水平，目的是改善 MTU 运动学和路径。进行了三个比较：（1）非优化（模型 1）和优化模型（模型 3）具有通用关节机制；(2) 具有个性化关节机制的非优化（模型 2）和优化模型（模型 4）；(3) 两个优化模型（模型 3 和模型 4）。优化后，在比较 (1) 和 (2) 中，与尸体数据的模式相似性一致显示出改进。对于比较 (3)，许多比较显示两个比较模型之间没有显着差异。重要的是，在任何情况下，优化都不会产生统计学上显着更差的结果。