SCH: Spine-Hip Exoskeletons with Learning-Based Optimal Control for Low Back Pain Alleviation

SCH：具有基于学习的最佳控制的脊柱-髋部外骨骼，可缓解腰痛

• 批准号: 10816884
• 负责人: Hao Su
• 金额: $ 30万
• 依托单位: NORTH CAROLINA STATE UNIVERSITY RALEIGH
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10816884
• 关键词: Algorithms; Anatomy; Ankle; Area; Artificial Intelligence; Back; Biological; Biological feedback; Biomechanics; Caregivers; Data; Development; Disabled Persons; Education; Educational Curriculum; Elderly; Electrical Engineering; Engineering; Ensure; Future; Healthcare; Hip region structure; Human; Injury; Joints; Journals; Knee; Knowledge; Learning; Lifting; Low Back Pain; Lower Back Injury; Machine Learning; Mechanics; Methods; Modeling; Muscle; Musculoskeletal; Nature; Persons; Posture; Prevention; Productivity; Publishing; Rehabilitation device; Research; Research Training; Robot; Robotics; Safety; Science; Signal Transduction; Soldier; Students; Torque; Uncertainty; Vertebral column; Work; Workplace; career; cost; cost effective; design; doctoral student; exoskeleton; exosuit; experimental study; fire fighter; human-robot interaction; improved; interest; joint loading; mobile sensor; multidisciplinary; programs; response; simulation; spine bone structure; student training; success; symposium; time use; undergraduate student

This collaborative project will leverage the spine-hip exoskeleton, an interdisciplinary and integrative platform uniting rapidly advancing areas of science and engineering to advance knowledge and understanding within its field and across different fields. The state-of-the-art exoskeletons lack human adaptability and task versatility for injury mitigation of workers. Moreover, the anatomy of the human back presents unique challenges for the design and control of wearable robots. Thus spine exoskeletons are required to reduce at least one of three forces (also not increase other forces), including erector spinae muscle force and lumbar vertebral compressive and shear forces. This necessitates new solutions for robot design, modeling, and control to achieve all objectives. This project will 1) develop mechanics-guided spine-hip soft exoskeletons, 2) understand the high-fidelity musculoskeletal model of the human spine and its response to exoskeletons, and 3) investigate learning-based optimal control to reduce musculoskeletal joint loadings thus ultimately mitigate low back injuries to workers. Our multidisciplinary team consisting of experts in robotics (Dr. Hao Su), computational biomechanics (Dr. Katherine Saul), and learning-based optimal control (Dr. Zhong-Ping Jiang) will take a convergent approach to assist multiple joints using a bio-inspired powered soft exoskeleton composed of the spine and hip modules for low back pain prevention of workers who conduct lifting tasks (including squat and stoop postures).

这个合作项目将利用脊柱髋外骨骼，一个跨学科和综合的 平台联合迅速发展的科学和工程领域，以促进知识和 了解其领域内和不同领域之间的理解。最先进的外骨骼缺乏人类 减轻工人伤害的适应性和任务多样性。此外，人体背部的解剖结构 对可穿戴机器人的设计和控制提出了独特的挑战。因此，脊柱外骨骼是 需要减少至少三个力之一（也不增加其他力），包括竖脊肌 肌肉力和腰椎压缩力和剪切力。这需要新的解决方案， 机器人设计、建模和控制，以实现所有目标。该项目将1）开发 力学指导的脊柱髋关节软外骨骼，2）了解高保真的肌肉骨骼模型， 人体脊柱及其对外骨骼的反应，以及3）研究基于学习的最优控制， 减少肌肉骨骼关节负荷，从而最终减轻工人的腰部损伤。我们 由机器人专家（苏浩博士），计算生物力学（苏博士）， 凯瑟琳扫罗）和基于学习的最优控制（蒋忠平博士）将采取收敛 使用由脊柱组成的生物启发动力软外骨骼来辅助多个关节的方法 和髋关节模块，用于预防进行举重任务（包括蹲下和 弯腰姿势）。