Improving seated postural control and upper extremity function in bilateral CP with a robotic Trunk-Support-Trainer (TruST)

项目摘要/摘要 中重度双侧脑性瘫痪患儿躯干和上肢功能不佳 这对他们参与休闲和教育活动产生了负面影响。练习- 针对熟练的上肢运动任务进行了适当的任务进度训练 证明对恢复上肢和姿势控制有效。 我们之前已经证明，在后备箱应用机器人辅助有助于儿童 使用CP可以获得独立的坐姿，改善头-躯干-手臂的协调性。这项提议旨在 开发和测试复杂的虚拟任务，显示在屏幕或头戴式虚拟设备上 现实展示，这是专门为训练姿势控制和上肢运动而设计的。 这些任务将被整合到我们的机器人后备箱支持平台的培训中。这些任务将 精心设计为高度可重复性、可伸缩性，并允许分析 以及这种可变性如何影响性能。运动变异性及其变化是 与运动策略选择、技能获取和运动学习密切相关。结果将会是 用于探讨机器人姿势辅助和任务练习对姿势和运动能力的影响 上肢任务性能、运动变异性和性能改进。 复杂的姿势和上肢任务，允许儿童灵活地完成 任务经常被理疗师用来训练运动技能，但很难分析。示例 包括投球和接球，到达移动的目标，和阻挡堆叠。这个 开发的虚拟任务将允许研究患有CP的儿童如何执行这些任务 随着时间的推移，不同类型的姿势辅助。这些结果将为我们提供关于如何 姿势控制对上肢功能和新上肢任务运动学习的影响 在CP中练习时发生。这些发现可能会指出新的辅助和培训策略 促进功能恢复。 这项提议的第一个目标是发展这些虚拟姿势和上肢训练 任务，并探索机器人姿势辅助如何影响健康成人受试者的表现 以及患有脑性瘫痪的儿童。第二个目标是研究健康的成人和患有CP的儿童如何 通过练习这些任务来提高他们的姿势控制和上臂动作 课时训练。苏尼尔·阿格拉瓦尔博士，康复机器人专家，维克多·桑塔玛利亚博士， 理疗师和经验丰富的姿势控制研究员杰森·卡梅尔博士， 神经学家和神经学家将为该项目提供指导和指导。

Project Summary/Abstract Children with moderate-to-severe bilateral cerebral palsy (CP) have poor trunk and upper limb control which negatively impacts their participation in leisure and educational activities. Activity- oriented training of skilled upper limb motor tasks with appropriate task progression has been shown to be effective for recovery of upper limb and postural control. We have previously shown that robotically applied assistance at the trunk helps children with CP gain independent sitting and improve head-trunk-arm coordination. This proposal seeks to develop and test complex virtual tasks, displayed on a screen or a head-mounted virtual reality display, that are specifically designed to train postural control and upper limb movements. The tasks will be integrated into training with our robotic trunk support platform. These tasks will be carefully designed to be highly repeatable, scalable, and allow for analysis of variability in movements and how this variability affects performance. Motor variability and its changes are closely linked to motor strategy selection, skill acquisition, and motor learning. The results will be used to explore the effect of robotic postural assistance and task practice on postural and upper limb task performance, movement variability, and performance improvements. Complex postural and upper limb tasks that allow the child flexibility in accomplishing the task are often used by physical therapists to train motor skills but are hard to analyze. Examples include ball throwing and catching, reaching to a moving target, and block stacking. The developed virtual tasks will allow study of how children with CP perform these tasks with different kinds of postural assistance and over time. The results will provide insight on how postural control influences upper limb function and how motor learning of new upper limb tasks occurs with practice in CP. These findings could point to new assistive and training strategies to promote recovery of function. The first aim of this proposal is to develop these virtual postural and upper limb training tasks and explore how robotic postural assistance affects performance in healthy adult subjects and children with CP. The second aim is to study how healthy adults and children with CP improve their postural control and upper arm movements with practice of these tasks in a multi- session training. Dr. Sunil Agrawal, an expert in rehabilitation robotics, Dr. Victor Santamaria, a physical therapist and experienced postural control researcher, and Dr. Jason Carmel, a neurologist and neuroscientist, will provide guidance and mentorship on the project.