Bio-inspired Exoskeletons and Safety in Human-Exoskeleton Cooperation

人类运动的自然模式依赖于神经系统、肌肉和骨骼之间的相互作用。这些因素中的任何一个出现问题--可能是由于医疗条件、疾病或受伤--都可能导致行动受限。在这种情况下，人们可能会遵循物理治疗程序来恢复失去或改变的运动能力。目前，机器人和外骨骼被用于物理治疗，以帮助个人恢复到以前的功能水平，并帮助他们进行日常生活活动(ADL)。然而，这些机器人和外骨骼与人体解剖关节不对准，可能会导致使用者不适或受伤，影响康复治疗的成功。在这项研究项目中，将使用视频运动捕捉数据和肌肉骨骼计算机模拟来研究、记录和分析ADL期间的人体关节运动。分析后的人体运动模式将被用来启发生物外骨骼的设计，这种生物外骨骼能够模拟人类运动中涉及的复杂3D运动。然后，开发的仿生外骨骼将与传统的模仿人类关节的外骨骼进行比较。对比研究的结果将有助于促进生物外骨骼的设计和利用方面的知识，以提高医疗、工业和军事应用中人-外骨骼系统之间的协同作用。为了激励新一代和STEM教育，研究成果还将通过出版物、威奇托探索场所科学博物馆的展览和大学赞助的K-12学生夏令营与公众分享。此外，在大学层面，该小组将把拟议工作的研究成果整合到本科和研究生课程中，以激励学生进行系统研究，并通过在课堂上实施基于项目的学习(PBL)方法来减少辅助设备的概念性学习障碍。该项目的目标是研究外骨骼与人体匹配和对齐中涉及人类关节运动的参数之间的关联模型，以实现有效的人-外骨骼合作。传统上，外骨骼被设计成与人类关节的运动轴对齐，方法是为每个人类关节分配一个等效的外骨骼关节(例如肘部的铰链关节)，假设轴的位置可以准确知道，并且这样的固定轴存在于关节或关节集的运动范围内。不幸的是，情况并不总是如此。关节的复合运动使它们与外骨骼的对准变得更加困难，而不对准可能会对所连接的系统和潜在的人体解剖产生巨大的压力，从而导致对新的外骨骼设计策略的需求，这种策略允许独立于解剖测量和地标的复杂3D运动。为满足这一需要，研究计划分为四项任务。第一个任务是收集人类关节运动(手和手臂)中涉及的关节运动参数，同时执行所需的肢体轨迹。传统的运动捕捉系统(MOCAP)将与移动MOCAP系统相结合，移动MOCAP系统使用传感器来获得惯性测量，并将其无线传输到移动数据记录器，例如智能手机。组装的数据库将提供1)关于潜在的人类肢体运动的基本知识和2)识别和选择所需任务的功能性肢体运动的技术。第二个任务是使用肌肉骨骼软件应用程序来分析、建模和模拟人类关节运动中涉及的参数。手臂、手腕和手部肌肉骨骼模型的参数将使用OpenSim缩放模型工具进行缩放，以最适合实验测量的对象质量和标记位置。该模拟提供了1)在执行所需动作期间的肌力相互作用和关节反作用力，以及2)识别错位和装配挑战的来源的工具。第三个任务是基于与人体肢体期望轨迹相关的人体关节参数来研究仿生外骨骼。这项任务将提供：1)基于运动捕捉数据的人类肢体工作空间的几何和代数洞察\表示，以及2)机构拓扑及其工作空间的图集，以接近人类肢体工作空间的几何模式。第四项任务是制作原型，并研究参数与外骨骼拟合和比对之间的相关性。生物灵感原型将使用添加制造工艺制造，然后集成电子元件，以进行实时控制和反馈。受生物启发的外骨骼将与研究人员之前开发的基于3自由度关节的外骨骼进行比较。外骨骼将安装在轮椅上，用于对上肢活动度降低的人进行人体受试者测试，执行的ADL将提供诸如轨迹路径、肌电信号、FMG读数以及使用两种不同外骨骼机制的有效性和比较分析等数据集。收集的数据将用于1)为两个外骨骼独立开发相关模型，以及2)评估每个外骨骼设计的干预程度(基于生物启发方法的基于任务的方法和基于关节对关节对齐的设计方法)。该项目由残疾和康复工程(DARE)计划和既定的激励竞争研究计划(EPSCoR)共同资助。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。

The natural patterns of human movement depend on interactions between the nervous system, muscles and skeleton. A problem with any of these elements--perhaps due to medical conditions, illnesses or injuries--can lead to movement limitations. In such cases, people may follow physical therapy procedures to recover the loss or change in movement ability. Currently, robots and exoskeletons are used in physical therapy to help individuals return to their prior level of functioning and to assist them to do activities-of-daily living (ADL). However, these robots and exoskeletons do not align with the human anatomical joints, which can result in discomfort or injury to the user and affect the success of the rehabilitation therapy. In this research project, human joint motions during ADL will be studied, recorded, and analyzed using video motion capture data and musculoskeletal computer simulations. The analyzed human motion patterns will be used to inspire the design of bio-exoskeletons that are capable of mimicking the complex 3D motions involved in human movement. The bio-inspired exoskeletons developed will then be compared to the traditional exoskeletons designed to mimic a human joint. The outcome of the comparison study will help to advance the knowledge in the design and utilization of bio-exoskeletons for the improved synergy between the human-exoskeleton systems in medical, industrial, and military applications. To inspire the new generation and STEM education, findings will also be shared with the public via publication, exhibitions at the Exploration Place science museum in Wichita, and university sponsored summer camps for K-12 students. Additionally, at the university level, the team will integrate research findings from the proposed work into the undergraduate and graduate courses to motivate students to perform systematic research and to reduce conceptual learning barriers of assistive devices through the implementation of Project-Based-Learning (PBL) approaches in the classroom.The objective of this project is