NRI: FND: Soft Wearable Robots for Injury Prevention and Performance Augmentation

NRI：FND：用于预防伤害和增强性能的软可穿戴机器人

• 批准号: 1830613
• 负责人: Hao Su
• 金额: $ 25万
• 依托单位: CUNY City College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830613&HistoricalAwards=false
• 关键词: NRI; FND; Soft; Wearable; Robots

Musculoskeletal disorders are a leading cause of injury among workers who are exposed to physical workloads, with overexertion in lifting causing over one-third of these injuries. Every year approximately $56 billion is lost due to lift related injuries. The emerging technologies of exoskeletons hold promising potential to reduce biomechanical loads, thereby preventing worker injury. The obstacles to widespread adoption of this technology, however, arise from discomfort due to excessive weight, restricted range of motion, and high-pressure concentration. This project seeks to explore a new design for wearable robots as ubiquitous co-robots to address these challenges. The proposed bio-inspired, soft, back-support exoskeletons will provide joint moment assistance, while being lightweight and unobtrusive. Our soft back-support exoskeleton consists of 1) a soft exoskeleton that is lightweight as its design architecture (bio-inspired, cable-driven mechanism) and actuation (high-torque density actuators) overcome the limitations of rigid exoskeletons (heavy, limit range of motion) and textile-based soft exosuits (medium weight, exert high pressure concentration on tissue); and 2) wearable sensors and its on-site estimation algorithms of biological joint moment to characterize and prevent injuries. The proposed exoskeleton presents a promising solution in assisting injury prevention and performance augmentation. In terms of its societal impact, it will improve the quality of life and work as well as address the social and economic impact of robots on our workers. Thus, it will have a direct massive gain to the economy, health, and welfare of our society.The goal of this project is to explore new research and design of soft wearable collaborative robots to minimize injuries of workers prone to fatigue and musculoskeletal disorders. The project will focus on 1) designing bio-inspired soft back-support exoskeletons which are hybrid wearable robots that combine the advantages of rigid exoskeletons and soft exosuits while minimizing their respective limitations; 2) exploring on-site estimation algorithms using wearable sensors to characterize the biological joint moments to detect fatigue onset; and 3) evaluating the performance of the exoskeletons and its effectiveness for injury prevention. The contributions of this research entail both engineering innovations including new design methodology and enabling technologies for soft robots, as well as scientific foundation and tools to understand human-robot interaction and biomechanics. 1) Advances in robotics. Soft exoskeleton design architecture will enable a new type of wearable robot design that is comfortable, powerful, and versatile. High torque density actuators will significantly reduce the weight and increase the transparency of exoskeletons. 2) Understanding of human-robot interaction. The investigation into lifting biomechanics and assistive control strategy will shed light on human-robot interactions and improve human and robot performances.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.

肌肉骨骼疾病是暴露于身体工作量的工人受伤的主要原因，抬高造成超过三分之一的伤害的工作过度。每年由于相关伤害而损失约560亿美元。外骨骼的新兴技术具有减少生物力学负荷的有希望的潜力，从而防止工人受伤。然而，由于体重过多，运动范围和高压浓度引起的不适，因此广泛采用这项技术的障碍。该项目旨在探索可穿戴机器人的新设计，以解决这些挑战。拟议的生物启发的，柔软的，后支持外骨骼将提供联合力矩援助，同时轻巧且不引人注目。我们柔软的背部供体外部骨骼由1）组成，一种柔软的外骨骼组成，其设计架构（以生物启发，电缆驱动的机制）和致动（高扭矩密度执行器）的限制限制了刚性外骨架的局限2）可穿戴传感器及其在生物关节时刻的现场估计算法，以表征和防止受伤。拟议的外骨骼为有助于预防伤害和绩效增强提供了有前途的解决方案。就其社会影响而言，它将改善生活质量和工作的质量，并解决机器人对工人的社会和经济影响。因此，它将对我们社会的经济，健康和福利有直接的收益。该项目的目的是探索新的研究和设计柔软可穿戴协作机器人的新研究，以最大程度地减少容易发生疲劳和肌肉骨骼疾病的工人伤害。该项目将着重于1）设计以生物启发的软背支持外骨骼，这些外骨骼是混合可穿戴的机器人，可以结合刚性外骨骼和软外壳的优势，同时最大程度地限制其各自的限制； 2）使用可穿戴传感器探索现场估计算法，以表征生物关节矩，以检测疲劳发作； 3）评估外骨骼的性能及其对预防伤害的有效性。这项研究的贡献包括工程创新，包括新的设计方法和软机器人的启用技术，以及了解人类机器人互动和生物力学的科学基础和工具。 1）机器人技术的进步。柔软的外骨骼设计体系结构将启用一种舒适，功能强大且用途广泛的新型可穿戴机器人设计。高扭矩密度执行器将显着减轻重量并增加外骨骼的透明度。 2）了解人类机器人相互作用。对提升生物力学和辅助控制策略的调查将阐明人类机器人的相互作用并改善人类和机器人的表现。该奖项反映了NSF的法定任务，并通过使用该基金会的知识分子优点和更广泛的影响来审查标准，认为NSF的法定任务值得支持。

项目成果

Machine Learning Based Adaptive Gait Phase Estimation Using Inertial Measurement Sensors

使用惯性测量传感器进行基于机器学习的自适应步态相位估计

• DOI: 10.1115/dmd2019-3266
• 发表时间: 2019
• 期刊: 2019 Design of Medical Devices Conference
• 作者: Yang, Jianfu;Huang, Tzu-Hao;Yu, Shuangyue;Yang, Xiaolong;Su, Hao;Spungen, Ann M.;Tsai, Chung-Ying
• 通讯作者: Tsai, Chung-Ying

Spine-Inspired Continuum Soft Exoskeleton for Stoop Lifting Assistance

• DOI: 10.1109/lra.2019.2935351
• 发表时间: 2019-07
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Xiaolong Yang;T. Huang;Hang-ling Hu;Shuangyue Yu;Sainan Zhang;Xianlian Zhou;A. Carriero;Guang H. Yue;Hao Su

High-performance soft wearable robots for human augmentation and gait rehabilitation

• DOI: 10.1016/b978-0-12-818538-4.00001-0
• 发表时间: 2021-01-01
• 期刊: Soft Robotics in Rehabilitation
• 作者: Di Lallo, A.;Yu, S.;Su, H.
• 通讯作者: Su, H.