Toolbox for estimation, simulation and control of multi-joint movements

用于估计、模拟和控制多关节运动的工具箱

• 批准号: 7512485
• 负责人: Emanuel Todorov
• 金额: $ 16.9万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7512485
• 关键词: Academia; Algorithms; Appendix; Arts; Athletic; Automobile Driving; Behavior; Biological; Biomechanics; Brain; Budgets; Calibration; Clinical; Collaborations; Collection; Compatible; Complex; Computer software; Computing Methodologies; Data; Data Analyses; Detection; Development; Devices; Documentation; Eating; Electric Stimulation; Electromagnetics; Ensure; Environment; Equilibrium; Extensible Markup Language; Feedback; Funding; Generations; Goals; Grant; Hour; Human; Human body; Imagery; Industry; Joints; Laws; Left; Libraries; Limb structure; Location; Measurement; Methodology; Methods; Modality; Modeling; Motion; Motor; Movement; Muscle; Numbers; Occupational Safety; Operative Surgical Procedures; Optics; Output; Performance; Placement; Positioning Attribute; Production; Productivity; Publishing; Purpose; Reconstructive Surgical Procedures; Rehabilitation therapy; Reliance; Research; Research Personnel; Running; Sensory Receptors; Signal Transduction; Simulate; Skeletal system; Skeleton; Software Tools; Specific qualifier value; Standards of Weights and Measures; Students; Suggestion; System; Testing; Time; Translating; Trees; United States National Institutes of Health; Variant; Work; Writing; animation; base; clinical application; computer human interaction; data modeling; data structure; design; engineering design; experience; graphical user interface; interest; kinematics; motor control; neural prosthesis; neuroregulation; relating to nervous system; research and development; sensor; simulation; size; soft tissue; software development; sound; tool; usability; virtual

DESCRIPTION (provided by applicant): We propose to develop a toolbox for estimation, simulation and control of multi-joint movements. Our immediate goal is to facilitate research in Motor Control, by providing access to advanced computational methods and making such methods an integral part of the hypothesis generation-and-testing cycle. The estimation component of the toolbox will enable researchers to accurately compute multi-joint movement trajectories as well as limb sizes from motion capture data, without spending hours to place markers at precise locations and redesign setups to ensure that every marker is always visible. The control component will make it possible to formulate mathematically-sound hypotheses about the control strategies used by the brain, and automatically synthesize detailed control laws corresponding to the user's hypotheses. These control laws will then be applied to realistic musculo-skeletal models, using the simulation component, and the predicted behavior will be compared to experimental data in terms of kinematics, contact forces and EMGs. In case of a mismatch the toolbox will be able to netune any free parameters of the controller, and also search the library of candidate control strategies and identify the one which best agrees with the data. Our longer-term goal is to assist clinicians and engineers designing new treatments such as reconstructive surgery and functional electric stimulation. Testing candidate control mechanisms on simulated musculo-skeletal dynamics can greatly reduce the undesirable trial-and-error iterations. Customizations necessary for clinical use are left outside the scope of this project, however they will be possible once the core functionality is developed in a system with open design. The toolbox will be written in Matlab, with some C++ components, and will be freely available for academic, research and non-prot purposes. Project narrative We propose to develop a toolbox for estimation, simulation and control of multi-joint movement. Our immediate goal is to facilitate research in the eld of Motor Control by providing access to advanced computational methods presently beyond the reach of many investigators. While tools for simulating musculo-skeletal dynamics already exist, simulation alone is rarely suffcient to advance our understanding of motor function. Here we will combine simulation with automatic controllers capable of driving realistic musculo-skeletal models, and provide tools for estimating multi-joint movements from motion capture data. Our longer-term goal is to assist clinicians and engineers designing new treatments such as reconstructive surgery and functional electric stimulation.

描述（由申请人提供）：我们建议开发一个工具箱，以估算，模拟和控制多关节运动。我们的近期目标是通过提供对先进的计算方法的访问并将这种方法作为假设生成和测试周期不可或缺的一部分来促进运动控制的研究。该工具箱的估计组件将使研究人员能够准确地计算多接头运动轨迹以及运动捕获数据的肢体大小，而无需花费小时以将标记放置在精确的位置和重新设计设置，以确保每个标记始终可见。控制组件将使关于大脑使用的控制策略的数学词立假设成为可能，并自动合成与用户假设相对应的详细控制法。然后，使用模拟成分将这些控制定律应用于现实的肌肉骨骼模型，并将预测的行为与运动学，接触力和EMG的实验数据进行比较。如果不匹配，则工具箱将能够为控制器的任何免费参数净化，并搜索候选控制策略的库，并确定最能与数据一致的库。我们的长期目标是协助临床医生和工程师设计新治疗方法，例如重建手术和功能性电刺激。在模拟的肌肉骨骼动力学上测试候选控制机制可以大大减少不良的试验和错误迭代。临床使用所需的自定义不在该项目的范围之内，但是一旦在具有开放设计的系统中开发核心功能后，它们将成为可能。该工具箱将用MATLAB编写，其中有一些C ++组件，并可以免费用于学术，研究和非功能。项目叙述我们建议开发一个工具箱，以估算，模拟和控制多接头运动。我们的近期目标是通过在许多研究人员的范围内提供对先进的计算方法的访问，从而促进运动控制的研究。尽管已经存在用于模拟肌肉骨骼动力学的工具，但单独的模拟很少足以提高我们对运动功能的理解。在这里，我们将将仿真与能够驱动现实的肌肉骨骼模型的自动控制器结合在一起，并提供用于估算运动捕获数据的多关节运动的工具。我们的长期目标是协助临床医生和工程师设计新治疗方法，例如重建手术和功能性电刺激。