Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, Australia.
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, Australia.
Comput Biol Med. 2023 Sep;164:107292. doi: 10.1016/j.compbiomed.2023.107292. Epub 2023 Aug 2.
Distal radius fractures (DRFs) treated with volar locking plates (VLPs) allows early rehabilitation exercises favourable to fracture recovery. However, the role of rehabilitation exercises induced muscle forces on the biomechanical microenvironment at the fracture site remains to be fully explored. The purpose of this study is to investigate the effects of muscle forces on DRF healing by developing a depth camera-based fracture healing model.
First, the rehabilitation-related hand motions were captured by a depth camera system. A macro-musculoskeletal model is then developed to analyse the data captured by the system for estimating hand muscle and joint reaction forces which are used as inputs for our previously developed DRF model to predict the tissue differentiation patterns at the fracture site. Finally, the effect of different wrist motions (e.g., from 60° of extension to 60° of flexion) on the DRF healing outcomes will be studied.
Muscle and joint reaction forces in hands which are highly dependent on hand motions could significantly affect DRF healing through imposed compressive and bending forces at the fracture site. There is an optimal range of wrist motion (i.e., between 40° of extension and 40° of flexion) which could promote mechanical stimuli governed healing while mitigating the risk of bony non-union due to excessive movement at the fracture site.
The developed depth camera-based fracture healing model can accurately predict the influence of muscle loading induced by rehabilitation exercises in distal radius fracture healing outcomes. The outcomes from this study could potentially assist osteopathic surgeons in designing effective post-operative rehabilitation strategies for DRF patients.
掌侧锁定板(VLP)治疗桡骨远端骨折(DRF)可早期进行康复锻炼,有利于骨折愈合。然而,康复锻炼引起的肌肉力量对骨折部位生物力学微环境的作用仍有待充分探索。本研究旨在通过开发基于深度相机的骨折愈合模型,研究肌肉力量对 DRF 愈合的影响。
首先,通过深度相机系统捕获与康复相关的手部运动。然后开发一个宏观肌肉骨骼模型来分析系统捕获的数据,以估计手部肌肉和关节反作用力,这些力作为输入用于我们之前开发的 DRF 模型,以预测骨折部位的组织分化模式。最后,研究不同腕部运动(例如,从 60°伸展到 60°屈曲)对 DRF 愈合结果的影响。
手部运动高度依赖的肌肉和关节反作用力会通过在骨折部位施加压缩力和弯曲力,显著影响 DRF 愈合。存在一个最佳的腕部运动范围(即,40°伸展和 40°屈曲之间),可以促进机械刺激为主的愈合,同时减轻由于骨折部位过度运动导致的骨不连风险。
开发的基于深度相机的骨折愈合模型可以准确预测康复锻炼引起的肌肉负荷对桡骨远端骨折愈合结果的影响。这项研究的结果可能有助于整骨外科医生为 DRF 患者设计有效的术后康复策略。