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

使用机器人躯干支撑训练器 (TruST) 改善双侧脑瘫的坐姿控制和上肢功能

• 批准号: 10705411
• 负责人: Sunil K. Agrawal
• 金额: $ 5.93万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10705411
• 关键词: Adult; Affect; Bilateral; Cerebral Palsy; Child; Complex; Educational Activities; Head; Learning; Leisure Activities; Link; Mentorship; Motor; Motor Skills; Movement; Musculoskeletal Equilibrium; Neurologist; Performance; Posture; Recovery; Recovery of Function; Research Personnel; Robotics; Task Performances; Testing; Time; Training; Upper Extremity; Upper arm; Upper limb movement; arm; arm movement; design; experience; flexibility; improved; insight; motor learning; physical therapist; robot rehabilitation; skill acquisition; skills training; virtual; virtual environment; virtual reality; virtual reality headset

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.

项目总结/文摘