Shoulder musculo-skeletal modelling: from muscle path refinement to optimal control based on direct multiple shooting

肩关节疾病的患病率仅次于背痛。由于肩部肌肉冗余和多关节肌肉的存在，在没有估计肌肉力量的情况下，难以确定每块肌肉对关节活动性与稳定性的贡献。这种分析有助于改善神经和骨科疾病的诊断和治疗。由于肌肉力量的动态测量在临床环境中是不可行的，因此将肌电图（EMG）和运动学的非侵入性协议与肌肉骨骼（MSK）模型相结合来估计肌肉力量。利用这种方法，我们最近设计了一种创新的肩关节术后矫形器。然而，根据我们和其他人的经验，已经发现当前的MSK模型在更个性化的临床和工业应用中失败。模型在力量能力和肌肉协调策略方面不是特定于主题的。此外，迄今为止的建模工作并没有集中在肩袖肌肉上，而最常见和最昂贵的肩部投诉与这些从肩胛骨到肱骨的深层肌肉有关。我们的5年目标是确定个性化的肩部肌肉参数，特别强调肩袖肌肉（特定目标，SO1），以估计准确的肌肉力量在职业任务（SO2），使用EMG和运动学数据。最优控制和识别问题都将使用直接多重打靶法来解决。这种方法在机器人和生物力学中得到了很好的验证，但从未应用于MSK模型。补充目标（SO3）是细化MSK模型中的肩袖几何结构。SO1：为了确定肌肉参数，受试者将在测力计上进行一系列等长和等速最大自主收缩。运动的多样性是必不可少的，因为没有一个单一的运动完全激活所有的肩部肌肉。二氧化硫：与现有的方法估计肌肉力量，假设无噪声运动学，我们的方法的新奇是共同优化运动学和EMG数据，在约束下，最佳的解决方案仍然在受试者内的变化，当重复一个标准化的任务。关节运动学中的预期误差也将被添加到变异性中，因为将标记物置于皮肤上的临床方案会导致肩骨运动学中的大量误差。虽然在过去的3年里，我们专注于肩关节运动学的估计，准确性仍然是未知的。基于皮肤标记的运动学将与使用金标准的骨骼运动学进行比较，即在锁骨、肩胛骨和肱骨中拧入的销钉。SO3：最后，应该使用弹簧网格来获得更多的生理肌肉路径，而不是以非生理方式在肱骨头上散布的独立作用线。补片应再现肌腱的几何形状，肌腱相互交错，在肱骨头周围形成袖套。尸体肩关节将用于在几种臂配置中确认模型。我们的方法将提供最好的估计肌肉力量的特定主题的技术。该项目为培养4名研究生和10名本科生提供了一个极好的机会，他们将使用最先进的设备进行实验人体生物力学和多体系统的最优控制算法。我们的方法有望成为最先进的肩关节MSK建模，特别是研究肩袖损伤。完善模拟模型和改进肩部最佳控制方法是开发肩部矫形器、改进肩部肌肉撕裂手术修复和预防工作场所肩部损伤项目的基石。

Shoulder disorder prevalence stands just after back pain. Due to shoulder muscle redundancy and the presence of polyarticular muscles, the contribution of each muscle to joint mobility versus stability is difficulty to determine without an estimate of muscle forces. Such analyses can contribute to improved diagnosis and treatment of neurological and orthopedic diseases. Since dynamic measure of muscle forces are unfeasible in clinical settings, non-invasive protocols with electromyography (EMG) and kinematics are to be combined with musculoskeletal (MSK) models to estimate muscle forces. Using this approach, we recently design an innovative shoulder post-operative orthosis. However, from our and other’s experience, current MSK models have be found to fail in more personalized clinical and industrial applications. Models are not subject-specific in terms of strength capacity and muscle coordination strategies. Furthermore, to date modeling efforts have not focused on the rotator cuff muscles, while the most frequent and costly shoulder complaints are related to these deep muscles, which run from the scapula to the humerus. Our 5-year objective is to identify personalized shoulder muscle parameters with a particular emphasis on rotator cuff muscles (specific objective, SO1) to estimate accurate muscle force in occupational tasks (SO2), using both EMG and kinematic data. Both optimal control and identification problems will be solved using a direct multiple shooting method. This method is well-tried in robotics and biomechanics but has never been applied to MSK models. A complementary objective (SO3) is to refine the rotator cuff geometry in the MSK model. SO1: To identify muscle parameters, subjects will perform series of isometric and isokinetic maximal voluntary contractions on a dynamometer. Diversity of exercises is essential since no single movement fully activates all shoulder muscles. SO2: In contrast to existing methods for estimating muscle forces, which assume noiseless kinematics, the novelty of our approach is to jointly optimize kinematic and EMG data, under the constraint that the optimal solution remains within intra-subject variability when repeating a standardized task. An expected error in joint kinematics will also be added to variability, since clinical protocols with markers put on the skin lead to substantial errors in shoulder bone kinematics. While in the last 3 years we focused on estimating of shoulder joint kinematics, the accuracy is still unknown. Skin marker-based kinematics will be compared to skeletal kinematics using a gold standard, namely pins screwed in clavicle, scapula and humerus. SO3: Finally, more physiological muscle paths should be obtained using a mesh of springs instead of independent lines of action that spread on the humeral head in a non-physiological manner. The mesh should reproduce the geometry of the tendons which interdigitate with each other to form a cuff around the humeral head. Cadaveric shoulders will be used to validate the model in several arm configurations. Our method will provide the best estimate of muscle forces for a subject-specific technique. This proposal is an outstanding opportunity to train 4 graduate students and 10 undergraduates in both experimental human biomechanics with the most advanced equipment and optimal control algorithms of multibody systems. Our method is expected to become the state-of-the-art in shoulder MSK modeling, particularly to study rotator cuff injuries. Refining simulation models and improving methods for shoulder optimal control are the cornerstone of projects leading to shoulder orthotic development, improvements in surgical restoration of shoulder muscle tears and in the prevention of shoulder injuries in the workplace.