VIRTUAL MUSCLE: A HIERARCHICAL MATHEMATICAL MUSCLE MODEL

拟议SBIR项目的目的是为C-Motion增强和商业化一个强大的数学肌肉模型（在杰里勒布博士的实验室开发）在一个交互式程序（虚拟肌肉）的实验与神经肌肉控制的动态模拟。它将允许研究人员使用图形用户界面和自动化测试协议，在正向动态模拟中凭经验探索可定制肌肉模型的行为。在第一阶段，我们将：确定人体肌肉的模型参数;在Visual C++中实现模型，优化计算速度并允许在商业建模程序中作为致动器实现;开发用于模拟单个肌肉收缩的测试程序，并测试输出对模型参数扰动的灵敏度：开发一个二维人类和猴子手臂运动的自定义模拟，Loeb博士和他的同事正在研究这个问题; 2设计一个自动化测试的命令脚本方案;并定义测试数据后处理和编辑成格式化报告的规范。在第二阶段，我们将开发一个程序，探索计算作用于关节的个体肌肉力量的方法，从而对运动障碍进行临床和研究评估。拟议的商业应用：一个商业化的肌肉模型，易于使用，并准确地捕捉复杂的机械性能的真实的肌肉和肌腱，将是有用的研究人员谁必须了解神经肌肉控制，以解决临床康复问题。虚拟肌肉将成为下一代临床运动分析软件的关键元素，为神经肌肉控制研究提供环境，以开发解决一般分布问题和估计个体肌肉力量的新策略。

The purpose of the proposed SBIR project is for C-Motion to enhance and commercialize a powerful mathematical muscle model (developed in the laboratory of Dr. Jerry Loeb) within an interactive program (Virtual Muscle) for experimenting with dynamic simulations of neuromuscular control. It will allow investigators to explore empirically the behavior of customizable muscle models in forward dynamic simulations, using a graphical user interface and automated testing protocols. In Phase I, we will: determine model parameters for human muscles; implement the model in Visual C++, optimizing for speed of the calculations and allowing implementation as an actuator in commercial modeling programs; develop a testing program for simulation of the contraction of a single muscle, and test the output sensitivity to perturbations in model parameters: develop a custom simulation of two- dimensional human and monkey arm movements now being studied by Dr. Loeb and colleagues; design a command script scheme for automated testing; and define the specifications for post-processing and compilation of test data into a formatted report. In Phase II we will develop a program for exploring approaches to calculating individual muscle forces acting at a joint, leading to clinical and research evaluations of movement disorders. PROPOSED COMMERCIAL APPLICATIONS: A commercial muscle model that is easy to use, and captures accurately the complex mechanical properties of real muscles and tendons, will be useful to researchers who must understand neuromuscular control in order to address clinical rehabilitation issues. Virtual Muscle will be a key element of the next generation of clinical movement analysis software providing an environment for research in neuromuscular control in the development of new strategies for solving the general distribution problem and estimating individual muscle forces.