to investigate a correlation model between parameters involved in human joint movements in the fitting and alignment of exoskeletons to a human body for an effective human-exoskeleton cooperation. Traditionally, exoskeletons are designed to align with the human joint axes of motion by assigning each human joint with an equivalent exoskeleton joint (e.g. a hinge joint for the elbow) that assumes that the location of the axis can be accurately known, and that such a fixed axis exists for the range of motion of the joint or set of joints. Unfortunately, this is not always the case. The compound motion of joints makes their alignment with an exoskeleton more difficult and misalignment can create large stresses on the attached systems and underlying human anatomy, giving rise to the need for novel exoskeleton design strategies that permit the complex 3D motions independent of anatomical measures and landmarks. To address this need, the Research Plan is organized under four tasks. The FIRST Task is to collect joint movement parameters involved in human joint movements (hand and arm) while performing desired limb trajectories. Conventional motion capture systems (MoCap) will be combined with a mobile MoCap system that uses sensors to obtain inertial measurements that are communicated wirelessly to a mobile data logger, e.g., a smartphone. The data base assembled will provide 1) fundamental knowledge on the underlying human limb motion and 2) techniques to identify and select functional limb motion for a desired task. The SECOND Task is to analyze, model, and simulate the parameters involved in human joint movements using a musculoskeletal software application. The parameters of an arm, wrist, and hand musculoskeletal model will be scaled using the OpenSim Scale Model tool to best fit the experimentally measured subject mass and marker positions. The simulations provide 1) muscle force interaction and joint reaction forces during the execution of the desired motions and 2) a tool for the identification of sources for misalignment and fitting challenges. The THIRD Task is to investigate bio-inspired exoskeletons based on the related human joint parameters related to the desired trajectory of the human limb. This task will provide: 1) geometrical and algebraic insight\representation of the human limb workspace based on the motion captured data and 2) an atlas of mechanism topologies and their workspaces to closely approximate the geometrical pattern of the human limb workspace. The FOURTH Task is to prototypes and investigate the correlation between parameters and exoskeleton fitting and alignments. A bio-inspired prototype will be fabricated using an additive manufacturing process followed by integration of electronic components for real-time control and feedback. The bio-inspired exoskeletons will be compared to a 3 DOF joint-based exoskeleton previously developed by the investigators. The exoskeletons will be mounted on a wheelchair and be used in human subject testing on persons with reduced upper limb mobility, and the ADL performed will provide datasets such as trajectory path, EMG signals, FMG readings, and effectiveness and comparative analysis using the two different exoskeleton mechanisms. Data collected will be used to 1) develop a correlation model for the two exoskeletons independently and 2) to assess the intervention of each of the exoskeleton designs (the task-based approach based on the bioinspired method and joint-to-joint alignment-based design approaches).This project is jointly funded by the Disabilities and Rehabilitation Engineering (DARE) program and the Established Program to Stimulate Competitive Research (EPSCoR).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.