Control of Arm Posture and Movement Followoing Stroke

该项目分析了中风患者伸手过程中姿势和运动的紊乱控制。 由大脑中动脉闭塞引起。先前的研究表明，控制姿势和运动 两者都可能受损，并对残疾有重要影响。我们最近的研究表明，正常的到达 要求同时控制姿势和动作，这两种功能由不同的神经指定 这种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招募和放松 平衡肌肉协同收缩既需要克服与高张力相关的肢体姿势偏差，也需要 以稳定手以抵御工作空间中的不稳定载荷。我们进一步假设少校 达到卒中后的损害是由于肌肉协同激活的不适当的缩放和时机，因此限制了 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，目标1提出了表征与中风相关的 变化：1)通过分级协同激活在整个工作空间中保持姿势稳定的能力 2)不同程度共激活的潜伏期和发育时程；3) 本体感觉反馈在肢体位置调节中的应用 存在机械扰动。 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)探索姿势和动作任务之间的学习迁移，评估 两个控制器之间的耦合增加了冲程后，以及2)决定了轨迹规划 适应中风后的姿势调节的生物力学效应。 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 预计首先应用机器人和生物反馈方法将促进手臂功能的改善 将协同激活、姿势控制和动作控制分开训练，再结合起来训练。

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.