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).

这个协作项目将利用跨学科和综合性的脊柱外骨骼 平台团结迅速发展科学和工程领域，以提高知识和 在其领域和跨不同领域的理解。最先进的外骨骼缺乏人类 适应性和任务多功能性减轻工人的伤害。此外，人类背部的解剖结构 针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 需要减少至少三种力中的至少一个（也不增加其他力），包括梯形脊柱 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。这个项目将1）发展 力学引导的脊柱螺旋软外骨骼，2）了解高保真的肌肉骨骼模型 人脊柱及其对外骨骼的反应，3）研究基于学习的最佳控制 减少肌肉骨骼关节载荷，因此最终减轻了对工人的后背损伤。我们的 多学科团队由机器人技术专家（Hao Su博士）组成，计算生物力学（博士 凯瑟琳·索尔（Katherine Saul）和基于学习的最佳控制（郑 - 董博士）将采取收敛性 使用由脊柱组成的生物启发的软外骨骼协助多个关节的方法 和臀部模块，用于预防执行起重任务的工人（包括蹲下和 弯曲姿势）。