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

项目总结/摘要 中重度双侧脑性瘫痪（CP）患儿躯干及上肢发育不良 这对她们参与休闲和教育活动产生了负面影响。活动- 具有适当任务进展的熟练上肢运动任务的定向训练已经被 对上肢恢复和姿势控制有效。 我们之前已经证明，在躯干处应用机器人辅助可以帮助儿童 与CP获得独立的坐姿和改善头躯干手臂协调。该提案寻求 开发和测试复杂的虚拟任务，显示在屏幕上或头戴式虚拟 现实显示，这是专门设计的训练姿势控制和上肢运动。 这些任务将与我们的机器人躯干支持平台集成到培训中。这些任务将 精心设计，使其具有高度可重复性和可扩展性，并允许分析 运动以及这种变化如何影响性能。运动变异性及其变化是 与运动策略选择、技能获得和运动学习密切相关。结果将 用于探讨机器人姿势辅助和任务练习对姿势和 上肢任务表现、运动变异性和表现改善。 复杂的姿势和上肢任务，让孩子灵活地完成 物理治疗师经常使用任务来训练运动技能，但很难分析。示例 包括投球和接球、到达移动目标以及垒块。的 开发的虚拟任务将允许研究CP儿童如何执行这些任务， 不同种类的姿势帮助和时间。结果将提供洞察如何 姿势控制对上肢功能的影响以及上肢新任务的运动学习 在CP中进行练习。这些发现可以指出新的辅助和培训策略， 促进功能恢复。 这项建议的第一个目的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 儿童CP第二个目的是研究健康的成年人和儿童如何与CP 改善他们的姿势控制和上臂运动与实践这些任务在一个多 会话训练。康复机器人专家Sunil Agrawal博士，康复机器人专家维克托Santamaria博士， 物理治疗师和经验丰富的姿势控制研究员，杰森博士卡梅尔，一个 神经学家和神经科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.