Collaborative Research: Towards Task-Agnostic and Device-Agnostic Ankle Exoskeleton Control for Mobility Enhancement

外骨骼在改善或增强人类机动性方面具有巨大的潜力。然而，尽管最近的研究表明，这会对步行等容易定义的任务产生影响，但研究人员往往忽略了日常生活中必要的更复杂的动作，比如在厨房里拖着脚走，弯腰拿起背包，或者在车里上下车。因此，外骨骼目前不能在高度有限的任务范围之外提供帮助，甚至可能降低在这些更复杂任务中的表现。此外，它们必须在特定主题的基础上进行调整，以获得足够的性能，从而阻碍广泛采用这些设备，并使许多人无法访问这些设备。该项目旨在通过利用可穿戴式传感和机器学习方面的最新进展来彻底改变下肢外骨骼领域。拟议的研究涉及将传感器读数映射到外骨骼辅助，并要求外骨骼佩戴者收集运动数据，执行广泛的任务。其目标是使外骨骼能够帮助完成所有可能的日常生活任务，增加其实用性和可获得性，供更广泛的人使用。这与NSF促进国民健康和福利的使命是一致的，因为这项新技术将显著提高未来的机动性和独立性，特别是在老龄化期间和有神经肌肉缺陷的个人。该项目将开源其数据集和深度学习模型，通过使其他研究人员能够在我们的进步基础上再接再厉，进一步推动该领域的技术创新来促进科学进步。最后，该项目通过与生物力学和机器人相关的外联活动支持教育和多样性，将少数族裔服务的高中的学生带到东北大学和佐治亚理工学院，进行可穿戴机器人的动手演示和比赛。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Exoskeletons have tremendous potential to improve or augment human mobility. However, despite recent work showing the impact on easily defined tasks such as walking, researchers have tended to ignore the more complex maneuvers that are necessary in daily life, such as shuffling in the kitchen, bending to pick up a backpack, or transitioning in and out of a vehicle. Accordingly, exoskeletons are currently incapable of assisting beyond a highly limited range of tasks and may even reduce performance in these more complex tasks. Further, they must be tuned on a subject-specific basis for adequate performance, hindering broad adoption and leaving the devices inaccessible for many people. This project aims to revolutionize the field of lower limb exoskeletons by leveraging recent advancements in wearable sensing and machine learning. Proposed research involves mapping sensor readings to exoskeleton assistance and requires collecting motion data exoskeleton wearers performing a wide range of tasks. The goal is to make exoskeletons capable of assisting with all possible tasks of daily living, increasing their utility and accessibility for a broader range of people. This is aligned with NSF's mission to advance national health and welfare, as this new technology will significantly improve mobility and independence in the future, particularly during aging and for individuals with neuromuscular deficits. This project will open-source its datasets and deep learning models, promoting the progress of science by enabling other researchers to build upon our advances and further drive technological innovation in this domain. Finally, this project supports education and diversity through outreach events related to biomechanics and robotics, bringing students from minority-serving high schools to Northeastern University and Georgia Tech for hands-on demos and competitions with wearable robotics.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.