Clinical gait analysis incorporated with neuromusculoskeletal modelling could provide valuable information about joint movements and muscle functions during ambulation for children with cerebral palsy (CP). This study investigated how imposing pre-calculated joint angles during musculoskeletal model scaling influence the ankle joint angle and muscle force computation. Ten children with CP and equinus gait underwent clinical gait analysis. For each participant, a “default” (scaled without pre-calculated joint angles) and a “PJA” (scaled with pre-calculated ankle joint angles) model were generated to simulate their gait. Ankle joint angles were calculated with an inverse kinematic (IK) and direct kinematic (DK) approach. Triceps surae and tibialis anterior muscle forces were predicted by static optimisation and EMG-assisted modelling. We found that PJA-derived ankle angles showed a better agreement with what derived from the DK approach. The tibialis anterior muscle prediction was more likely to be affected by the scaling methods for the static optimisation approach and the gastrocnemius muscle force prediction was more likely to be influenced for the EMG-assisted modelling. This study recommends using the PJA model since the good consistency between IK and DK-derived joint angles facilitates communication among different research disciplines.

结合神经肌肉骨骼模型进行的临床步态分析可以为患有脑瘫（CP）的儿童在行走过程中提供有关关节运动和肌肉功能的有价值的信息。这项研究调查了肌肉骨骼模型缩放过程中强加的预先计算的关节角度如何影响踝关节角度和肌肉力量的计算。十名患有CP和马蹄型步态的儿童接受了临床步态分析。对于每个参与者，都会生成一个“默认”模型（不使用预先计算的关节角度进行缩放）和一个“ PJA”模型（用预先计算的踝关节角度进行缩放）模型来模拟他们的步态。踝关节角度通过反向运动学（IK）和直接运动学（DK）方法计算。通过静态优化和EMG辅助模型预测了肱三头肌和胫骨前肌的力量。我们发现，PJA派生的踝角与DK方法派生的角更好地吻合。静态优化方法的缩放方法更可能影响胫骨前肌的预测，而肌电图辅助建模更可能影响腓肠肌的肌力预测。本研究推荐使用PJA模型，因为IK和DK派生的关节角度之间的良好一致性有利于不同研究学科之间的交流。