Department of Biomedical Engineering, New Jersey Institute of Technology, 323 Martin Luther King Blvd, Newark, NJ, 07102, USA.
Kessler Foundation, 1199 Pleasant Valley Way, West Orange, NJ, 07052, USA.
Med Biol Eng Comput. 2019 Feb;57(2):519-532. doi: 10.1007/s11517-018-1895-z. Epub 2018 Sep 25.
Upper limb overuse injuries are common in manual wheelchair users with spinal cord injury. Patient-specific in silico models enhance experimental biomechanical analyses by estimating in vivo shoulder muscle and joint contact forces. Current models exclude deep shoulder muscles that have important roles in wheelchair propulsion. Freely accessible patient-specific models have not been generated for persons with tetraplegia, who have a greater risk for shoulder pain and injury. The objectives of this work were to (i) construct a freely accessible, in silico, musculoskeletal model capable of generating patient-specific dynamic simulations of wheelchair propulsion and (ii) establish proof-of-concept with data obtained from an individual with tetraplegia. Constructed with OpenSim, the model features muscles excluded in existing models. Shoulder muscle forces and activations were estimated via inverse dynamics. Mean absolute error of estimated muscle activations and fine-wire electromyography (EMG) recordings was computed. Mean muscle activation for five consecutive stroke cycles demonstrated good correlation (0.15-0.17) with fine-wire EMG. These findings, comparable to other studies, suggest that the model is capable of estimating shoulder muscle forces during wheelchair propulsion. The additional muscles may provide a greater understanding of shoulder muscle contribution to wheelchair propulsion. The model may ultimately serve as a powerful clinical tool. Graphical abstract ᅟ.
上肢过度使用损伤在脊髓损伤的手动轮椅使用者中很常见。患者特异性的计算机模型通过估计体内肩部肌肉和关节接触力来增强实验生物力学分析。当前的模型排除了在轮椅推进中具有重要作用的深层肩部肌肉。尚未为四肢瘫痪患者生成可供自由访问的患者特异性模型,而四肢瘫痪患者患肩部疼痛和损伤的风险更高。这项工作的目的是:(i)构建一个可自由访问的计算机骨骼肌肉模型,能够生成针对特定患者的轮椅推进动态模拟;(ii)使用来自四肢瘫痪患者的数据建立概念验证。该模型由 OpenSim 构建,具有现有模型中排除的肌肉。通过逆动力学估计肩部肌肉力量和激活。计算估计的肌肉激活和细电线肌电图(EMG)记录的平均绝对误差。连续五个冲程周期的平均肌肉激活与细电线 EMG 具有良好的相关性(0.15-0.17)。这些发现与其他研究相当,表明该模型能够在轮椅推进过程中估计肩部肌肉力量。额外的肌肉可能更深入地了解肩部肌肉对轮椅推进的贡献。该模型最终可能成为一种强大的临床工具。