CAREER: The Ultimate Machine, Modeling neuromuscular control and musculoskeletal dynamics to improve human ability

职业：终极机器，模拟神经肌肉控制和肌肉骨骼动力学以提高人类能力

• 批准号: 1452646
• 负责人: Katherine Steele
• 金额: $ 50.44万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-02-15 至 2022-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1452646&HistoricalAwards=false
• 关键词: CAREER; Ultimate; Machine; Modeling; neuromuscular

This CAREER grant focuses on the development and evaluation of novel computational tools to predict changes in human movement with exoskeletons. Recent technological advances have created new exoskeletons, external devices including orthoses and braces, which can apply passive or active torques to the human body. However, the ability of these devices to make consistent improvements in movement remains challenging. A fundamental knowledge gap exists in how the human body responds and adapts when wearing these devices, hindering performance and development. To overcome this gap, this research will use a combination of musculoskeletal simulation and experimental motion capture to create a conceptual framework for modeling and predicting changes in neuromuscular control and musculoskeletal dynamics when wearing devices that apply assistive, augmentive, or preventive torques to the human body. Two model systems that apply external torques to the ankle will be used to experimentally test and evaluate this framework: passive ankle foot orthoses for assisting movement and active ankle orthoses for enhancing power. These systems will be tested with individuals with stroke or cerebral palsy who commonly use orthoses to improve movement, as well as unimpaired individuals. Prior simulations of human movement have largely focused on the musculoskeletal system, but few techniques exist to model neuromuscular control and muscle recruitment. Dynamic simulation provides an ideal framework to specify and test different neuromuscular control strategies and expand our ability to design optimized exoskeletons. This research will develop algorithms to model neuromuscular control with dynamic simulation, predict changes in human movement with exoskeletons, and experimentally evaluate this new framework. All algorithms developed will be shared in an open-source simulation framework, OpenSim, for other researchers and educators to use.The proposed research will provide the foundation to improve movement for individuals with neurological disorders, such as cerebral palsy and stroke, and others who can benefit from advances in wearable technology. The technical advances in algorithm development and neuromuscular simulation will provide a new set of tools for researchers and clinicians to use in the design, evaluation, and prescription of devices to enhance human movement. To help train engineers who can apply their knowledge to the complexities of the human body, a multidisciplinary education program focused on human engineering will be created at the University of Washington for students in engineering and medicine. Students will participate in journal clubs, coursework, and design projects where they will create open-source orthoses for individuals with disabilities. We will also develop open-source outreach modules focused on human engineering in partnership with local programs that encourage under-represented groups to pursue careers in engineering, including women, minorities, and individuals with disabilities. These modules will be shared on-line for other groups to use and help encourage a diverse community of future engineers. Together this work will help to accelerate the design and prescription of exoskeletons for individuals with neurological disorders and promote a community passionate about enhancing the performance of the ultimate machine - the human body.

这项CAREER资助的重点是开发和评估新的计算工具，以预测人类运动与外骨骼的变化。最近的技术进步已经创造了新的外骨骼，包括矫形器和支架在内的外部设备，其可以向人体施加被动或主动扭矩。然而，这些设备在运动方面做出一致改进的能力仍然具有挑战性。在佩戴这些设备时，人体如何做出反应和适应方面存在根本的知识差距，阻碍了性能和发展。为了克服这一差距，本研究将使用肌肉骨骼模拟和实验动作捕捉的组合来创建一个概念框架，用于建模和预测神经肌肉控制和肌肉骨骼动力学的变化，当佩戴设备时，将辅助，增强或预防扭矩应用于人体。两个模型系统，施加外部扭矩的踝关节将被用来实验测试和评估这个框架：被动踝足矫形器辅助运动和主动踝矫形器，以提高功率。这些系统将在中风或脑瘫患者中进行测试，他们通常使用矫形器来改善运动，以及未受损的个人。以前的人体运动模拟主要集中在肌肉骨骼系统，但很少有技术存在模型神经肌肉控制和肌肉招募。动态仿真提供了一个理想的框架来指定和测试不同的神经肌肉控制策略，并扩展我们设计优化外骨骼的能力。这项研究将开发算法来模拟神经肌肉控制与动态仿真，预测人类运动与外骨骼的变化，并实验评估这一新的框架。所有开发的算法都将在开源模拟框架OpenSim中共享，供其他研究人员和教育工作者使用。拟议的研究将为改善患有神经系统疾病（如脑瘫和中风）的个人以及其他可以从可穿戴技术进步中受益的人的运动提供基础。算法开发和神经肌肉模拟的技术进步将为研究人员和临床医生提供一套新的工具，用于设计，评估和处方设备，以增强人体运动。为了帮助培养能够将其知识应用于人体复杂性的工程师，华盛顿大学将为工程和医学专业的学生创建一个以人体工程学为重点的多学科教育计划。学生将参加期刊俱乐部，课程和设计项目，他们将为残疾人创建开源矫形器。我们还将与当地计划合作开发以人类工程为重点的开源外展模块，鼓励代表性不足的群体从事工程职业，包括妇女，少数民族和残疾人。这些模块将在线共享给其他团体使用，并有助于鼓励未来工程师的多元化社区。这项工作将有助于加速为患有神经系统疾病的个人设计和处方外骨骼，并促进一个热衷于提高终极机器-人体性能的社区。