CAREER: Hybrid Ankle Exoskeleton Therapy to Optimize Long-Term Gait Rehabilitation

这个NSF教师早期职业发展（Career）项目旨在推进步行康复的科学研究，并开创一种新的可穿戴康复策略。目前迫切需要针对步行残疾的根本原因进行治疗，包括力量、肌肉控制和协调能力受损。虽然可穿戴的机器人外骨骼对行走障碍的人有潜力，但之前的研究主要集中在通过动力辅助立即改善行走性能。该项目旨在了解可穿戴踝关节外骨骼交替辅助和抵抗是否比单独使用任何一种方法都能带来更大的行走改善。该项目的成果有可能改变多种条件下步行残疾的治疗方法。通过辅助机器人与工程的新课程，该项目旨在激励工科学生解决残疾人所面临的挑战，并改善以人为本的设计工程教育。本CAREER项目旨在开发一种基于适应性辅助和阻力混合应用的步态康复整体治疗框架，并将其应用于踝关节跖屈肌功能障碍的治疗。第一个目标是在不同程度的步行障碍中建立适应性跖屈肌辅助和抵抗的混合传递的基础知识。第二个目标是开发一个框架，通过使用整体性能指标来优化混合外骨骼疗法的长期交付，考虑到时空和神经肌肉的结果，以及一个人工神经网络，从参与者的反应中学习。第三个目标是验证混合优化框架与单独辅助和阻力训练的对比，并将混合外骨骼训练与标准步态训练进行比较。这个CAREER项目有望开拓长期人在环优化技术的发展，以提供神经肌肉功能和行走能力的持久改善。该项目将建立疾病严重程度与可穿戴辅助设备和抵抗力之间相互作用的基础知识。所开发的策略将是可推广的，使其他研究人员能够将该框架应用于不同类型的控制算法、设备、关节和患者群体。辅助机器人与工程新课程（CARE）将作为该项目的一部分开发，包括先进的机器人课程模块、残疾人设计顶点项目和K-12经验。预计参与CARE的学生将对身体残疾人士的需求有更好的了解，这将转化为有效的工程解决方案，并产生更多积极、有洞察力和有影响力的工程学生和专业人士。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This NSF Faculty Early Career Development (CAREER) project seeks to advance the scientific study of walking rehabilitation and pioneer a novel wearable rehabilitation strategy. There is a critical need for treatments that address the root causes of walking disability, including impaired strength, muscle control, and coordination. While wearable robotic exoskeletons hold potential for individuals with walking disabilities, prior research has focused on immediate improvements in walking performance from powered assistance. This project seeks to understand if alternating assistance and resistance with a wearable ankle exoskeleton will elicit greater improvements in walking than either approach alone. The outcomes of this project have the potential to transform the treatment of walking disabilities across a wide range of conditions. Through a new curriculum in assistive robotics and engineering, this project aims to motivate engineering students to address the challenges experienced by individuals with disabilities and improve engineering education on human-centered design.The purpose of this CAREER project is to develop a holistic treatment framework for gait rehabilitation based on the hybrid application of adaptive assistance and resistance and apply it to the treatment of ankle plantar-flexor dysfunction. The first objective is to establish foundational knowledge on the hybrid delivery of adaptive plantar-flexor assistance and resistance across different severities of walking impairment. The second objective is to develop a framework to optimize the long-term delivery of the hybrid exoskeleton therapy through the use of a holistic performance metric, accounting for both spatiotemporal and neuromuscular outcomes, and an artificial neural network to learn from participant responses over time. The third objective is to validate the hybrid optimization framework against training with assistance and resistance alone and compare hybrid exoskeleton training to standard gait training. This CAREER project is expected to pioneer the development of long-term human-in-the-loop optimization techniques to deliver lasting improvements in neuromuscular function and walking ability. This project will establish fundamental knowledge on the interplay between disease severity and wearable assistance and resistance. The strategies developed will be generalizable, enabling other investigators to apply this framework to different types of control algorithms, devices, joints, and patient populations. New Curriculum in Assistive Robotics and Engineering (CARE) will be developed as part of this project, incorporating advanced robotics course modules, design-for-disability capstone projects, and K-12 experiences. It is anticipated that the students involved in CARE will gain an improved understanding of the needs of people with physical disabilities, which will translate into effective engineering solutions, and result in more motivated, insightful, and impactful engineering students and professionals.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.