CAREER: A Task-Invariant Customization Framework for Lower-Limb Exoskeletons to Assist Volitional Human Motion

职业生涯：用于辅助人类意志运动的下肢外骨骼的任务不变定制框架

• 批准号: 2340261
• 负责人: Ge Lv
• 金额: $ 57.09万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-04-01 至 2029-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2340261&HistoricalAwards=false
• 关键词: CAREER; Task; Invariant; Customization; Framework

This Faculty Early Career Development (CAREER) award will support research that advances knowledge in the control and optimization of lower-limb exoskeletons in providing their human users with customized assistance across locomotor tasks. Conventional customization paradigms often aim at optimizing parameters of pre-defined torque profiles for specific locomotor tasks, which cannot accommodate the continuously varying activities humans perform every day. Prevalent approaches also place emphasis on minimizing slow-converging energy expenditures associated with human locomotion, which is important for able-bodied persons but might not be of high priority for individuals with pathological gaits. The goal of this project is to provide a paradigm shift from task-specific, slow convergent customization to task-invariant, rapid customization. This research will facilitate active learning and adaptation of lower-limb exoskeletons to drastically reduce the cost of gait rehabilitation for nearly a million Americans who sustain a new stroke every year. Key parameters throughout gait rehabilitation such as body-weight support ratio will be automatically customized based on stroke subject's training progress, which will otherwise be tuned by a team of therapists and engineers that usually lasts for hours. This research will also promote the use of exoskeletons for able-bodied users in manufacturing sites, warehouses, battlefields, and other relevant scenes by reducing the associated costs in control parameter customization. The integrated education plan will help cultivate the next-generation wearable robot researchers and motivating K-12 students to further pursue STEM degrees. The human subject studies and exhibits will promote the awareness of wearable technologies among the public, especially among traditionally underrepresented groups.The goals of this project are to: 1) investigate invariant assistive strategies in continuously varying locomotor tasks and environments, 2) construct a complete framework for customizing exoskeleton assistance across locomotor tasks, and 3) understand how the customization framework facilitates assistance adaptations to different user’s volitional motion and activities. Utilizing a two-layer optimization structure will rapidly determine task-invariant assistive strategies in the inner-loop through tracking the desired energetics or centroidal momentum of a virtual reference model, meanwhile updating its parameters in the outer-loop based on human performance-based cost functions. The research the PI and his team will conduct will investigate task-invariant assistive strategies that alter human body energetics and centroidal momentum, construct a complete, human-in-the-loop customization framework that rapidly customizes these two quantities, and validate its efficacy via experiments on human subjects across various locomotor tasks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项教师早期职业发展（职业）奖将支持研究，以在低LIMB外骨骼控制和优化的知识方面为其人类用户提供跨运动任务的自定义帮助。常规的自定义范例通常旨在优化特定运动任务的预定扭矩轮廓的参数，这些参数无法适应人类每天执行的连续变化的活动。普遍的方法还强调最大程度地减少与人类运动相关的慢置能量消耗，这对于身体健全的人来说很重要，但对于病理步态的人来说可能不是很高的优先事项。该项目的目的是提供从特定于任务的，缓慢的收敛自定义到任务不变的快速自定义的范式转变。这项研究将有助于积极学习和适应下限的外骨骼，以大大降低每年维持新中风的近一百万美国人的步态康复成本。整个步态康复中的关键参数，例如体重支持率，将根据Stroke受试者的训练进度自动定制，否则，通常会持续数小时的治疗师和工程师团队进行调整。这项研究还将通过降低控制参数定制的相关成本来促进在制造网站，仓库，战场和其他相关场景中在制造网站，仓库，战场和其他相关场景中使用外骨骼的使用。综合教育计划将有助于培养下一代可穿戴的机器人研究人员，并激励K-12学生进一步购买STEM学位。人类主题的研究和展览将促进公众之间对可穿戴技术的认识，尤其是在传统上代表性不足的群体中。该项目的目标是：1）调查不变的辅助策略，以不断变化的运动任务和环境，2）构建各种跨越型号的范围，以构建各种型号的范围，并了解各种型号的范围，并了解各种型号的范围。和活动。利用两层优化结构将通过跟踪虚拟参考模型的所需能量或质心动量来迅速确定内循环中的任务不变辅助策略，这是指基于人类绩效的基于基于人类绩效的成本功能的外循环中更新其参数的同时。 PI和他的团队将进行的研究将调查任务不断变化的辅助策略，这些策略改变了人体能量和中心动量，构建了一个完整的，人类的环境定制框架，迅速自定义这两个数量，并通过实验对人类的实验来确认其有效性，这些框架对人类的主体进行了各种智力的授权，并反映了NSF的范围，并反映了NSF的范围。影响审查标准。