A Musculoskeletal Simulation Framework for In Silico Design and Optimization of a Soft Exosuit for Children with Muscular Dystrophy

项目摘要/摘要 肌营养不良症(MD)，如Duchenne MD和Becker MD，是导致 进行性肌肉变性在5-24岁的100,000名男性中约有14人。目前尚无已知的 可以阻止或逆转MD造成的损害的治疗。营养不良的肌肉特别容易患 在偏心收缩过程中损坏。软质外衣是一种新兴的可穿戴设备，它可能能够 为了减少下坡行走等功能性运动中的偏心收缩，这需要大量的 膝关节伸肌偏心收缩。Exosuts利用基于纺织品的顺应性执行器固有地提供 安全性和舒适性，这是非常可取的，以避免男孩的肌肉过度损伤的MD。 然而，对于患有MD的男孩来说，开发外衣的一个潜在障碍是在人类 受试者测试新的原型。肌肉骨骼模拟是早期设计的理想工具 用于MD儿童的外衣，因为模拟提供了肌肉偏心收缩的特征， 这很难在实验中观察到，并避免了在测试原型时对人体造成伤害的风险。 因此，本项目的总体目标是开发一个用于计算机设计的肌肉骨骼仿真框架 并优化了一种用于MD儿童的软性外衣。首先，现有的健康成年人步行模拟 下坡将被修改为包括一种模拟的柔软外衣。最初的外衣设计将基于现有的 物理原型。采用一种新的优化框架对外衣进行优化，使偏心最小化 下坡行走时股直肌(膝关节伸肌)收缩。将进行统计分析 为了检验以下假设：(1)模拟股直肌的偏心收缩(即净负功)是 (2)优化后的偏心收缩进一步减小。在……里面 此外，关节反作用力和其他肌肉的偏心收缩的变化将被量化为 调查潜在的不良副作用。在确定了成人使用外衣的潜在好处之后 模型，将开发一个儿童肌肉骨骼模型。将使用模拟的等轴测任务来校准 在典型的发育中和MD儿童模型中的最大等长肌力，以匹配公布的力量数据。 儿童穿着外衣下山的初步模拟将通过对成人进行缩放来生成 使用重定目标算法的移动数据。Exosuit优化框架将应用于 通常开发患有MD模型的儿童和儿童，以确定优化的外衣是否提供 股直肌偏心收缩的充分减少在未来的人类受试者中具有统计学意义 实验。这项拟议的研究旨在为设计一种能够实质上 近期改善MD儿童的生活质量。此外，基于肌肉骨骼的仿真 设计优化框架将促进辅助设备的快速电子设计和测试，如软件 外衣，对人体没有风险。

PROJECT SUMMARY/ABSTRACT Muscular dystrophies (MD), such as Duchenne MD and Becker MD, are rare genetic diseases that cause progressive muscle degeneration in approximately 14 in 100,000 males ages 5-24. Currently there is no known treatment that can stop or reverse the damage caused by MD. Dystrophic muscle is especially susceptible to damage during eccentric contraction. Soft exosuits are an emerging class of wearable device that may be able to reduce eccentric contraction during functional movements such as downhill walking, which requires substantial eccentric knee extensor contraction. Exosuits utilize compliant textile-based actuators to inherently provide safety and comfort to the user, which is highly desirable for avoiding excessive muscle injury in boys with MD. However, one potential barrier to development of exosuits for boys with MD is the risk of injury during human subjects testing of new prototypes. Musculoskeletal simulations are an ideal tool for early-stage design of exosuits for children with MD because simulations provide characterization of muscle eccentric contraction, which is difficult to observe experimentally, and avoid risk of injury to human subjects when testing prototypes. Thus, the overall objective of this project is to develop a musculoskeletal simulation framework for in silico design and optimization of a soft exosuit for children with MD. First, existing simulations of healthy adults walking downhill will be modified to include a simulated soft exosuit. The initial exosuit design will be based on existing physical prototypes. A novel optimization framework will be used to optimize the exosuit to minimize eccentric contraction in the rectus femoris (a knee extensor) during downhill walking. Statistical analysis will be performed to test the hypotheses that (1) simulated eccentric contraction (i.e., net negative work) in the rectus femoris is significantly reduced by the exosuit and (2) eccentric contraction is further reduced following optimization. In addition, changes in joint reaction forces and eccentric contraction in other muscles will be quantified to investigate potential adverse side effects. After establishing potential benefits of the exosuit using the adult model, a musculoskeletal model of a child will be developed. A simulated isometric task will be used to calibrate maximum isometric muscle force in a typically developing and MD child model to match published strength data. Preliminary simulations of a child walking downhill with the exosuit will be generated by scaling the adult movement data using a retargeting algorithm. The exosuit optimization framework will be applied to both the typically developing child and child with MD models to determine whether the optimized exosuit provided a sufficient reduction in rectus femoris eccentric contraction to be statistically significant in future human subjects experiments. The proposed research aims to establish a foundation for design of an exosuit that can substantially improve quality of life for children with MD in the near term. In addition, the musculoskeletal simulation-based design optimization framework will facilitate rapid in silico design and testing of assistive devices, such as soft exosuits, without risk to human subjects.