Multibody dynamics, simulation, and parameter identification of 3D biomechanical systems

一位外科医生有一个新的想法，可以帮助受伤的病人再次行走。 手术包括重新安排一些肌腱和韧带。 但是，外科医生在将其用于患者之前如何测试他们的想法？ 生物力学工程师如何设计和测试新的假肢或康复设备？ 安全问题是深远的，特别是如果该设备包含电动机和控制器。 计算机模拟可以帮助回答这些和其他问题，但模拟必须准确和快速。 这项研究的5年目标是开发与机电设备相互作用的三维（3D）生物力学系统的自动模拟，这一领域被称为“生物机电一体化”。申请人将建立在他以前在多体动力学方面的工作基础上，其中已经创建了算法来自动模拟互连机构系统的运动。 通过简化分析，可以将更多的时间花在新产品和工艺的设计上;因此，多体动力学已被机器人，航空航天和汽车工业广泛采用。 然而，最近尝试将多体动力学扩展到3D人体运动的分析遇到了一些挑战：软组织的非线性，特别是在与地面或其他硬表面接触时，模型参数的识别，以及3D人体平衡的控制。 目前还没有多体动力学算法可以忠实地预测具有计算效率高的接触模型的3D生物力学系统的自然运动。 为了开发这种模拟，肌肉、关节和与硬表面的3D接触的数学模型将被纳入申请人的多体算法。敏感性分析将用于确定给出有效结果的模型参数。为了预测平衡的人体运动，我们将结合联合收割机新的优化方法与最近的理论，机器人控制。 应用程序将集中在步行和触摸，实验设施可用。 我们将与运动学家和其他医疗保健专业人员合作，将我们的模拟工具应用于疾病的治疗和辅助设备的设计。

A surgeon has a new idea for a procedure that may help an injured patient walk again. The procedure involves re-routing some tendons and ligaments. But how does the surgeon test out their idea before using it on a patient? How can a biomechanical engineer design and test a new prosthesis or rehabilitation device? The safety implications are profound, especially if the device contains electrical motors and controllers. Computer simulations can help answer these and other questions, but the simulations must be accurate and fast. The 5-year goal of this research is to develop automated simulations of three-dimensional (3D) biomechanical systems that interact with electro-mechanical devices, a field known as "biomechatronics". The applicant will build upon his previous work in multibody dynamics, in which algorithms have been created to automatically simulate the motion of a system of interconnected bodies. By streamlining the analysis, more time can be spent on the design of new products and processes; hence, multibody dynamics has been widely adopted by the robotics, aerospace, and automotive industries. However, recent attempts to extend multibody dynamics to the analysis of 3D human motions have encountered a number of challenges: the nonlinearity of soft tissues, especially during contact with the ground or other hard surfaces, identification of model parameters, and the control of 3D human balance. There are currently no multibody dynamics algorithms that can faithfully predict the natural motion of a 3D biomechanical system with computationally-efficient contact models. To develop such simulations, mathematical models of muscles, joints, and 3D contact with hard surfaces will be incorporated into the applicant's multibody algorithms. Sensitivity analyses will be used to identify model parameters that give valid results. To predict balanced human motions, we will combine new optimization methods with recent theories on biped robot control. Applications will focus on walking and touching, for which experimental facilities are available. We will collaborate with kinesiologists and other health care professionals to apply our simulation tools to the treatment of illnesses and the design of assistive devices.