CAREER: Modeling Time Invariances in Human Motor Coordination for Robot-Assisted Rehabilitation

机器人辅助康复可以增强和加速脑损伤（如中风）后的运动控制恢复。大多数现有的康复方法和支持它们的建模工作主要集中在产生受控运动所需的力量上，实际上不强调在运动学水平上发生的规划。全面了解运动学在协调中的作用有助于诊断缺陷所在的水平，然后在该水平上进行重点治疗。在这个项目中，PI将基于输出空间和控制空间之间的基本时不变运动映射，制定并实验验证人类运动协调的统一连贯模型。受传统上应用于机构综合的曲率理论的启发，这种映射提供了对运动的优雅描述。通过这种新颖的方法，PI将试图证明将运动学几何与基于时间的手臂运动轨迹跟踪解耦，可以得到与实验数据一致的紧凑的内部路径规划模型。这项工作将进一步证明，类似紧凑的内部动态模型为电机控制的有效制定提供了额外的一层。要开发的内部运动学和动力学模型将能够在运动学水平、动力学水平以及通过两者的相互作用来研究优化机制。为了在实验上验证该模型，PI将开发一个驱动但可反向驱动的平面x-y工作台，该工作台在整个工作空间内具有均匀的表观端点惯性。该设备既可以进行模型验证实验，也可以作为新型机器人辅助康复设备的第一个原型，用于临床利用从建模工作中获得的知识。PI将与他所在机构的物理治疗部门和物理医学和康复部门的同事合作，根据研究结果开发和评估新的诊断和康复技术，以实施新设备。更广泛的影响：随着医疗成本的上升和人口老龄化导致中风人数的增加，机器人辅助康复可能会对社会产生越来越大的影响。在理解人类运动协调的基础上，这项研究将影响运动、神经控制假肢、数字人体建模和机器人控制等领域。研究者将把这项研究整合到他的教育活动中，有两个重点：增加学生对运动学和动力学在人体运动协调中的重要性的理解；提高学生对机械系统中物理运动的内在形象化能力。这些活动将包括修改一门必修的本科运动学课程，一门选修的本科产品设计课程，以及两门研究生运动学课程，以结合研究结果。此外，将为所有学术单位的学生编写一个讨论会课程，以便更广泛地传播这项工作。PI将与俄亥俄州立工程学院（Ohio State College of Engineering）的其他四位教员一起，为女性和少数族裔高中生组织为期一周的工程夏令营。PI将为夏令营创建两个模块：一个与人体运动协调有关，学生将使用项目中开发的x-y表进行实验；一个是关于机械系统中运动的可视化。

Robot-assisted rehabilitation can enhance and speed motor control recovery following brain injury such as stroke. Most existing rehabilitation approaches and modeling work supporting them focus primarily on the forces required to generate controlled movements, in effect deemphasizing planning that occurs at a kinematic level. A thorough understanding of the role of kinematics in coordination is needed to help diagnose the level at which deficiencies lie, and then focus treatment at that level. In this project, the PI will formulate and experimentally validate unified, coherent models of human motor coordination based on a foundational time-invariant, kinematic mapping between the output space and the control space. Inspired by curvature theory, which is traditionally applied to mechanism synthesis, such a mapping provides an elegant description of motion. With this novel approach, the PI will seek to demonstrate that decoupling the kinematic geometry from the time-based trajectory tracking of arm motion leads to a compact internal model of path planning consistent with experimental data. The work will further demonstrate that a similarly compact internal dynamic model provides an additional layer for an efficient formulation of motor control. The internal kinematic and dynamic models to be developed will enable investigation of optimization mechanisms at the kinematic level, the dynamic level, and through mutual interaction of the two. In order to experimentally validate this model, the PI will develop an actuated, but back-drivable, planar x-y table that has uniform apparent endpoint inertia throughout its workspace. This device will both enable the model validation experiments and serve as a first prototype for a new robot-assisted rehabilitation device that can be used to clinically leverage the knowledge gained from the modeling effort. The PI will collaborate with colleagues in his institution's Physical Therapy Division and Physical Medicine and Rehabilitation Department to develop and evaluate new diagnostic and rehabilitation techniques that implement the new device based on the findings.Broader Impacts: Robot-assisted rehabilitation is likely to have an increasingly significant impact on society as health care costs rise and the number of strokes increases with population aging. Grounded in understanding human motor coordination, this research will impact the fields of locomotion, neurally controlled prosthetics, digital human modeling, and robot control. The investigator will integrate this research into his educational activities with two foci: increasing student understanding of the significance of kinematics and dynamics in human motor coordination; and enhancing student ability to internally visualize physical movement in mechanical systems. These activities will involve modifications to a required undergraduate kinematics course, an elective undergraduate product design course, and two graduate kinematics courses to incorporate the results of the research. Additionally, a seminar course for students from all academic units will be developed to more broadly disseminate the work. In conjunction with four other faculty in the Ohio State College of Engineering, the PI will organize a weeklong engineering summer camp for women and minority high school students. The PI will create two modules for the camp: one related to human motor coordination in which the students will conduct experiments using the x-y table developed in the project; and one related to visualization of motion in mechanical systems.