Control of Arm Posture and Movement Followoing Stroke

描述(由申请人提供)：项目摘要/摘要本项目分析了由于大脑中动脉闭塞导致的中风患者在伸展时姿势和运动的紊乱控制。先前的研究表明，对姿势和运动的控制都可能受到损害，并对残疾有重要影响。我们最近的工作表明，正常的触觉需要控制姿势和运动，这两种功能由不同的神经机制指定，准确性取决于两者之间的适应(学习)和协调。根据我们的初步观察，我们假设中风降低了恢复和放松平衡肌肉协同收缩的能力，而平衡肌肉协同收缩既是克服与高张症相关的肢体姿势偏差所需的，也是稳定手对抗工作空间中不稳定负荷所需的。我们进一步假设，卒中后的主要损害是由于肌肉共激活的不适当的缩放和时机，从而限制了手臂轨迹和位置控制的独立性。 使用平面机械臂和新颖的肌电生物反馈方法，Aim 1建议在以下方面描述与中风相关的变化：1)通过分级协同激活对抗肌肉来维持整个工作空间的姿势稳定的能力；2)不同水平协同激活的潜伏期和发展时间过程；3)在存在机械扰动的情况下，使用本体感觉反馈来抵消肢体位置调节过程中的反射异常。 目的2研究姿势和运动控制整合中与中风相关的变化。使用平面机器人，我们将：1)探索姿势和运动任务之间的学习迁移，评估两个控制器之间的耦合是否增加中风后，以及2)确定轨迹规划是否适应中风后，以考虑姿势调节的生物力学影响。 我们期望我们的研究结果最终能为中风后手臂功能的康复提供新的方法。我们预计，通过应用机器人和生物反馈方法，首先分别训练共激活、姿势和运动控制，然后将其结合起来，将促进手臂功能的改善。

DESCRIPTION (provided by applicant): Project Summary/Abstract This project analyzes disordered control of posture and movement during reaching in patients with stroke resulting from middle cerebral artery occlusion. Prior studies have shown that control of posture and movement may both be impaired, and contribute importantly to disability. Our recent work has shown that normal reaching requires control of both posture and movement, that these two functions are specified by different neural mechanisms, and that accuracy is dependent on adaptation (learning) and coordination between the two. Based on our preliminary observations, we hypothesize that stroke degrades the ability to recruit and relax the balanced muscle co-contractions needed both to overcome limb postural bias associated with hypertonia and to stabilize the hand against unsteady loads across the workspace. We further hypothesize that major impairment in reaching post-stroke arises from improper scaling and timing of muscle coactivation, thus limiting the independence of arm trajectory and position control. Using a planar robot arm and novel EMG biofeedback methods, Aim 1 proposes to characterize the stroke- related changes in: 1) the ability to maintain postural stability throughout the workspace via graded coactivation of antagonist muscles; 2) the latency and developmental time course of different levels of coactivation, and 3) the use of proprioceptive feedback to counteract reflex abnormalities during regulation of limb position in the presence of mechanical perturbations. Aim 2 examines stroke-related changes in the integration of posture and movement control. Using the planar robot we will: 1) explore transfer of learning between posture and movement tasks, assessing whether coupling between the two controllers increases post-stroke, and 2) determine whether trajectory planning adapts post-stroke to account for the biomechanical effects of posture regulation. We expect our results will ultimately lead to new approaches for rehabilitating arm function post-stroke. We anticipate that improvement in arm function will be promoted by applying robotic and biofeedback methods first to train coactivation, posture and movement control separately, then in combination.