Simulation framework to develop ankle exoskeleton gait assistance for older adults

项目总结/摘要 候选人的长期目标是实现最佳和定制的干预，以改善流动性。莫- bility是维持积极的生活方式和功能独立性的基本身体活动， 这是老年人的常见问题，肌肉骨骼疾病是导致行动受限的主要原因。 虽然机器人矫形器或外骨骼有望改善移动性，但研究进展缓慢， 对步态辅助的结果的评估目前需要对人类受试者进行广泛的实验。在这 项目，候选人提出开发一个计算机模拟框架，可以预测步态动力学 和不同踝关节外骨骼辅助装置的性能。这项研究将开发和评估踝关节- 外骨骼辅助影响代谢能量消耗、步行速度和步行过程中的疼痛。 健康的年轻人和老年人以及患有膝关节骨关节炎的老年人。候选人将发展 仿真框架基于计算神经机械人类运动模型，他已经证实， 并使用他实验室开发的脚踝外骨骼模拟器收集人类步态数据 来验证框架的预测。除了模拟框架外，这项研究还将提供- kle外骨骼策略，可以有效地帮助健康的年轻人和老年人和那些膝盖骨， 关节炎走路更有效，更快，更少的痛苦。在K99阶段，候选人将接受培训- 我在斯坦福大学机械工程系工作。指导小组由四名 可以提供实验人体生物力学、计算机模拟人体运动- 老年人的肌肉骨骼疾病和老年学。由三名成员组成的咨询委员会 将提供额外的专业知识，在人体运动的最佳原则，并在非临床需要和手术 老年人的创伤培训将准备候选人成为一个领先的独立- 在运动控制和康复工程的多学科领域的研究员，谁生产的理论， 对改善活动性的caland clinical影响。

Project Summary / Abstract The candidate's long-term objective is to enable optimal and customized intervention to improve mobility. Mo- bility is an essential physical activity for maintaining an active lifestyle and functional independence and is a common issue for older adults, where musculoskeletal diseases are the leading cause of mobility limitations. While robotic orthoses, or exoskeletons, promise to improve mobility, the progress in research is slow as eval- uation on the outcome of gait assistance currently requires extensive experiments with human subjects. In this project, the candidate proposes to develop a computer simulation framework that can predict the gait dynamics and performance of different ankle-exoskeleton assistances. The study will develop and evaluate how ankle- exoskeleton assistance affects metabolic energy consumption, walking speed, and pain during walking in healthy young and older adults as well as in older adults with knee osteoarthritis. The candidate will develop the simulation framework based on a computational neuromechanical human locomotion model he has previ- ously developed, and collect human gait data using an ankle-exoskeleton emulator developed in his laboratory to validate the predictions of the framework. In addition to the simulation framework, the study will deliver an- kle-exoskeleton strategies that can effectively assist healthy young and older adults and those with knee osteo- arthritis to walk more efficiently, fast, and with less pain. During the K99 phase, the candidate will receive train- ing in the Department of Mechanical Engineering at Stanford University. The mentoring team consists of four experts who can provide training in experimental human biomechanics, computer simulation of human move- ment, musculoskeletal diseases in older adults, and gerontology. An advisory committee with three members will provide additional expertise in optimality principles in human motion, and in non-clinical needs and surgical trauma in the senior population. The training will prepare the candidate to become a leading independent in- vestigator in the multidisciplinary fields of motor control and rehabilitation engineering, who produces theoreti- cal and clinical impacts on improving mobility.