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Do Robotic and Non-Robotic Arm Movement Training Drive Motor Recovery after Stroke by a Common Neural Mechanism? Experimental Evidence and a Computational Model

机译:机器人和非机器人手臂运动训练训练过于普通神经机制后冲程后的电动机恢复吗?实验证据和计算模型

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Different dose-matched, upper extremity rehabilitation training techniques, including robotic and non-robotic techniques, can result in similar improvement in movement ability after stroke, suggesting they may elicit a common drive for recovery. Here we report experimental results that support the hypothesis of a common drive, and develop a computational model of a putative neural mechanism for the common drive. We compared weekly motor control recovery during robotic and unassisted movement training techniques after chronic stroke (n = 27), as assessed with quantitative measures of strength, speed, and coordination. The results showed that recovery in both groups followed an exponential time course with a time constant of about 4-5 weeks. Despite the greater range and speed of movement practiced by the robot group, motor recovery was very similar between the groups. The premise of the computational model is that improvements in motor control are caused by improvements in the ability to activate spared portions of the damaged corticospinal system, as learned by a biologically plausible search algorithm. Robot-assisted and unassisted training would in theory equally drive this search process.
机译:不同剂量匹配的上肢康复训练技术,包括机器人和非机器人技术,可以导致行程后运动能力的提高,表明它们可能引起康复的共同驱动器。在这里,我们报告了支持共同驱动器的假设的实验结果,并为共同驱动器开发推定神经机制的计算模型。我们在慢性中风(n = 27)后的机器人和非译备运动训练技术期间将每周运动控制恢复进行比较,如测量的强度,速度和协调的定量测量。结果表明,两组中的恢复遵循指数时间课程,时间常数约为4-5周。尽管机器人组练习的速度范围和速度较大,但组之间的电机恢复非常相似。计算模型的前提是通过在生物合理的搜索算法的学习中,通过改善电动机控制的改进是由激活损坏的皮质系统的施工部分的能力的改进引起的。理论上,机器人辅助和无批准的培训将同样推动此搜索过程。

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