Simulation framework to develop ankle exoskeleton gait assistance for older adults

项目摘要/摘要 候选人的长期目标是实现最佳和定制的干预措施，以提高机动性。莫- 脱发是保持积极生活方式和功能独立的基本体力活动，是一种 老年人的常见问题，肌肉骨骼疾病是活动受限的主要原因。 虽然机器人矫形器或外骨骼有望改善移动性，但随着年龄的增长，研究进展缓慢。 对步态辅助效果的评估目前需要在人体受试者身上进行广泛的实验。在这 在这个项目中，候选人建议开发一个可以预测步态动力学的计算机模拟框架 以及不同的脚踝外骨骼助攻的表现。这项研究将开发和评估脚踝- 外骨骼辅助影响新陈代谢能量消耗、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骨性关节炎的老年人。候选人将会发展 基于他提出的计算神经机械人体运动模型的仿真框架。 自己开发，并使用他实验室开发的脚踝外骨骼仿真器收集人类步态数据 以验证该框架的预测。除了模拟框架外，这项研究还将提供一个- Kle-外骨骼战略，可以有效地帮助健康的年轻人和老年人以及有膝盖骨的人- 关节炎使行走更有效、更快、更少疼痛。在K99阶段，考生将接受培训- 在斯坦福大学机械工程系工作。指导团队由四人组成 能够提供实验人体生物力学、计算机模拟人体运动的培训的专家- 老年人的肌肉骨骼疾病，以及老年学。由三名成员组成的咨询委员会 将在人体运动、非临床需求和外科手术的最优化原则方面提供额外的专业知识 老年人口中的创伤。培训将使候选人做好准备，成为- 在运动控制和康复工程的多学科领域的研究人员，他产生了理论- CAL和临床对改善活动能力的影响。

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.